Fractal characteristics and controlling factors of coal bearing shale pores in the continental fