The New Method for Evaluating the Advanced Treatment Effect of Limestone Aquifers in the Roof and Floor of Deep Coal Seam Mining

The New Method for Evaluating the Advanced Treatment Effect of Limestone Aquifers in the Roof and Floor of Deep Coal Seam Mining | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The New Method for Evaluating the Advanced Treatment Effect of Limestone Aquifers in the Roof and Floor of Deep Coal Seam Mining Yanbo Hu, Jingzheng Jiang, Gang Zheng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4969049/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The text discusses a new method for evaluating the effectiveness of advanced regional treatment of limestone aquifers in coal mining. Since the implementation of the "Technical specification for advanced regional treatment of limestone aquifer under coal seam" in early 2024, an effective evaluation method has been lacking. To fill this gap, this study is based on data from surface-directed multi-branch horizontal wells for advanced regional treatment. Using methods such as calculating the water-blocking capacity of the aquifer, statistical analysis of grouting data, and GIS model processing, a multi-factor evaluation model that affects the effectiveness of water hazard governance was constructed, and thematic distribution data of various influencing factors in the research area were obtained. Through mathematical modeling and GIS technology, various factor data were processed to form zoning evaluation data for the effectiveness of grouting transformation. This article proposes an innovative method for evaluating the effectiveness of advanced regional treatment using surface-directed multi-branch horizontal wells by comprehensively utilizing qualitative and quantitative evaluation modes, combined with supplementary exploration data from underground. Experimental results have shown that the evaluation system is effective and provides an important reference for research on water hazard prevention and control in deep coal seam mining. water damage control deep mining GIS treatment effect Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 1 Introduction During more than 40 years of rapid development since the reform and opening up, coal energy has played a crucial role in China's economic construction (Wang et al. 2021 ). However, with the extensive and rapid exploitation of coal resources, the shallow resources in the North China region have been almost exhausted, forcing mining enterprises to shift towards deep mining. Deep mining faces the challenges of "three highs and one disturbance" (high ground stress, high temperature, high water pressure, and intense mining disturbance), with the threat of high-pressure water being particularly severe (Wu et al. 2021 ; Hu et al. 2021 ). This high-pressure water not only increases the difficulty of extraction but also poses a significant threat to the safe production of mines (He et al. 2024 ). In recent years, continuous exploration has shown that the use of surface-directed multi-branch horizontal wells for advanced regional treatment of high-pressure aquifers has yielded promising results (Sun et al. 2021 ; Zhang et al. 2019 ). This technology can effectively reduce the threat of high-pressure water, thereby enhancing mine safety and production efficiency (Li et al. 2020 ). However, the "Technical Specification for Advanced Regional Treatment of Limestone Aquifers Under Coal Seams" was only implemented in early 2024. As of now, there is still no effective evaluation method to measure the actual effectiveness of these treatment measures. Zhao et al. ( 2023 ) studied the effectiveness of thin-layer limestone water prevention based on multi-branch horizontal drilling and grouting processes, showing significant improvement in the Taiyuan formation thin-layer limestone aquifers, with denser well placement leading to better results. Luo et al. ( 2022 ) constructed a precise "water stop plug" using stacked multi-branch horizontal wells for advanced treatment of karst collapse columns. Zhan et al. (2019) researched the application of surface-directed multi-branch horizontal wells in managing high-pressure aquifers, proposing practical procedures and effects of this technology. However, these studies mainly focus on the application of the technology itself, lacking systematic evaluation of the treatment effectiveness. In terms of high-pressure water hazard prevention, Wang et al. ( 2022 ) studied the water-blocking capacity of aquicludes, proposing a preliminary evaluation method based on this capacity. Wu et al. ( 2016 ) introduced a framework using scenario analysis combined with Bayesian networks to assess the probability of mine water inrush accidents. By setting different state combinations of scenario factors, they calculated and analyzed the probabilities of various mine water inrush scenarios, including typical and catastrophic ones. Wu et al. (2008, 2011 ) used the vulnerability index method and GIS technology to scientifically process data in coal mine water hazard prevention, providing new technical means for such research. Li et al (2021) proposed three water control modes and key technologies based on the water inrush coefficient and combined with the Ts-q method, forming a theoretical and technical system for water hazard prevention in the Huaibei mining area. Although these studies provide a theoretical basis for evaluation methods, they still have many shortcomings in practical applications, such as incomplete evaluation indicators and insufficient data processing precision. Given the shortcomings in the existing research on evaluating the effectiveness of advanced regional treatment of limestone aquifers under coal seams, this paper aims to propose a new method for scientifically evaluating the effectiveness of surface-directed multi-branch horizontal well advanced regional treatment. This study, based on data from surface-directed multi-branch horizontal well advanced regional treatment, utilizes methods such as aquiclude water-blocking capacity calculation, statistical analysis, and GIS model processing to establish a specific evaluation model for factors affecting water hazard treatment effectiveness, obtaining thematic distribution data of various influencing factors in the study area. Through mathematical modeling and GIS processing of various factor data, zoning evaluation data for the grouting transformation effectiveness were obtained. By combining qualitative and quantitative evaluation modes and supplementary underground exploration evaluations, this paper proposes a method for evaluating the effectiveness of advanced regional treatment using surface-directed multi-branch horizontal wells. This study is the first to propose the "Effectiveness Evaluation Method for Advanced Regional Treatment using Surface-Directed Multi-Branch Horizontal Wells," providing a new evaluation system for water hazard prevention in deep coal seam mining. Practical tests on several deep mining faces in the North China coalfields have proven the significant effectiveness of this evaluation system, providing scientific basis and technical support for coal mining enterprises in formulating and implementing water hazard prevention measures. Future research can be further deepened in the following aspects: (1) Expanding the research scope to other regions and different types of mines to verify the universality of this method. (2) Optimizing the evaluation model to enhance the accuracy and reliability of the evaluation results. (3) Promoting the technical application in more coal mining enterprises to improve the level of water hazard prevention in the coal mining industry. In conclusion, the results of this study not only provide strong support for water hazard prevention in deep coal seam mining but also offer new directions and ideas for related research fields. Through continuous improvement and widespread application, this method is expected to play an increasingly important role in coal mine water hazard prevention. 2 Overview of the Study Area 2.1 Overview of the Mining Area This study is based on the Zhaoguan Coal Mine of Shandong Energy Group. The Zhaoguan mine field is part of the Yellow River North Coalfield, located in the northwest of Shandong Province, covering an area of 59.2 km² with a mining elevation range of -200.0m to -1200.0m. The Yellow River flows along the southeast side of the mine field, providing convenient transportation. The area is flat, with a surface elevation generally between + 27.0m and + 32.0m. The ground level within the study area is lower than the riverbed of the Yellow River, making it prone to flooding during the rainy season. Figure 1 . Location Map of the Study Area The stratigraphic division of the Yellow River North Coalfield belongs to the Luxi stratigraphic subregion of the North China stratigraphic region. The Carboniferous-Permian system is unconformably overlain by Ordovician limestone. The Ordovician and Cambrian coal-bearing strata are exposed along the southern bank of the Yellow River from Changqing to Pingyin, forming a region of low to middle mountains and hills. The Carboniferous-Permian coal-bearing strata are well-developed and rich in coal resources, being covered by a considerable thickness of Quaternary and Neogene strata, forming a concealed coalfield. Figure 2 . Comprehensive Geological Columnar Section The coal-bearing strata of the mine field belong to the Taiyuan and Shanxi formations of the Carboniferous-Permian system, containing 16 coal seams in total. The Shanxi formation contains 4 coal seams, with only seams 2, 3, and 4 present in the mine field, and seam 4 being the only minable seam. The Taiyuan formation contains 12 coal seams, with 4 main minable seams (seams 7, 10, 11, and 13). Seam 13 is a stable coal seam, while seams 7, 10, and 11 are relatively stable, and seam 4 is unstable. Currently, the shallow resources have been exhausted. To continue production, preparations for mining the lower coal seams of the Taiyuan formation (seams 11 and 13) have been initiated. These seams face severe threats from the overlying fourth and fifth limestone aquifers and the underlying Xujiazhuang and Ordovician limestone aquifers. To ensure the safe mining of the lower coal seams, it is necessary to conduct advanced regional treatment of the direct and indirect water-bearing aquifers in the roof and floor of the coal seams (Fig. 2 ). This study aims to evaluate the treatment effectiveness based on the data from advanced regional treatment, ensuring safe mining. 2.2 Engineering Geological and Hydrogeological Conditions 2.2.1 Stratigraphic Structure The mine field is located in the central-western part of the Yellow River North Coalfield, being a fully concealed North China-type Carboniferous-Permian coalfield. The coal series are based on the Middle-Lower Ordovician strata, overlaid by the Benxi formation of the Middle Carboniferous, Taiyuan formation of the Upper Carboniferous, Shanxi formation of the Lower Permian, Lower Shihezi formation, Upper Shihezi formation of the Upper Permian, and the Neogene and Quaternary strata. The stratigraphic sequence from top to bottom is as follows: (1) Quaternary System: Thickness 65.00–106.00 m, average 89.70 m. The upper part consists of silt and loess deposited by the modern Yellow River, while the middle and lower parts are mainly sandy clay and clay. The base has an unstable layer of grey to yellow-brown gravel, which demarcates it from the Neogene, with an angular unconformity contact. (2) Neogene System: Thickness 125.90–252.10 m, average 191.60 m. Predominantly clay, with the upper part being variegated (purple-red, grey-green), and the middle to lower part green to grey-white. The base has an unstable gravel layer, predominantly limestone, with an angular unconformity overlying the Paleozoic. (3) Upper Permian Upper Shihezi Formation: Thickness 281.60 m. Mainly composed of variegated claystone, siltstone, and grey-white to grey-green sandstone. (4) Lower Permian Lower Shihezi Formation: Thickness 29.88–69.87 m, average 47.93 m. Mainly composed of grey-green sandstone and variegated claystone, locally interbedded with grey to dark grey claystone and siltstone. (5) Lower Permian Shanxi Formation: Thickness 66.20–113.90 m, average 97.62 m. This formation is one of the coal-bearing strata of the mine field, composed of medium to fine sandstone, siltstone, silty mudstone, mudstone, and coal seams. The coal seams are concentrated in the middle to lower parts, with only seams 3 and 4 present in the mine field, and seam 4 being locally minable. (6) Upper Carboniferous Taiyuan Formation: Thickness 142.80–174.65 m, average 163.23 m. This is the main coal-bearing formation of the mine field, composed of mudstone, siltstone, medium to fine sandstone, thin limestone layers, and coal seams. It includes five limestone layers, sequentially named from top to bottom as the first to fifth limestones. The formation contains 9 coal seams from top to bottom, namely seams 5, 6, 7, 8, 9, 10, 11, 13, and 14, with the main minable seams (seams 11 and 13) located below the fifth limestone. (7) Middle Carboniferous Benxi Formation: Thickness 20.66–56.05 m, average 32.42 m. Composed of mudstone, siltstone, grey claystone, limestone, sandstone, aluminous mudstone, and variegated claystone. The top contains an unstable limestone layer (sixth limestone); the middle contains the stable Xujiazhuang limestone, often with chert nodules and marine fossils, with a thickness of 7.70–12.40 m (average 10.03 m), serving as a good marker layer in the area; the bottom consists of aluminous mudstone and variegated claystone. The formation is in unconformable contact with the underlying Ordovician. (8) Middle-Lower Ordovician: Mainly composed of medium to thick-bedded limestone, often showing karst phenomena and well-developed fractures, mostly filled with calcite. It serves as an indirect water-bearing aquifer for the coal series, with a total thickness of about 800 m based on peripheral exposures. 2.2.2 Aquifers (1) Quaternary Aquifer: Composed of several layers of fine to coarse sand and gravel, loosely consolidated with good permeability and strong water-bearing capacity. The water level in the mine field is + 28.68 m, with a unit water inflow of 0.0044 L/s·m and a mineralization of 0.6508 g/L. (2) Neogene Aquifer: Contains clay in the sand layers, resulting in weak water-bearing capacity. The water level is + 28.65 m, with a unit water inflow of 0.0736 L/s·m and a mineralization of 1.4284 g/L. The Neogene layer is generally more than 150 m below seam 4, separated by the Shihezi and Shanxi formations, acting as an indirect water-bearing aquifer with no direct impact on coal seam mining. (3) Shanxi Formation Sandstone: Total thickness of 66.20–113.90 m, average 97.62 m. Most fine sandstone and siltstone have high clay mineral content and poorly developed fractures, resulting in poor water-bearing capacity. Only parts of the medium to coarse sandstone have developed joints and fractures, showing some water-bearing capacity. (4) Taiyuan Formation Limestones (First to Fifth): 1) First Limestone: Thickness 0–3.00 m, average 1.81 m. Unit water inflow of 0.2217 L/s·m, showing moderate karst fracture water-bearing capacity. The neighboring Qiujia Coal Mine has reported a maximum water discharge of 60 m³/h from the first limestone, causing flooding incidents. 2) Second Limestone: Thickness 0–2.55 m, average 1.78 m. Displays weak to moderate karst fracture water-bearing capacity. 3) Third Limestone: Thickness 0–3.70 m, average 1.95 m. Water-bearing capacity similar to the first and second limestones but slightly weaker. 4) Fourth and Fifth Limestones: Combined thickness of 0–13.58 m, average 6.58 m. The distance between the fourth and fifth limestones is 0–10.54 m, average 3.63 m, with thin mudstone intercalations. In the southern part of the mine field, the fourth and fifth limestones merge, while in the northeast, the distance increases, making them a single aquifer. Unit water inflow of 0.2997 L/s·m, showing moderate water-bearing capacity. The water level is + 30.2 m, with borehole measurements indicating significant water discharge. 5) Xujiazhuang Limestone: Locally developed small karst caves, thickness 0–12.40 m, average 8.49 m. Water level + 30.23–31.93 m, unit water inflow 0.0035–0.0085 L/s·m, mineralization 0.3333–2.358 g/L. 6) Ordovician Limestone: Dense and hard, with locally developed karst fractures. Water level + 29.45–+31.70 m, unit water inflow 0.0019–0.1517 L/s·m, mineralization 0.3146–3.0152 g/L, showing weak to moderate water-bearing capacity. 3 Geological engineering data for advanced regional governance The evaluation area for the ground directional drilling and grouting treatment of the Fourth and Fifth Limestones and Xujiazhuang Limestone water-bearing layers is located in the central part of the Seventh Mining Area. It includes the northern part of the eastern edge of the western wing, the southern edge of the western measurement of the eastern wing, the concentrated return airway of the upper section of -415, the concentrated track transport roadway of the upper section of -415, and the concentrated transport roadway of the upper section of -415. The total area of the evaluation zone is 32.98e4 m², with a perimeter of 3257.03 m, as shown in Fig. 5 − 1. Currently, the construction of the uphill section of the return airway, the uphill section of auxiliary transport, and the uphill section of transport in the Seventh Mining Area has been completed safely. Partial exposures of the Fourth and Fifth Limestones water-bearing layers have been revealed in the original trial mining face of the eastern wing of the Seventh Mining Area. Figure 3 . Plan View of the Study Area 3.1 Grouting Data for Xu Limestone Aquifer The evaluation area involves multiple drilling groups (D11, D12, original D2, etc.), with grouting modifications performed on the Xu Limestone layer of the 11th coal seam floor through ground directional drilling. This has achieved phased results. As of November 2023, the Xu Limestone drilling for D11, D12, and original D2 has been completed. The original D2 drilling group includes four branch drill holes, labeled: "original D2-1, original D2-2, original D2-3, original D2-4." The D11 drilling group consists of nine branch drill holes, labeled: "D11-1 to D11-9." The D12 drilling group consists of eight branch drill holes, labeled: "D12-1 to D12-8." This evaluation needs to assess the effectiveness of the completed branches in the Xu Limestone drilling groups D11, D12, and original D2. The total grouting volumes for D11, D12, and original D2 are 33,121 tons, 11,791 tons, and 1,124 tons, respectively (Fig. 4 ). Each branch successfully sealed small fractures and pores during the high-pressure grouting stage, providing a reliable geological foundation for subsequent coal seam mining. Figure 4 . Grouting Data Map for Xu Limestone Aquifer in the Study Area 3.2 Grouting Data for the Fourth and Fifth Limestone Aquifers The treatment of the fourth and fifth limestone aquifers involves six drilling groups within the study area: S1, S2, S4, S11, S12, and S14. The specifics for each drilling group are as follows: ① S1 Drilling Group: Contains five branch drill holes (S1-4, S1-5, S1-6, S1-7, S1-8) with a total grouting volume of 76,678 tons, including 43,703 tons of cement and 22,964 tons of fly ash. ② S2 Drilling Group: Contains five branch drill holes (S2-1, S2-4, S2-6, S2-7, S2-8) with a total grouting volume of 53,774 tons, including 28,007 tons of cement and 16,782 tons of fly ash. ③ S4 Drilling Group: Contains four branch drill holes (S4-1, S4-3, S4-4, S4-7) with a total grouting volume of 56,454 tons, including 34,295 tons of cement and 14,623 tons of fly ash. ④ S11 Drilling Group: Contains seven branch drill holes (S11-1 to S11-7) with a total grouting volume of 65,099 tons. ⑤ S12 Drilling Group: Contains six branch drill holes (S12-2, S12-3, S12-4, S12-5, S12-6, S12-7) with a total grouting volume of 24,976 tons, including 16,887 tons of cement and 8,089 tons of fly ash. ⑥ S14 Drilling Group: Contains one branch drill hole (S14-4) with a grouting volume of 13,389 tons, including 6,702 tons of cement and 324 tons of fly ash. For detailed grouting data, see Fig. 5 . Figure 5 . Grouting Data Map for fourth and fifth limestone aquifers in the Study Area 4 Methodology for evaluating the effectiveness of advanced regional governance 4.1 Statistical Analysis Method for Grouting Data Based on the data of ground directional near-horizontal drilling grouting projects in the fourth and fifth limestone aquifers and Xu limestone aquifers in the study area, statistical analysis is conducted on parameters such as final grouting pressure and grouting volume using the standard deviation method and box plot method. The analysis results can provide data support for the zoning system of grouting improvement evaluation. 4.2 Grading Evaluation Method Based on GIS Data This section outlines a grading evaluation method based on GIS data for the grouting improvement of the fourth and fifth limestone aquifers on the roof of the 11th coal seam and the Xu limestone aquifers on the bottom of the coal seam in the study area. (1) Data Analysis Coordinate data from ground directional drilling for grouting at each coordinate point during the grouting improvement are analyzed. The trajectory of grouting drillholes is used to compile statistical data for each grouting point. (2) Thematic Maps Creation Thematic maps for grouting pressure distribution areas and grouting volume distribution areas are created based on the grouting pressure and grouting volume data at each coordinate point. (3) Zoning Evaluation Thresholds are set for the grouting pressure distribution areas and grouting volume distribution areas to create zoning evaluation maps. (4) Scientific Evaluation Using GIS Overlay Buffer Algorithm The grouting effect in the study area is scientifically evaluated using the overlay buffer algorithm with GIS data layers. This method provides a systematic approach to evaluating the effectiveness of grouting in the study area, utilizing GIS data analysis and visualization techniques. 4.3 Establishment of the Preemptive Regional Governance Evaluation System An evaluation system for the effectiveness of preemptive regional governance based on ground directional drilling has been established by integrating key processes such as statistical model analysis and GIS modeling data processing, as illustrated in Fig. 6 . (1) Qualitative Evaluation After completing the preemptive regional governance project using ground directional drilling, the water-blocking capability of the coal seam floor aquitard is assessed. This can be done using methods such as the water inrush coefficient method (Dong et al. 2021 ) and the permeability coefficient method (Hu and Zhao 2021 ). Several exploratory drillholes can be arranged along the working face to conduct a qualitative evaluation (Hu et al. 2021 ). (2) Quantitative Evaluation Step 1: Create thematic maps for the grouting pressure distribution areas and the grouting volume distribution areas based on the coordinate points of the grouting improvement, grouting pressure, and grouting volume data. Step 2: Perform statistical analysis on the final ground grouting pressure and grouting volume data in the evaluation area using the standard deviation method and the box plot method to establish a threshold setting algorithm for the thematic map zoning. Step 3: Use the threshold setting algorithm for the thematic map zoning to conduct a zoning evaluation on the grouting improvement pressure distribution areas and the grouting volume distribution areas, resulting in the creation of a grouting volume distribution evaluation map and a final grouting pressure distribution evaluation map for the study area. Step 4: Perform overlay buffer analysis on the grouting volume distribution evaluation map and the final grouting pressure distribution evaluation map using GIS to ultimately create a thematic evaluation map of the grouting data for the study area. Step 5: If mine electrical prospecting data (Sun et al. 2016 ) or other drilling exploratory data are available, further overlay analysis can be conducted. Step 6: For anomalous areas identified in the grouting data evaluation thematic map, conduct underground drilling exploration (Hu et al. 2021 ). Set the threshold for single-hole water inflow, and carry out exploration and supplementary underground grouting simultaneously, ensuring full coverage within the working face area. Step 7: After all supplementary underground grouting meets the standards, trial mining can commence in the working face. Figure 6 . Flow chart for evaluating the effectiveness of advanced regional treatment of limestone aquifers on the roof and floor of deep mining coal seams 5 Results and Analysis 5.1 Statistical Analysis of Grouting Data 5.1.1 Statistical Analysis of Grouting Volume in Xu Limestone Layer Based on the standard deviation method for outlier analysis, the results show that the total grouting volume in the evaluation area is 63,450 m³, with an average value of 1,294.90 m³. The overall standard deviation is 2,791.73 m³, and the sample standard deviation is 2,763.10 m³. The upper limit for outliers is 9,584.20 m³, while the lower limit is negative. $$\:\sigma\:=\sqrt{\frac{\sum\:{（{X}_{i}-{\mu\:}）}^{2}}{N}}$$ Where σ represents the standard deviation, µ denotes the mean value, X stands for the individual grouting volume value, and N represents the number of data points. Upper limit = \(\:\mu\:\) + 3 \(\:\sigma\:\) Lower limit = \(\:\mu\:\) − 3 \(\:\sigma\:\) Based on the box plot analysis, the results indicate that the lower quartile Q1 of the total grouting volume data in the evaluation area is 80, the upper quartile Q3 is 579, and the interquartile range IQR is 499. The upper limit for outlier detection is 1327.5, and the lower limit is a negative value. Figure 7 . Analysis of Outlier Grouting Volumes in the Xu Limestone Evaluation Area Table 1 Statistical Summary of Grouting Volumes in Xu Limestone Table 1 Statistical Summary of Grouting Volumes in Xu Limestone NO. Grouting volume NO. Grouting volume NO. Grouting volume 1 1364.0 18 85.0 35 77.0 2 7636.0 19 380.0 36 159.0 3 8624.0 20 1049.0 37 65.0 4 6510.0 21 558.0 38 579.0 5 11787.0 22 387.0 39 63.0 6 80.0 23 265.0 40 785.0 7 222.0 24 276.0 41 560.0 8 828.0 25 10820.0 42 254.0 9 532.0 26 29.0 43 23.0 10 102.0 27 514.0 44 132.0 11 243.0 28 137.0 45 38.0 12 64.0 29 369.0 46 104.0 13 46.0 30 181.0 47 51.0 14 44.0 31 941.0 48 2414.0 15 58.0 32 42.0 49 3422.0 16 89.0 33 135.0 17 236.0 34 91.0 The statistical analysis of ground grouting volume data in the evaluation area, based on the standard deviation method and boxplot method, indicates that the dataset pertains to grouting reinforcement. A higher grouting volume value suggests anomalies (or geological structural control). Considering the dataset's central tendencies, with a median of 236 and an upper quartile Q3 of 579, an upper limit value of 1364 was determined. The proportion of grouting points exceeding 1364 is 14%. Consequently, based on this analysis, the threshold for grouting volume anomalies can be set at 1364 (Fig. 7 ). 5.1.2 Statistical Analysis of Grouting End Pressure in the Xu Limestone Layer Based on the standard deviation method for analyzing outliers, the results indicate that the overall value in the evaluation area is 576.80, with a mean of 11.77 and a total standard deviation of 1.46. The sample standard deviation is 1.45. The upper limit for outliers is 16.11, and the lower limit is 7.43. $$\:\sigma\:=\sqrt{\frac{\sum\:{（{X}_{i}-{\mu\:}）}^{2}}{N}}$$ Where σ represents the standard deviation, µ denotes the mean value, X stands for the individual grouting volume value, and N represents the number of data points. Upper limit = \(\:\mu\:\) + 3 \(\:\sigma\:\) Lower limit = \(\:\mu\:\) − 3 \(\:\sigma\:\) Using the boxplot method to analyze outliers, the results reveal that in the evaluation area, the lower quartile Q1 of the overall grouting pressure data is 11, the upper quartile Q3 is 12.5, and the interquartile range IQR is 1.5. The upper limit for outliers is 14.75, and the lower limit is 8.75. Figure 8 . illustrates the analysis of outliers in grouting pressure within the evaluation area for the Xu limestone layer Table 2 Statistical Summary of Grouting Terminal Pressure Data for Xu Limestone Grouting Points Table 2 Statistical Summary of Grouting Terminal Pressure Data for Xu Limestone Grouting Points No. Grouting pressure No. Grouting pressure No. Grouting pressure 1 11.00 18 12.00 35 12.50 2 10.50 19 12.50 36 12.00 3 13.90 20 12.40 37 12.50 4 12.60 21 12.50 38 12.20 5 12.20 22 12.30 39 13.00 6 13.50 23 12.60 40 12.20 7 9.60 24 12.20 41 12.20 8 10.00 25 12.60 42 11.50 9 7.00 26 12.30 43 12.20 10 11.00 27 12.50 44 13.00 11 7.00 28 12.50 45 13.00 12 10.50 29 12.40 46 11.00 13 10.00 30 13.00 47 12.10 14 10.00 31 12.50 48 12.40 15 13.50 32 12.40 49 12.20 16 10.00 33 12.80 17 12.00 34 9.00 Based on the statistical analysis using both the standard deviation method and the box plot method for the grouting terminal pressure data in the evaluation area, and considering the grouting reinforcement data, smaller values of grouting pressure indicate anomalies (or geological structure control). The median value of the overall data is 12.20, with the lower quartile Q1 being 11.00. The percentage of grouting points with pressure values less than 8.75 is 4.0%. Therefore, based on the analysis above, the lower limit value of 8.75 is considered as the lower limit for evaluating anomalous grouting pressure values. Additionally, considering that the grouting pressure design parameter is 2 to 2.5 times the water pressure and combining it with practical data, the comprehensive determination of the lower limit of the anomaly value can be set at 8.0 for evaluation (Fig. 8 ). 5.1.3 Statistical Analysis of Grouting Volume in Fourth and Fifth Limestone Layers Using the standard deviation method to analyze outliers, the results indicate that the total grouting volume in the evaluation area is 278,84 m³, with an average value of 2,681.16 m³. The overall standard deviation is 2,206.17 m³, and the sample standard deviation is 2,195.54 m³. The upper limit for outliers is 9,267.79 m³, while the lower limit is negative. $$\:\sigma\:=\sqrt{\frac{\sum\:{（{X}_{i}-{\mu\:}）}^{2}}{N}}$$ Where σ represents the standard deviation, µ denotes the mean value, X stands for the individual grouting volume value, and N represents the number of data points. Upper limit = \(\:\mu\:\) + 3 \(\:\sigma\:\) Lower limit = \(\:\mu\:\) − 3 \(\:\sigma\:\) Using the box plot method to analyze outliers, the results indicate that within the evaluation area, the lower quartile (Q1) for the total grouting volume data is 965, the upper quartile (Q3) is 3,878, and the interquartile range (IQR) is 2,913. The upper limit for outliers is 8,247.5, while the lower limit is negative. Figure 9 . Analysis of Grouting Volume Data in the Evaluation Area for the Fourth and Fifth Limestone Table 3 Statistical Table of Grouting Volume Data for Fourth and Fifth Limestone Table 3 Statistical Table of Grouting Volume Data for Fourth and Fifth Limestone NO. Grouting volume NO. Grouting volume NO. Grouting volume 1 10009.0 36 114.0 71 205.0 2 2204.0 37 3410.0 72 2155.0 3 5204.0 38 1842.0 73 2417.0 4 3083.0 39 1876.0 74 2423.0 5 7273.0 40 2237.0 75 1887.0 6 5374.0 41 100.0 76 609.0 7 6435.0 42 4940.0 77 2152.0 8 6213.0 43 105.0 78 2262.0 9 4385.0 44 1544.0 79 3933.0 10 4491.0 45 3009.0 80 3035.0 11 1729.0 46 658.0 81 2926.0 12 2509.0 47 1375.0 82 3895.0 13 2243.0 48 7536.0 83 673.0 14 1285.0 49 3840.0 84 121.0 15 258.0 50 140.0 85 2331.0 16 3292.0 51 1853.0 86 2231.0 17 2253.0 52 6729.0 87 421.0 18 2205.0 53 490.0 88 2148.0 19 4623.0 54 3836.0 89 1033.0 20 4183.0 55 65.0 90 941.0 21 5672.0 56 1772.0 91 1708.0 22 3434.0 57 4037.0 92 269.0 23 1967.0 58 2203.0 93 3881.0 24 1932.0 59 3398.0 94 459.0 25 1837.0 60 3877.0 95 77.0 26 8944.0 61 228.0 96 2187.0 27 41.0 62 2377.0 97 321.0 28 4966.0 63 2208.0 98 95.0 29 3004.0 64 4032.0 99 622.0 30 1921.0 65 126.0 100 1951.0 31 59.0 66 2630.0 101 1793.0 32 3852.0 67 973.0 102 295.0 33 4002.0 68 9613.0 103 6363.0 34 3337.0 69 4780.0 104 7026.0 35 1069.0 70 755.0 Based on the results of statistical analysis using the standard deviation method and the box plot method on the grouting volume data in the evaluation area, where the data itself pertains to grouting reinforcement, higher grouting volume values indicate anomalies (or structural control by the strata). The median of the overall data is 2206.5, the upper quartile Q3 is 3878, and grouting points with values greater than 3878 account for 25% of the total. Therefore, according to the above analysis, the upper limit of the grouting volume anomaly value can be set at the third quartile ( Q3 ) for evaluation (Fig. 9 ). 5.1.4 Statistical Analysis of Final Grouting Pressure in the Fourth and Fifth Limestone Layers Based on the standard deviation method for analyzing outliers, the results show that the overall grouting pressure value in the evaluation area is 961.10, with a mean value of 9.24, an overall standard deviation of 1.55, and a sample standard deviation of 1.54. The upper limit for outliers is 13.88, and the lower limit for outliers is 4.59. $$\:\sigma\:=\sqrt{\frac{\sum\:{（{X}_{i}-{\mu\:}）}^{2}}{N}}$$ Where σ represents the standard deviation, µ denotes the mean value, X stands for the individual grouting volume value, and N represents the number of data points. Upper limit = \(\:\mu\:\) + 3 \(\:\sigma\:\) Lower limit = \(\:\mu\:\) − 3 \(\:\sigma\:\) Based on the box plot method for analyzing outliers, the results show that the overall grouting pressure data in the evaluation area has a lower quartile Q1 of 8.4, an upper quartile Q3 of 10, and an interquartile range ( IQR ) of 1.6. The upper limit for outliers is 12.4, and the lower limit for outliers is 6.0 (Fig. 10 ). Figure 10 . illustrates the analysis of grouting pressure in the research area for the fourth and fifth limestone aquifers Table 4 Statistical Summary of Grouting Pressure Data for the Fourth and Fifth Limestone Aquifers Table 4 Statistical Summary of Grouting Pressure Data for the Fourth and Fifth Limestone Aquifers No. Grouting pressure No. Grouting pressure No. Grouting pressure 1 8.2 36 10.2 71 11.6 2 8.1 37 10.0 72 8.5 3 12.0 38 10.0 73 9.7 4 12.0 39 8.7 74 10.0 5 8.2 40 8.2 75 8.4 6 8.5 41 10.0 76 8.7 7 4.2 42 9.5 77 10.8 8 14.5 43 9.9 78 8.2 9 9.5 44 12.6 79 9.1 10 13.5 45 11.5 80 12.7 11 8.3 46 9.6 81 9.6 12 8.6 47 9.0 82 8.6 13 8.8 48 8.5 83 11.8 14 8.3 49 8.5 84 10.3 15 8.5 50 8.6 85 10.3 16 8.5 51 8.3 86 8.7 17 8.5 52 9.0 87 8.2 18 8.4 53 6.3 88 9.8 19 11.6 54 12.0 89 8.4 20 9.0 55 9.0 90 9.8 21 9.1 56 9.9 91 8.5 22 10.0 57 4.5 92 8.0 23 8.2 58 9.2 93 8.1 24 10.2 59 8.5 94 11.0 25 11.0 60 9.0 95 8.6 26 8.1 61 10.0 96 8.3 27 8.5 62 8.0 97 8.2 28 9.0 63 8.2 98 10.0 29 5.0 64 9.2 99 10.2 30 10.5 65 8.5 100 9.2 31 8.1 66 8.6 101 8.2 32 9.5 67 9.0 102 8.4 33 8.7 68 10.5 103 9.5 34 9.5 69 8.2 104 8.7 35 10.2 70 9.5 Based on the statistical analysis using the standard deviation method and the box plot method for the ground grouting pressure data in the evaluation area, where lower grouting pressure values indicate anomalies (or structural control), it is observed that the median of the overall data is 9.0, the lower quartile Q1 is 8.4. The percentage of grouting points with pressure values less than 8.4 is 3.8%. Therefore, based on the above analysis, the lower quartile (Q1) value of 8.4 is selected as the lower limit for evaluating abnormal grouting pressure values. Additionally, considering the grouting pressure design parameter being 2 to 2.5 times the water pressure and practical data, a comprehensive determination of the lower limit for abnormal values can be set at 8.0 for evaluation. 5.2 GIS-Based Grading Evaluation Results 5.2.1 Evaluation of Grouting Effectiveness in the Xu Limestone Aquifer Based on the statistical analysis of grouting volume data from surface directional drilling provided by the mining company, and using the natural break method in the GIS system for grading analysis (Sun et al., 2020 ), as well as considering the results of statistical analysis of grouting data, the study area was divided into three grades: stable zone (grouting volume < 579 t), transition zone (579 t ≤ grouting volume < 1364 t), and anomaly area (grouting volume ≥ 1364 t); as shown in Fig. 11 . Figure 11 . Thematic Map of Grouting Volume Distribution in the Xu Limestone Aquifer Based on the grouting data of the Xu limestone aquifer, the grouting pressure of most grouting sections has reached 8 MPa, while a small portion of the grouting sections have not reached 10 MPa. Based on past grouting experience and the relatively high mineralization degree of the Xu aquifer, it is analyzed and judged that there may be concealed structural connections between the fourth and fifth limestone aquifers of the 11th coal seam roof and the underlying Xu and Ao limestone aquifers. Combining this with the results of statistical analysis of the data, this study sets the evaluation criteria for the grouting effect of the Xu limestone aquifer, with the grouting pressure not less than 8.0 MPa considered acceptable. Therefore, based on the completed grouting data of the Xu limestone aquifer and the observation of water stress center displacement data from pumping test observation wells, the grouting effect of the Xu limestone aquifer can be classified into three levels: stable zone (pressure ≥ 10 MPa), transitional zone (8.0 MPa ≤ pressure < 10 MPa), and anomaly zone (pressure < 8.0 MPa). This classification is illustrated in the single-item evaluation map of grouting effects in the Xu limestone aquifer (Fig. 12 ). Figure 12 . Distribution thematic map of grouting pressure in the Xu limestone aquifer Based on the grouting volume and grouting pressure of the Xu limestone aquifer in the study area, a comprehensive evaluation is conducted. Using the GIS system, grouting pressure evaluation is weighted at 0.6, while grouting volume evaluation is weighted at 0.4 (with a negative correlation) for overlay evaluation. Finally, based on the natural classification method in GIS, the effectiveness of the ground directional horizontal grouting treatment in the Xu limestone aquifer area is categorized into three levels: standards-compliant zone, qualified zone, and weak zone, as illustrated in Fig. 13 . Figure 13 . depicts the evaluation of the grouting treatment effectiveness in the Xu limestone aquifer 5.2.2 Evaluation of Grouting Effectiveness in the Fourth and Fifth Limestone Aquifers Based on the grouting data of the fourth and fifth limestone aquifers in the roof of coal seam 11, most of the grouting sections have reached a final pressure of 8 MPa. However, there are still small sections where the final pressure has not reached 10 MPa. According to previous grouting experiences and the high degree of mineralization in the fourth and fifth limestone aquifers, an analysis suggests the possibility of hidden structural conduits between the fourth and fifth limestone aquifers and the underlying Xu limestone and Ao limestone aquifers. Combining these factors with the results of statistical analysis, the evaluation of grouting effectiveness is set with a criterion that the final pressure should not be less than 8.0 MPa, indicating acceptable grouting effectiveness. Therefore, based on the completed grouting hole data for the roof of coal seam 11 and observations of water stress center displacement from the pumping test in the fourth and fifth limestone aquifers, the grouting effect can be classified into three levels: stable zone (final pressure ≥ 10 MPa), transition zone (8.0 MPa ≤ final pressure < 10 MPa), and anomaly zone (final pressure < 8.0 MPa), as illustrated in the single-factor evaluation map of grouting effectiveness for the roof of coal seam 11 in the fourth and fifth limestone aquifers (Fig. 14 ). Figure 14 . Distribution thematic map of grouting final pressure in the fourth and fifth limestone aquifers Based on statistical analysis of grouting volume data from surface directional drilling provided by the mining company, the research area of the fourth and fifth limestone aquifers was categorized into three levels using the natural breakpoints method within the GIS system. This classification was further informed by the statistical analysis of grouting data. The areas were classified as stable (grouting volume < 2037 t), transitional (2037 t ≤ grouting volume < 3871 t), and anomalous (grouting volume ≥ 3871 t). The grouting volume was found to be negatively correlated with the evaluation results, as illustrated in Fig. 15 . Figure 15 . depicts the thematic distribution of grouting volume in the fourth and fifth limestone aquifers Based on the comprehensive evaluation of grouting volume and grouting pressure in the top plate fourth and fifth limestone aquifers, a weighted evaluation is conducted using a GIS system, with a weight of 0.6 for grouting pressure evaluation and 0.4 for grouting volume evaluation (negatively correlated). Finally, based on the natural grading method in GIS, the ground directional horizontal grouting effect in the top plate fourth and fifth limestone aquifers is classified into three levels: standard area, qualified area, and weak area, as shown in Fig. 16 . Figure 16 . illustrates the evaluation of the grouting consolidation effect in the fourth and fifth limestone aquifers 5.3 Evaluation Mechanism for Advanced Area Treatment of Surface-directed Multi-branch Horizontal Wells In response to the characteristics of advanced treatment of coal mine water hazards using ground directional multi-branch horizontal wells, which can effectively address the lack of underground treatment in areas of delayed or restricted mining, but with grouting effects that cannot be verified underground (according to regulations, area treatment must be completed before conversion to a mineable area), this study proposes a scientific evaluation mechanism. Firstly, based on surface boreholes or directional horizontal boreholes, the permeability coefficient and sealing capacity of the water barrier layer after grouting are evaluated to conduct the initial qualitative analysis of grouting effects. Secondly, statistical analysis is performed on the surface grouting renovation data (grouting volume, grouting pressure), providing evaluation thresholds for each indicator. Thirdly, GIS-based modeling is utilized to process the data, generating maps for grouting effect evaluation. Fourthly, intensive borehole exploration and supplementary grouting renovation are conducted underground in the anomaly areas identified by the evaluation system. Finally, after all areas in the study region have been evaluated as qualified, trial mining can be conducted in the working face. This evaluation mechanism integrates closely with various aspects of mining practices, providing scientifically effective evaluation results to guide safe mine production. It has been validated in multiple mines in the East China region, showing significant effectiveness. This study also proposes, for the first time, the "Evaluation Method for the Effectiveness of Advanced Area Treatment of Ground Directional Multi-Branch Horizontal Wells," as the "Technical Specification for Advanced Area Treatment of Coal Seam Bottom Limestone Aquifers" has only been implemented since early 2024, and effective evaluation methods are not yet available. 6 Conclusion This study addresses the evaluation issue of the effectiveness of high-pressure water hazard prevention during coal seam mining, proposing a series of systematic analysis methods. Firstly, qualitative analysis of the grouting effect was conducted based on the impermeability and permeability of the water-resistant layer after treatment. Secondly, utilizing statistical analysis methods, evaluation thresholds for various factors affecting the treatment effect were proposed based on the grouting data of each coordinate point in the advanced treatment area of surface-directed multi-branch horizontal wells. Finally, through GIS data processing techniques, thematic maps of the evaluated factors were overlaid, and comprehensive evaluation results of the treatment effect in the research area were obtained by combining verification and supplementary grouting processes through intensive drilling underground. This study introduces for the first time the "evaluation method of the treatment effect in the advanced treatment area of surface-directed multi-branch horizontal wells." Through practical tests on multiple deep mining faces in the North China coalfield, the effectiveness and reliability of this method have been demonstrated, facilitating safe mining. The findings of this study provide important reference for water hazard prevention in deep coal seam mining, demonstrating significant practical value. Declarations Statement of Novelty Using ground-oriented multi-branch wells for preemptive regional control is currently the most effective method for addressing high-pressure aquifers in deep mines. However, until now, there has been no scientifically validated method for evaluating the effectiveness of such preemptive regional control globally. This study develops a novel mathematical model based on a GIS platform to evaluate the effectiveness of this control method. It significantly reduces construction costs for production mines and has been successfully applied in several deep mining operations in the North China Coalfields, demonstrating remarkable results. CRediT authorship contribution statement Yanbo Hu: Writing – review & editing, Software, Writing – original draft, Visualization, Investigation, Validation, Methodology, Formal analysis, Data curation, Conceptualization. Jingzheng Jiang: Formal analysis, Data curation. Gang Zheng: Investigation, Data curation, Conceptualization. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Declaration of Generative AI and AI-assisted technologies in the writing process During the preparation of this work, the authors used Google’s Gemini and Anthropic’s Claude in order to proofread the article, give a final review, and improve its readability. After using these tools, the authors reviewed and edited the content as needed and took full responsibility for the content of the publication. Acknowledgements This work was supported by the China Postdoctoral Science Foundation under Grant 2024M750682, and the Natural Science Foundation of Jiangsu Province under Grant BK20221319. References Dong S, Zhang W, Zhou W et al (2021) Discussion on some topical issues of water prevention and control in coal mines. Mine Water Environ 40:547–552. https://doi.org/10.1007/s10230-021-00773-3 He MC, Wu YY, Gao YB et al (2024) Research progress of rock mechanics in deep mining. J China Coal Soc 49(01):75–99. https://doi.org/10.13225/j.cnki.jccs.2023.1400 Hu W, Zhao C (2021) Evolution of water hazard control technology in china’s coal mines. Mine Water Environ 40:334–344. https://doi.org/10.1007/s10230-020-00744-0 Hu YB, Li WP, Chen XM, Xu HZ, Liu SL (2022) Temporal and spatial evolution characteristics of fracture distribution of floor strata in deep coal seam mining. 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Mod Min 39(02):211–214 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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18:21:36","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":24151,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of Grouting Volume Data in the Evaluation Area for the Fourth and Fifth Limestone\u003c/p\u003e","description":"","filename":"Fig.189.png","url":"https://assets-eu.researchsquare.com/files/rs-4969049/v1/63f392790fe65b5f7d6efd1a.png"},{"id":65947704,"identity":"dc803554-1566-4716-a3ba-635981aac314","added_by":"auto","created_at":"2024-10-04 18:13:36","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":24825,"visible":true,"origin":"","legend":"\u003cp\u003eillustrates the analysis of grouting pressure in the research area for the fourth and fifth limestone aquifers\u003c/p\u003e","description":"","filename":"Fig.1810.png","url":"https://assets-eu.researchsquare.com/files/rs-4969049/v1/09bf00c017520d480d96eb49.png"},{"id":65947709,"identity":"682c1d0f-5455-4889-8696-7955b577899d","added_by":"auto","created_at":"2024-10-04 18:13:36","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":89913,"visible":true,"origin":"","legend":"\u003cp\u003eThematic Map of Grouting Volume Distribution in the Xu Limestone Aquifer\u003c/p\u003e","description":"","filename":"Fig.1811.png","url":"https://assets-eu.researchsquare.com/files/rs-4969049/v1/2a58623840fa35d8caba364f.png"},{"id":65947697,"identity":"fccd82e9-3f0f-49f6-bfda-794d984c915e","added_by":"auto","created_at":"2024-10-04 18:13:36","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":88106,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution thematic map of grouting pressure in the Xu limestone aquifer\u003c/p\u003e","description":"","filename":"Fig.1812.png","url":"https://assets-eu.researchsquare.com/files/rs-4969049/v1/6e71d6a3738c25af5aa02fee.png"},{"id":65948111,"identity":"c6519787-6610-43f7-8d55-60f237bea68d","added_by":"auto","created_at":"2024-10-04 18:21:36","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":109124,"visible":true,"origin":"","legend":"\u003cp\u003eDepicts the evaluation of the grouting treatment effectiveness in the Xu limestone aquifer\u003c/p\u003e","description":"","filename":"Fig.1813.png","url":"https://assets-eu.researchsquare.com/files/rs-4969049/v1/b310cd003e364ff7769476fd.png"},{"id":65948115,"identity":"4717b40a-3f71-47ff-a1b4-e884fca53667","added_by":"auto","created_at":"2024-10-04 18:21:36","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":92784,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution thematic map of grouting final pressure in the fourth and fifth limestone aquifers\u003c/p\u003e","description":"","filename":"Fig.1814.png","url":"https://assets-eu.researchsquare.com/files/rs-4969049/v1/d08977912b9e4ac250fc8c7d.png"},{"id":65947706,"identity":"c7db3dc7-519e-4e4d-9d94-21e8617ef42c","added_by":"auto","created_at":"2024-10-04 18:13:36","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":92436,"visible":true,"origin":"","legend":"\u003cp\u003eDepicts the thematic distribution of grouting volume in the fourth and fifth limestone aquifers\u003c/p\u003e","description":"","filename":"Fig.1815.png","url":"https://assets-eu.researchsquare.com/files/rs-4969049/v1/5f2e1ad0a94d28665ddf1d54.png"},{"id":65947708,"identity":"dbcd5314-46d9-4ba8-9f1b-01424888567d","added_by":"auto","created_at":"2024-10-04 18:13:36","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":110158,"visible":true,"origin":"","legend":"\u003cp\u003eillustrates the evaluation of the grouting consolidation effect in the fourth and fifth limestone aquifers\u003c/p\u003e","description":"","filename":"Fig.1816.png","url":"https://assets-eu.researchsquare.com/files/rs-4969049/v1/5322e4b7257c00c6094e7769.png"},{"id":66026090,"identity":"901edcc6-fc38-43b1-a8f7-48b4859fca6c","added_by":"auto","created_at":"2024-10-07 00:27:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2454600,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4969049/v1/74bd07aa-8533-4e2e-8d0e-497e4480e072.pdf"}],"financialInterests":"","formattedTitle":"The New Method for Evaluating the Advanced Treatment Effect of Limestone Aquifers in the Roof and Floor of Deep Coal Seam Mining","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eDuring more than 40 years of rapid development since the reform and opening up, coal energy has played a crucial role in China's economic construction (Wang et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, with the extensive and rapid exploitation of coal resources, the shallow resources in the North China region have been almost exhausted, forcing mining enterprises to shift towards deep mining. Deep mining faces the challenges of \"three highs and one disturbance\" (high ground stress, high temperature, high water pressure, and intense mining disturbance), with the threat of high-pressure water being particularly severe (Wu et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hu et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This high-pressure water not only increases the difficulty of extraction but also poses a significant threat to the safe production of mines (He et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn recent years, continuous exploration has shown that the use of surface-directed multi-branch horizontal wells for advanced regional treatment of high-pressure aquifers has yielded promising results (Sun et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This technology can effectively reduce the threat of high-pressure water, thereby enhancing mine safety and production efficiency (Li et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the \"Technical Specification for Advanced Regional Treatment of Limestone Aquifers Under Coal Seams\" was only implemented in early 2024. As of now, there is still no effective evaluation method to measure the actual effectiveness of these treatment measures.\u003c/p\u003e \u003cp\u003eZhao et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) studied the effectiveness of thin-layer limestone water prevention based on multi-branch horizontal drilling and grouting processes, showing significant improvement in the Taiyuan formation thin-layer limestone aquifers, with denser well placement leading to better results. Luo et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) constructed a precise \"water stop plug\" using stacked multi-branch horizontal wells for advanced treatment of karst collapse columns. Zhan et al. (2019) researched the application of surface-directed multi-branch horizontal wells in managing high-pressure aquifers, proposing practical procedures and effects of this technology. However, these studies mainly focus on the application of the technology itself, lacking systematic evaluation of the treatment effectiveness.\u003c/p\u003e \u003cp\u003eIn terms of high-pressure water hazard prevention, Wang et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) studied the water-blocking capacity of aquicludes, proposing a preliminary evaluation method based on this capacity. Wu et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) introduced a framework using scenario analysis combined with Bayesian networks to assess the probability of mine water inrush accidents. By setting different state combinations of scenario factors, they calculated and analyzed the probabilities of various mine water inrush scenarios, including typical and catastrophic ones. Wu et al. (2008, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) used the vulnerability index method and GIS technology to scientifically process data in coal mine water hazard prevention, providing new technical means for such research. Li et al (2021) proposed three water control modes and key technologies based on the water inrush coefficient and combined with the Ts-q method, forming a theoretical and technical system for water hazard prevention in the Huaibei mining area.\u003c/p\u003e \u003cp\u003eAlthough these studies provide a theoretical basis for evaluation methods, they still have many shortcomings in practical applications, such as incomplete evaluation indicators and insufficient data processing precision.\u003c/p\u003e \u003cp\u003eGiven the shortcomings in the existing research on evaluating the effectiveness of advanced regional treatment of limestone aquifers under coal seams, this paper aims to propose a new method for scientifically evaluating the effectiveness of surface-directed multi-branch horizontal well advanced regional treatment. This study, based on data from surface-directed multi-branch horizontal well advanced regional treatment, utilizes methods such as aquiclude water-blocking capacity calculation, statistical analysis, and GIS model processing to establish a specific evaluation model for factors affecting water hazard treatment effectiveness, obtaining thematic distribution data of various influencing factors in the study area. Through mathematical modeling and GIS processing of various factor data, zoning evaluation data for the grouting transformation effectiveness were obtained. By combining qualitative and quantitative evaluation modes and supplementary underground exploration evaluations, this paper proposes a method for evaluating the effectiveness of advanced regional treatment using surface-directed multi-branch horizontal wells.\u003c/p\u003e \u003cp\u003eThis study is the first to propose the \"Effectiveness Evaluation Method for Advanced Regional Treatment using Surface-Directed Multi-Branch Horizontal Wells,\" providing a new evaluation system for water hazard prevention in deep coal seam mining. Practical tests on several deep mining faces in the North China coalfields have proven the significant effectiveness of this evaluation system, providing scientific basis and technical support for coal mining enterprises in formulating and implementing water hazard prevention measures.\u003c/p\u003e \u003cp\u003eFuture research can be further deepened in the following aspects: (1) Expanding the research scope to other regions and different types of mines to verify the universality of this method. (2) Optimizing the evaluation model to enhance the accuracy and reliability of the evaluation results. (3) Promoting the technical application in more coal mining enterprises to improve the level of water hazard prevention in the coal mining industry.\u003c/p\u003e \u003cp\u003eIn conclusion, the results of this study not only provide strong support for water hazard prevention in deep coal seam mining but also offer new directions and ideas for related research fields. Through continuous improvement and widespread application, this method is expected to play an increasingly important role in coal mine water hazard prevention.\u003c/p\u003e"},{"header":"2 Overview of the Study Area","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Overview of the Mining Area\u003c/h2\u003e \u003cp\u003eThis study is based on the Zhaoguan Coal Mine of Shandong Energy Group. The Zhaoguan mine field is part of the Yellow River North Coalfield, located in the northwest of Shandong Province, covering an area of 59.2 km\u0026sup2; with a mining elevation range of -200.0m to -1200.0m. The Yellow River flows along the southeast side of the mine field, providing convenient transportation. The area is flat, with a surface elevation generally between +\u0026thinsp;27.0m and +\u0026thinsp;32.0m. The ground level within the study area is lower than the riverbed of the Yellow River, making it prone to flooding during the rainy season.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Location Map of the Study Area\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe stratigraphic division of the Yellow River North Coalfield belongs to the Luxi stratigraphic subregion of the North China stratigraphic region. The Carboniferous-Permian system is unconformably overlain by Ordovician limestone. The Ordovician and Cambrian coal-bearing strata are exposed along the southern bank of the Yellow River from Changqing to Pingyin, forming a region of low to middle mountains and hills. The Carboniferous-Permian coal-bearing strata are well-developed and rich in coal resources, being covered by a considerable thickness of Quaternary and Neogene strata, forming a concealed coalfield.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Comprehensive Geological Columnar Section\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe coal-bearing strata of the mine field belong to the Taiyuan and Shanxi formations of the Carboniferous-Permian system, containing 16 coal seams in total. The Shanxi formation contains 4 coal seams, with only seams 2, 3, and 4 present in the mine field, and seam 4 being the only minable seam. The Taiyuan formation contains 12 coal seams, with 4 main minable seams (seams 7, 10, 11, and 13). Seam 13 is a stable coal seam, while seams 7, 10, and 11 are relatively stable, and seam 4 is unstable.\u003c/p\u003e \u003cp\u003eCurrently, the shallow resources have been exhausted. To continue production, preparations for mining the lower coal seams of the Taiyuan formation (seams 11 and 13) have been initiated. These seams face severe threats from the overlying fourth and fifth limestone aquifers and the underlying Xujiazhuang and Ordovician limestone aquifers. To ensure the safe mining of the lower coal seams, it is necessary to conduct advanced regional treatment of the direct and indirect water-bearing aquifers in the roof and floor of the coal seams (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This study aims to evaluate the treatment effectiveness based on the data from advanced regional treatment, ensuring safe mining.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Engineering Geological and Hydrogeological Conditions\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Stratigraphic Structure\u003c/h2\u003e \u003cp\u003eThe mine field is located in the central-western part of the Yellow River North Coalfield, being a fully concealed North China-type Carboniferous-Permian coalfield. The coal series are based on the Middle-Lower Ordovician strata, overlaid by the Benxi formation of the Middle Carboniferous, Taiyuan formation of the Upper Carboniferous, Shanxi formation of the Lower Permian, Lower Shihezi formation, Upper Shihezi formation of the Upper Permian, and the Neogene and Quaternary strata. The stratigraphic sequence from top to bottom is as follows:\u003c/p\u003e \u003cp\u003e(1) Quaternary System: Thickness 65.00\u0026ndash;106.00 m, average 89.70 m. The upper part consists of silt and loess deposited by the modern Yellow River, while the middle and lower parts are mainly sandy clay and clay. The base has an unstable layer of grey to yellow-brown gravel, which demarcates it from the Neogene, with an angular unconformity contact.\u003c/p\u003e \u003cp\u003e(2) Neogene System: Thickness 125.90\u0026ndash;252.10 m, average 191.60 m. Predominantly clay, with the upper part being variegated (purple-red, grey-green), and the middle to lower part green to grey-white. The base has an unstable gravel layer, predominantly limestone, with an angular unconformity overlying the Paleozoic.\u003c/p\u003e \u003cp\u003e(3) Upper Permian Upper Shihezi Formation: Thickness 281.60 m. Mainly composed of variegated claystone, siltstone, and grey-white to grey-green sandstone.\u003c/p\u003e \u003cp\u003e(4) Lower Permian Lower Shihezi Formation: Thickness 29.88\u0026ndash;69.87 m, average 47.93 m. Mainly composed of grey-green sandstone and variegated claystone, locally interbedded with grey to dark grey claystone and siltstone.\u003c/p\u003e \u003cp\u003e(5) Lower Permian Shanxi Formation: Thickness 66.20\u0026ndash;113.90 m, average 97.62 m. This formation is one of the coal-bearing strata of the mine field, composed of medium to fine sandstone, siltstone, silty mudstone, mudstone, and coal seams. The coal seams are concentrated in the middle to lower parts, with only seams 3 and 4 present in the mine field, and seam 4 being locally minable.\u003c/p\u003e \u003cp\u003e(6) Upper Carboniferous Taiyuan Formation: Thickness 142.80\u0026ndash;174.65 m, average 163.23 m. This is the main coal-bearing formation of the mine field, composed of mudstone, siltstone, medium to fine sandstone, thin limestone layers, and coal seams. It includes five limestone layers, sequentially named from top to bottom as the first to fifth limestones. The formation contains 9 coal seams from top to bottom, namely seams 5, 6, 7, 8, 9, 10, 11, 13, and 14, with the main minable seams (seams 11 and 13) located below the fifth limestone.\u003c/p\u003e \u003cp\u003e(7) Middle Carboniferous Benxi Formation: Thickness 20.66\u0026ndash;56.05 m, average 32.42 m. Composed of mudstone, siltstone, grey claystone, limestone, sandstone, aluminous mudstone, and variegated claystone. The top contains an unstable limestone layer (sixth limestone); the middle contains the stable Xujiazhuang limestone, often with chert nodules and marine fossils, with a thickness of 7.70\u0026ndash;12.40 m (average 10.03 m), serving as a good marker layer in the area; the bottom consists of aluminous mudstone and variegated claystone. The formation is in unconformable contact with the underlying Ordovician.\u003c/p\u003e \u003cp\u003e(8) Middle-Lower Ordovician: Mainly composed of medium to thick-bedded limestone, often showing karst phenomena and well-developed fractures, mostly filled with calcite. It serves as an indirect water-bearing aquifer for the coal series, with a total thickness of about 800 m based on peripheral exposures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Aquifers\u003c/h2\u003e \u003cp\u003e(1) Quaternary Aquifer: Composed of several layers of fine to coarse sand and gravel, loosely consolidated with good permeability and strong water-bearing capacity. The water level in the mine field is +\u0026thinsp;28.68 m, with a unit water inflow of 0.0044 L/s\u0026middot;m and a mineralization of 0.6508 g/L.\u003c/p\u003e \u003cp\u003e(2) Neogene Aquifer: Contains clay in the sand layers, resulting in weak water-bearing capacity. The water level is +\u0026thinsp;28.65 m, with a unit water inflow of 0.0736 L/s\u0026middot;m and a mineralization of 1.4284 g/L. The Neogene layer is generally more than 150 m below seam 4, separated by the Shihezi and Shanxi formations, acting as an indirect water-bearing aquifer with no direct impact on coal seam mining.\u003c/p\u003e \u003cp\u003e(3) Shanxi Formation Sandstone: Total thickness of 66.20\u0026ndash;113.90 m, average 97.62 m. Most fine sandstone and siltstone have high clay mineral content and poorly developed fractures, resulting in poor water-bearing capacity. Only parts of the medium to coarse sandstone have developed joints and fractures, showing some water-bearing capacity.\u003c/p\u003e \u003cp\u003e(4) Taiyuan Formation Limestones (First to Fifth):\u003c/p\u003e \u003cp\u003e1) First Limestone: Thickness 0\u0026ndash;3.00 m, average 1.81 m. Unit water inflow of 0.2217 L/s\u0026middot;m, showing moderate karst fracture water-bearing capacity. The neighboring Qiujia Coal Mine has reported a maximum water discharge of 60 m\u0026sup3;/h from the first limestone, causing flooding incidents.\u003c/p\u003e \u003cp\u003e2) Second Limestone: Thickness 0\u0026ndash;2.55 m, average 1.78 m. Displays weak to moderate karst fracture water-bearing capacity.\u003c/p\u003e \u003cp\u003e3) Third Limestone: Thickness 0\u0026ndash;3.70 m, average 1.95 m. Water-bearing capacity similar to the first and second limestones but slightly weaker.\u003c/p\u003e \u003cp\u003e4) Fourth and Fifth Limestones: Combined thickness of 0\u0026ndash;13.58 m, average 6.58 m. The distance between the fourth and fifth limestones is 0\u0026ndash;10.54 m, average 3.63 m, with thin mudstone intercalations. In the southern part of the mine field, the fourth and fifth limestones merge, while in the northeast, the distance increases, making them a single aquifer. Unit water inflow of 0.2997 L/s\u0026middot;m, showing moderate water-bearing capacity. The water level is +\u0026thinsp;30.2 m, with borehole measurements indicating significant water discharge.\u003c/p\u003e \u003cp\u003e5) Xujiazhuang Limestone: Locally developed small karst caves, thickness 0\u0026ndash;12.40 m, average 8.49 m. Water level\u0026thinsp;+\u0026thinsp;30.23\u0026ndash;31.93 m, unit water inflow 0.0035\u0026ndash;0.0085 L/s\u0026middot;m, mineralization 0.3333\u0026ndash;2.358 g/L.\u003c/p\u003e \u003cp\u003e6) Ordovician Limestone: Dense and hard, with locally developed karst fractures. Water level\u0026thinsp;+\u0026thinsp;29.45\u0026ndash;+31.70 m, unit water inflow 0.0019\u0026ndash;0.1517 L/s\u0026middot;m, mineralization 0.3146\u0026ndash;3.0152 g/L, showing weak to moderate water-bearing capacity.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3 Geological engineering data for advanced regional governance","content":"\u003cp\u003eThe evaluation area for the ground directional drilling and grouting treatment of the Fourth and Fifth Limestones and Xujiazhuang Limestone water-bearing layers is located in the central part of the Seventh Mining Area. It includes the northern part of the eastern edge of the western wing, the southern edge of the western measurement of the eastern wing, the concentrated return airway of the upper section of -415, the concentrated track transport roadway of the upper section of -415, and the concentrated transport roadway of the upper section of -415. The total area of the evaluation zone is 32.98e4 m\u0026sup2;, with a perimeter of 3257.03 m, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u0026thinsp;\u0026minus;\u0026thinsp;1. Currently, the construction of the uphill section of the return airway, the uphill section of auxiliary transport, and the uphill section of transport in the Seventh Mining Area has been completed safely. Partial exposures of the Fourth and Fifth Limestones water-bearing layers have been revealed in the original trial mining face of the eastern wing of the Seventh Mining Area.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Plan View of the Study Area\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Grouting Data for Xu Limestone Aquifer\u003c/h2\u003e \u003cp\u003eThe evaluation area involves multiple drilling groups (D11, D12, original D2, etc.), with grouting modifications performed on the Xu Limestone layer of the 11th coal seam floor through ground directional drilling. This has achieved phased results. As of November 2023, the Xu Limestone drilling for D11, D12, and original D2 has been completed. The original D2 drilling group includes four branch drill holes, labeled: \"original D2-1, original D2-2, original D2-3, original D2-4.\" The D11 drilling group consists of nine branch drill holes, labeled: \"D11-1 to D11-9.\" The D12 drilling group consists of eight branch drill holes, labeled: \"D12-1 to D12-8.\"\u003c/p\u003e \u003cp\u003eThis evaluation needs to assess the effectiveness of the completed branches in the Xu Limestone drilling groups D11, D12, and original D2. The total grouting volumes for D11, D12, and original D2 are 33,121 tons, 11,791 tons, and 1,124 tons, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Each branch successfully sealed small fractures and pores during the high-pressure grouting stage, providing a reliable geological foundation for subsequent coal seam mining.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Grouting Data Map for Xu Limestone Aquifer in the Study Area\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Grouting Data for the Fourth and Fifth Limestone Aquifers\u003c/h2\u003e \u003cp\u003eThe treatment of the fourth and fifth limestone aquifers involves six drilling groups within the study area: S1, S2, S4, S11, S12, and S14. The specifics for each drilling group are as follows: ① S1 Drilling Group: Contains five branch drill holes (S1-4, S1-5, S1-6, S1-7, S1-8) with a total grouting volume of 76,678 tons, including 43,703 tons of cement and 22,964 tons of fly ash. ② S2 Drilling Group: Contains five branch drill holes (S2-1, S2-4, S2-6, S2-7, S2-8) with a total grouting volume of 53,774 tons, including 28,007 tons of cement and 16,782 tons of fly ash. ③ S4 Drilling Group: Contains four branch drill holes (S4-1, S4-3, S4-4, S4-7) with a total grouting volume of 56,454 tons, including 34,295 tons of cement and 14,623 tons of fly ash. ④ S11 Drilling Group: Contains seven branch drill holes (S11-1 to S11-7) with a total grouting volume of 65,099 tons. ⑤ S12 Drilling Group: Contains six branch drill holes (S12-2, S12-3, S12-4, S12-5, S12-6, S12-7) with a total grouting volume of 24,976 tons, including 16,887 tons of cement and 8,089 tons of fly ash. ⑥ S14 Drilling Group: Contains one branch drill hole (S14-4) with a grouting volume of 13,389 tons, including 6,702 tons of cement and 324 tons of fly ash. For detailed grouting data, see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Grouting Data Map for fourth and fifth limestone aquifers in the Study Area\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Methodology for evaluating the effectiveness of advanced regional governance","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Statistical Analysis Method for Grouting Data\u003c/h2\u003e \u003cp\u003eBased on the data of ground directional near-horizontal drilling grouting projects in the fourth and fifth limestone aquifers and Xu limestone aquifers in the study area, statistical analysis is conducted on parameters such as final grouting pressure and grouting volume using the standard deviation method and box plot method. The analysis results can provide data support for the zoning system of grouting improvement evaluation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Grading Evaluation Method Based on GIS Data\u003c/h2\u003e \u003cp\u003eThis section outlines a grading evaluation method based on GIS data for the grouting improvement of the fourth and fifth limestone aquifers on the roof of the 11th coal seam and the Xu limestone aquifers on the bottom of the coal seam in the study area.\u003c/p\u003e \u003cp\u003e(1) Data Analysis\u003c/p\u003e \u003cp\u003eCoordinate data from ground directional drilling for grouting at each coordinate point during the grouting improvement are analyzed.\u003c/p\u003e \u003cp\u003eThe trajectory of grouting drillholes is used to compile statistical data for each grouting point.\u003c/p\u003e \u003cp\u003e(2) Thematic Maps Creation\u003c/p\u003e \u003cp\u003eThematic maps for grouting pressure distribution areas and grouting volume distribution areas are created based on the grouting pressure and grouting volume data at each coordinate point.\u003c/p\u003e \u003cp\u003e(3) Zoning Evaluation\u003c/p\u003e \u003cp\u003eThresholds are set for the grouting pressure distribution areas and grouting volume distribution areas to create zoning evaluation maps.\u003c/p\u003e \u003cp\u003e(4) Scientific Evaluation Using GIS Overlay Buffer Algorithm\u003c/p\u003e \u003cp\u003eThe grouting effect in the study area is scientifically evaluated using the overlay buffer algorithm with GIS data layers.\u003c/p\u003e \u003cp\u003eThis method provides a systematic approach to evaluating the effectiveness of grouting in the study area, utilizing GIS data analysis and visualization techniques.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Establishment of the Preemptive Regional Governance Evaluation System\u003c/h2\u003e \u003cp\u003eAn evaluation system for the effectiveness of preemptive regional governance based on ground directional drilling has been established by integrating key processes such as statistical model analysis and GIS modeling data processing, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(1) Qualitative Evaluation\u003c/p\u003e \u003cp\u003eAfter completing the preemptive regional governance project using ground directional drilling, the water-blocking capability of the coal seam floor aquitard is assessed. This can be done using methods such as the water inrush coefficient method (Dong et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and the permeability coefficient method (Hu and Zhao \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Several exploratory drillholes can be arranged along the working face to conduct a qualitative evaluation (Hu et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e(2) Quantitative Evaluation\u003c/p\u003e \u003cp\u003eStep 1: Create thematic maps for the grouting pressure distribution areas and the grouting volume distribution areas based on the coordinate points of the grouting improvement, grouting pressure, and grouting volume data.\u003c/p\u003e \u003cp\u003eStep 2: Perform statistical analysis on the final ground grouting pressure and grouting volume data in the evaluation area using the standard deviation method and the box plot method to establish a threshold setting algorithm for the thematic map zoning.\u003c/p\u003e \u003cp\u003eStep 3: Use the threshold setting algorithm for the thematic map zoning to conduct a zoning evaluation on the grouting improvement pressure distribution areas and the grouting volume distribution areas, resulting in the creation of a grouting volume distribution evaluation map and a final grouting pressure distribution evaluation map for the study area.\u003c/p\u003e \u003cp\u003eStep 4: Perform overlay buffer analysis on the grouting volume distribution evaluation map and the final grouting pressure distribution evaluation map using GIS to ultimately create a thematic evaluation map of the grouting data for the study area.\u003c/p\u003e \u003cp\u003eStep 5: If mine electrical prospecting data (Sun et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) or other drilling exploratory data are available, further overlay analysis can be conducted.\u003c/p\u003e \u003cp\u003eStep 6: For anomalous areas identified in the grouting data evaluation thematic map, conduct underground drilling exploration (Hu et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Set the threshold for single-hole water inflow, and carry out exploration and supplementary underground grouting simultaneously, ensuring full coverage within the working face area.\u003c/p\u003e \u003cp\u003eStep 7: After all supplementary underground grouting meets the standards, trial mining can commence in the working face.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Flow chart for evaluating the effectiveness of advanced regional treatment of limestone aquifers on the roof and floor of deep mining coal seams\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Results and Analysis","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Statistical Analysis of Grouting Data\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e5.1.1 Statistical Analysis of Grouting Volume in Xu Limestone Layer\u003c/h2\u003e \u003cp\u003eBased on the standard deviation method for outlier analysis, the results show that the total grouting volume in the evaluation area is 63,450 m\u0026sup3;, with an average value of 1,294.90 m\u0026sup3;. The overall standard deviation is 2,791.73 m\u0026sup3;, and the sample standard deviation is 2,763.10 m\u0026sup3;. The upper limit for outliers is 9,584.20 m\u0026sup3;, while the lower limit is negative.\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\sigma\\:=\\sqrt{\\frac{\\sum\\:{（{X}_{i}-{\\mu\\:}）}^{2}}{N}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere σ represents the standard deviation, \u0026micro; denotes the mean value, X stands for the individual grouting volume value, and N represents the number of data points.\u003c/p\u003e \u003cp\u003eUpper limit = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\mu\\:\\)\u003c/span\u003e\u003c/span\u003e + 3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sigma\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eLower limit = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\mu\\:\\)\u003c/span\u003e\u003c/span\u003e \u0026minus;\u0026thinsp;3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sigma\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eBased on the box plot analysis, the results indicate that the lower quartile Q1 of the total grouting volume data in the evaluation area is 80, the upper quartile Q3 is 579, and the interquartile range IQR is 499. The upper limit for outlier detection is 1327.5, and the lower limit is a negative value.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Analysis of Outlier Grouting Volumes in the Xu Limestone Evaluation Area\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Statistical Summary of Grouting Volumes in Xu Limestone\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical Summary of Grouting Volumes in Xu Limestone\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrouting volume\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGrouting volume\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGrouting volume\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1364.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e77.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7636.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e380.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e159.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8624.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1049.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e65.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6510.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e558.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e579.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11787.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e387.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e63.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e265.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e785.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e222.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e276.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e560.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e828.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10820.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e254.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e532.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e102.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e514.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e132.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e243.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e137.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e369.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e104.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e181.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e941.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2414.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3422.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e89.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e135.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e236.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e91.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe statistical analysis of ground grouting volume data in the evaluation area, based on the standard deviation method and boxplot method, indicates that the dataset pertains to grouting reinforcement. A higher grouting volume value suggests anomalies (or geological structural control). Considering the dataset's central tendencies, with a median of 236 and an upper quartile Q3 of 579, an upper limit value of 1364 was determined. The proportion of grouting points exceeding 1364 is 14%. Consequently, based on this analysis, the threshold for grouting volume anomalies can be set at 1364 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e5.1.2 Statistical Analysis of Grouting End Pressure in the Xu Limestone Layer\u003c/h2\u003e \u003cp\u003eBased on the standard deviation method for analyzing outliers, the results indicate that the overall value in the evaluation area is 576.80, with a mean of 11.77 and a total standard deviation of 1.46. The sample standard deviation is 1.45. The upper limit for outliers is 16.11, and the lower limit is 7.43.\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:\\sigma\\:=\\sqrt{\\frac{\\sum\\:{（{X}_{i}-{\\mu\\:}）}^{2}}{N}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere σ represents the standard deviation, \u0026micro; denotes the mean value, X stands for the individual grouting volume value, and N represents the number of data points.\u003c/p\u003e \u003cp\u003eUpper limit = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\mu\\:\\)\u003c/span\u003e\u003c/span\u003e + 3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sigma\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eLower limit = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\mu\\:\\)\u003c/span\u003e\u003c/span\u003e \u0026minus;\u0026thinsp;3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sigma\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eUsing the boxplot method to analyze outliers, the results reveal that in the evaluation area, the lower quartile Q1 of the overall grouting pressure data is 11, the upper quartile Q3 is 12.5, and the interquartile range IQR is 1.5. The upper limit for outliers is 14.75, and the lower limit is 8.75.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. illustrates the analysis of outliers in grouting pressure within the evaluation area for the Xu limestone layer\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e Statistical Summary of Grouting Terminal Pressure Data for Xu Limestone Grouting Points\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical Summary of Grouting Terminal Pressure Data for Xu Limestone Grouting Points\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrouting pressure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGrouting pressure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGrouting pressure\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on the statistical analysis using both the standard deviation method and the box plot method for the grouting terminal pressure data in the evaluation area, and considering the grouting reinforcement data, smaller values of grouting pressure indicate anomalies (or geological structure control). The median value of the overall data is 12.20, with the lower quartile Q1 being 11.00. The percentage of grouting points with pressure values less than 8.75 is 4.0%. Therefore, based on the analysis above, the lower limit value of 8.75 is considered as the lower limit for evaluating anomalous grouting pressure values. Additionally, considering that the grouting pressure design parameter is 2 to 2.5 times the water pressure and combining it with practical data, the comprehensive determination of the lower limit of the anomaly value can be set at 8.0 for evaluation (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e5.1.3 Statistical Analysis of Grouting Volume in Fourth and Fifth Limestone Layers\u003c/h2\u003e \u003cp\u003eUsing the standard deviation method to analyze outliers, the results indicate that the total grouting volume in the evaluation area is 278,84 m\u0026sup3;, with an average value of 2,681.16 m\u0026sup3;. The overall standard deviation is 2,206.17 m\u0026sup3;, and the sample standard deviation is 2,195.54 m\u0026sup3;. The upper limit for outliers is 9,267.79 m\u0026sup3;, while the lower limit is negative.\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:\\sigma\\:=\\sqrt{\\frac{\\sum\\:{（{X}_{i}-{\\mu\\:}）}^{2}}{N}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere σ represents the standard deviation, \u0026micro; denotes the mean value, X stands for the individual grouting volume value, and N represents the number of data points.\u003c/p\u003e \u003cp\u003eUpper limit = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\mu\\:\\)\u003c/span\u003e\u003c/span\u003e + 3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sigma\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eLower limit = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\mu\\:\\)\u003c/span\u003e\u003c/span\u003e \u0026minus;\u0026thinsp;3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sigma\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eUsing the box plot method to analyze outliers, the results indicate that within the evaluation area, the lower quartile (Q1) for the total grouting volume data is 965, the upper quartile (Q3) is 3,878, and the interquartile range (IQR) is 2,913. The upper limit for outliers is 8,247.5, while the lower limit is negative.\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. Analysis of Grouting Volume Data in the Evaluation Area for the Fourth and Fifth Limestone\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e Statistical Table of Grouting Volume Data for Fourth and Fifth Limestone\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical Table of Grouting Volume Data for Fourth and Fifth Limestone\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrouting volume\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGrouting volume\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGrouting volume\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10009.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e114.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e205.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2204.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3410.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2155.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5204.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1842.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2417.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3083.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1876.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2423.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7273.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2237.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1887.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5374.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e609.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6435.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4940.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2152.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6213.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e105.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2262.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4385.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1544.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3933.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4491.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3009.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3035.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1729.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e658.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2926.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2509.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1375.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3895.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2243.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7536.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e673.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1285.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3840.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e121.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e258.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e140.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2331.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3292.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1853.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2231.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2253.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6729.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e421.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2205.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e490.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2148.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4623.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3836.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1033.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4183.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e941.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5672.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1772.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1708.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3434.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4037.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e269.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1967.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2203.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3881.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1932.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3398.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e459.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1837.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3877.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e77.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8944.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e228.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2187.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2377.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e321.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4966.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2208.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e95.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3004.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4032.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e622.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1921.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e126.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1951.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2630.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1793.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3852.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e973.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e295.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4002.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9613.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6363.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3337.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4780.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7026.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1069.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e755.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on the results of statistical analysis using the standard deviation method and the box plot method on the grouting volume data in the evaluation area, where the data itself pertains to grouting reinforcement, higher grouting volume values indicate anomalies (or structural control by the strata). The median of the overall data is 2206.5, the upper quartile \u003cem\u003eQ3\u003c/em\u003e is 3878, and grouting points with values greater than 3878 account for 25% of the total. Therefore, according to the above analysis, the upper limit of the grouting volume anomaly value can be set at the third quartile (\u003cem\u003eQ3\u003c/em\u003e) for evaluation (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e5.1.4 Statistical Analysis of Final Grouting Pressure in the Fourth and Fifth Limestone Layers\u003c/h2\u003e \u003cp\u003eBased on the standard deviation method for analyzing outliers, the results show that the overall grouting pressure value in the evaluation area is 961.10, with a mean value of 9.24, an overall standard deviation of 1.55, and a sample standard deviation of 1.54. The upper limit for outliers is 13.88, and the lower limit for outliers is 4.59.\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\:\\sigma\\:=\\sqrt{\\frac{\\sum\\:{（{X}_{i}-{\\mu\\:}）}^{2}}{N}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere σ represents the standard deviation, \u0026micro; denotes the mean value, X stands for the individual grouting volume value, and N represents the number of data points.\u003c/p\u003e \u003cp\u003eUpper limit = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\mu\\:\\)\u003c/span\u003e\u003c/span\u003e + 3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sigma\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eLower limit = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\mu\\:\\)\u003c/span\u003e\u003c/span\u003e \u0026minus;\u0026thinsp;3\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\sigma\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eBased on the box plot method for analyzing outliers, the results show that the overall grouting pressure data in the evaluation area has a lower quartile \u003cem\u003eQ1\u003c/em\u003e of 8.4, an upper quartile \u003cem\u003eQ3\u003c/em\u003e of 10, and an interquartile range (\u003cem\u003eIQR\u003c/em\u003e) of 1.6. The upper limit for outliers is 12.4, and the lower limit for outliers is 6.0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e. illustrates the analysis of grouting pressure in the research area for the fourth and fifth limestone aquifers\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e Statistical Summary of Grouting Pressure Data for the Fourth and Fifth Limestone Aquifers\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical Summary of Grouting Pressure Data for the Fourth and Fifth Limestone Aquifers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrouting pressure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGrouting pressure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGrouting pressure\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on the statistical analysis using the standard deviation method and the box plot method for the ground grouting pressure data in the evaluation area, where lower grouting pressure values indicate anomalies (or structural control), it is observed that the median of the overall data is 9.0, the lower quartile Q1 is 8.4. The percentage of grouting points with pressure values less than 8.4 is 3.8%. Therefore, based on the above analysis, the lower quartile (Q1) value of 8.4 is selected as the lower limit for evaluating abnormal grouting pressure values. Additionally, considering the grouting pressure design parameter being 2 to 2.5 times the water pressure and practical data, a comprehensive determination of the lower limit for abnormal values can be set at 8.0 for evaluation.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e5.2 GIS-Based Grading Evaluation Results\u003c/h2\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e5.2.1 Evaluation of Grouting Effectiveness in the Xu Limestone Aquifer\u003c/h2\u003e \u003cp\u003eBased on the statistical analysis of grouting volume data from surface directional drilling provided by the mining company, and using the natural break method in the GIS system for grading analysis (Sun et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), as well as considering the results of statistical analysis of grouting data, the study area was divided into three grades: stable zone (grouting volume\u0026thinsp;\u0026lt;\u0026thinsp;579 t), transition zone (579 t\u0026thinsp;\u0026le;\u0026thinsp;grouting volume\u0026thinsp;\u0026lt;\u0026thinsp;1364 t), and anomaly area (grouting volume\u0026thinsp;\u0026ge;\u0026thinsp;1364 t); as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e. Thematic Map of Grouting Volume Distribution in the Xu Limestone Aquifer\u003c/p\u003e \u003cp\u003eBased on the grouting data of the Xu limestone aquifer, the grouting pressure of most grouting sections has reached 8 MPa, while a small portion of the grouting sections have not reached 10 MPa. Based on past grouting experience and the relatively high mineralization degree of the Xu aquifer, it is analyzed and judged that there may be concealed structural connections between the fourth and fifth limestone aquifers of the 11th coal seam roof and the underlying Xu and Ao limestone aquifers. Combining this with the results of statistical analysis of the data, this study sets the evaluation criteria for the grouting effect of the Xu limestone aquifer, with the grouting pressure not less than 8.0 MPa considered acceptable. Therefore, based on the completed grouting data of the Xu limestone aquifer and the observation of water stress center displacement data from pumping test observation wells, the grouting effect of the Xu limestone aquifer can be classified into three levels: stable zone (pressure\u0026thinsp;\u0026ge;\u0026thinsp;10 MPa), transitional zone (8.0 MPa\u0026thinsp;\u0026le;\u0026thinsp;pressure\u0026thinsp;\u0026lt;\u0026thinsp;10 MPa), and anomaly zone (pressure\u0026thinsp;\u0026lt;\u0026thinsp;8.0 MPa). This classification is illustrated in the single-item evaluation map of grouting effects in the Xu limestone aquifer (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e. Distribution thematic map of grouting pressure in the Xu limestone aquifer\u003c/p\u003e \u003cp\u003eBased on the grouting volume and grouting pressure of the Xu limestone aquifer in the study area, a comprehensive evaluation is conducted. Using the GIS system, grouting pressure evaluation is weighted at 0.6, while grouting volume evaluation is weighted at 0.4 (with a negative correlation) for overlay evaluation.\u003c/p\u003e \u003cp\u003eFinally, based on the natural classification method in GIS, the effectiveness of the ground directional horizontal grouting treatment in the Xu limestone aquifer area is categorized into three levels: standards-compliant zone, qualified zone, and weak zone, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e. depicts the evaluation of the grouting treatment effectiveness in the Xu limestone aquifer\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e5.2.2 Evaluation of Grouting Effectiveness in the Fourth and Fifth Limestone Aquifers\u003c/h2\u003e \u003cp\u003eBased on the grouting data of the fourth and fifth limestone aquifers in the roof of coal seam 11, most of the grouting sections have reached a final pressure of 8 MPa. However, there are still small sections where the final pressure has not reached 10 MPa. According to previous grouting experiences and the high degree of mineralization in the fourth and fifth limestone aquifers, an analysis suggests the possibility of hidden structural conduits between the fourth and fifth limestone aquifers and the underlying Xu limestone and Ao limestone aquifers. Combining these factors with the results of statistical analysis, the evaluation of grouting effectiveness is set with a criterion that the final pressure should not be less than 8.0 MPa, indicating acceptable grouting effectiveness. Therefore, based on the completed grouting hole data for the roof of coal seam 11 and observations of water stress center displacement from the pumping test in the fourth and fifth limestone aquifers, the grouting effect can be classified into three levels: stable zone (final pressure\u0026thinsp;\u0026ge;\u0026thinsp;10 MPa), transition zone (8.0 MPa\u0026thinsp;\u0026le;\u0026thinsp;final pressure\u0026thinsp;\u0026lt;\u0026thinsp;10 MPa), and anomaly zone (final pressure\u0026thinsp;\u0026lt;\u0026thinsp;8.0 MPa), as illustrated in the single-factor evaluation map of grouting effectiveness for the roof of coal seam 11 in the fourth and fifth limestone aquifers (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e. Distribution thematic map of grouting final pressure in the fourth and fifth limestone aquifers\u003c/p\u003e \u003cp\u003eBased on statistical analysis of grouting volume data from surface directional drilling provided by the mining company, the research area of the fourth and fifth limestone aquifers was categorized into three levels using the natural breakpoints method within the GIS system. This classification was further informed by the statistical analysis of grouting data. The areas were classified as stable (grouting volume\u0026thinsp;\u0026lt;\u0026thinsp;2037 t), transitional (2037 t\u0026thinsp;\u0026le;\u0026thinsp;grouting volume\u0026thinsp;\u0026lt;\u0026thinsp;3871 t), and anomalous (grouting volume\u0026thinsp;\u0026ge;\u0026thinsp;3871 t). The grouting volume was found to be negatively correlated with the evaluation results, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e15\u003c/span\u003e. depicts the thematic distribution of grouting volume in the fourth and fifth limestone aquifers\u003c/p\u003e \u003cp\u003eBased on the comprehensive evaluation of grouting volume and grouting pressure in the top plate fourth and fifth limestone aquifers, a weighted evaluation is conducted using a GIS system, with a weight of 0.6 for grouting pressure evaluation and 0.4 for grouting volume evaluation (negatively correlated).\u003c/p\u003e \u003cp\u003eFinally, based on the natural grading method in GIS, the ground directional horizontal grouting effect in the top plate fourth and fifth limestone aquifers is classified into three levels: standard area, qualified area, and weak area, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig16\" class=\"InternalRef\"\u003e16\u003c/span\u003e. illustrates the evaluation of the grouting consolidation effect in the fourth and fifth limestone aquifers\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Evaluation Mechanism for Advanced Area Treatment of Surface-directed Multi-branch Horizontal Wells\u003c/h2\u003e \u003cp\u003eIn response to the characteristics of advanced treatment of coal mine water hazards using ground directional multi-branch horizontal wells, which can effectively address the lack of underground treatment in areas of delayed or restricted mining, but with grouting effects that cannot be verified underground (according to regulations, area treatment must be completed before conversion to a mineable area), this study proposes a scientific evaluation mechanism.\u003c/p\u003e \u003cp\u003eFirstly, based on surface boreholes or directional horizontal boreholes, the permeability coefficient and sealing capacity of the water barrier layer after grouting are evaluated to conduct the initial qualitative analysis of grouting effects. Secondly, statistical analysis is performed on the surface grouting renovation data (grouting volume, grouting pressure), providing evaluation thresholds for each indicator. Thirdly, GIS-based modeling is utilized to process the data, generating maps for grouting effect evaluation. Fourthly, intensive borehole exploration and supplementary grouting renovation are conducted underground in the anomaly areas identified by the evaluation system. Finally, after all areas in the study region have been evaluated as qualified, trial mining can be conducted in the working face.\u003c/p\u003e \u003cp\u003eThis evaluation mechanism integrates closely with various aspects of mining practices, providing scientifically effective evaluation results to guide safe mine production. It has been validated in multiple mines in the East China region, showing significant effectiveness. This study also proposes, for the first time, the \"Evaluation Method for the Effectiveness of Advanced Area Treatment of Ground Directional Multi-Branch Horizontal Wells,\" as the \"Technical Specification for Advanced Area Treatment of Coal Seam Bottom Limestone Aquifers\" has only been implemented since early 2024, and effective evaluation methods are not yet available.\u003c/p\u003e \u003c/div\u003e"},{"header":"6 Conclusion","content":"\u003cp\u003eThis study addresses the evaluation issue of the effectiveness of high-pressure water hazard prevention during coal seam mining, proposing a series of systematic analysis methods.\u003c/p\u003e \u003cp\u003eFirstly, qualitative analysis of the grouting effect was conducted based on the impermeability and permeability of the water-resistant layer after treatment.\u003c/p\u003e \u003cp\u003eSecondly, utilizing statistical analysis methods, evaluation thresholds for various factors affecting the treatment effect were proposed based on the grouting data of each coordinate point in the advanced treatment area of surface-directed multi-branch horizontal wells.\u003c/p\u003e \u003cp\u003eFinally, through GIS data processing techniques, thematic maps of the evaluated factors were overlaid, and comprehensive evaluation results of the treatment effect in the research area were obtained by combining verification and supplementary grouting processes through intensive drilling underground.\u003c/p\u003e \u003cp\u003eThis study introduces for the first time the \"evaluation method of the treatment effect in the advanced treatment area of surface-directed multi-branch horizontal wells.\" Through practical tests on multiple deep mining faces in the North China coalfield, the effectiveness and reliability of this method have been demonstrated, facilitating safe mining. The findings of this study provide important reference for water hazard prevention in deep coal seam mining, demonstrating significant practical value.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eStatement of Novelty\u003c/h2\u003e\n\u003cp\u003eUsing ground-oriented multi-branch wells for preemptive regional control is currently the most effective method for addressing high-pressure aquifers in deep mines. However, until now, there has been no scientifically validated method for evaluating the effectiveness of such preemptive regional control globally. This study develops a novel mathematical model based on a GIS platform to evaluate the effectiveness of this control method. It significantly reduces construction costs for production mines and has been successfully applied in several deep mining operations in the North China Coalfields, demonstrating remarkable results.\u003c/p\u003e\n\u003ch2\u003eCRediT authorship contribution statement\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eYanbo Hu:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Software, Writing \u0026ndash; original draft, Visualization, Investigation, Validation, Methodology, Formal analysis, Data curation, Conceptualization. \u003cstrong\u003eJingzheng Jiang:\u0026nbsp;\u003c/strong\u003eFormal analysis, Data curation. \u003cstrong\u003eGang Zheng:\u003c/strong\u003e Investigation, Data curation, Conceptualization.\u003c/p\u003e\n\u003ch2\u003eDeclaration of Competing Interest\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003ch2\u003eDeclaration of Generative AI and AI-assisted technologies in the writing process\u003c/h2\u003e\n\u003cp\u003eDuring the preparation of this work, the authors used Google\u0026rsquo;s Gemini and Anthropic\u0026rsquo;s Claude in order to proofread the article, give a final review, and improve its readability. After using these tools, the authors reviewed and edited the content as needed and took full responsibility for the content of the publication.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the China Postdoctoral Science Foundation under Grant 2024M750682, and the Natural Science Foundation of Jiangsu Province under Grant BK20221319.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDong S, Zhang W, Zhou W et al (2021) Discussion on some topical issues of water prevention and control in coal mines. 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Mod Min 39(02):211\u0026ndash;214\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"water damage control, deep mining, GIS, treatment effect","lastPublishedDoi":"10.21203/rs.3.rs-4969049/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4969049/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe text discusses a new method for evaluating the effectiveness of advanced regional treatment of limestone aquifers in coal mining. Since the implementation of the \"Technical specification for advanced regional treatment of limestone aquifer under coal seam\" in early 2024, an effective evaluation method has been lacking. To fill this gap, this study is based on data from surface-directed multi-branch horizontal wells for advanced regional treatment. Using methods such as calculating the water-blocking capacity of the aquifer, statistical analysis of grouting data, and GIS model processing, a multi-factor evaluation model that affects the effectiveness of water hazard governance was constructed, and thematic distribution data of various influencing factors in the research area were obtained. Through mathematical modeling and GIS technology, various factor data were processed to form zoning evaluation data for the effectiveness of grouting transformation. This article proposes an innovative method for evaluating the effectiveness of advanced regional treatment using surface-directed multi-branch horizontal wells by comprehensively utilizing qualitative and quantitative evaluation modes, combined with supplementary exploration data from underground. Experimental results have shown that the evaluation system is effective and provides an important reference for research on water hazard prevention and control in deep coal seam mining.\u003c/p\u003e","manuscriptTitle":"The New Method for Evaluating the Advanced Treatment Effect of Limestone Aquifers in the Roof and Floor of Deep Coal Seam Mining","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-04 18:13:31","doi":"10.21203/rs.3.rs-4969049/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"130295c4-f9b1-427c-ae17-608fb6b055de","owner":[],"postedDate":"October 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-07T00:18:52+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-04 18:13:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4969049","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4969049","identity":"rs-4969049","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}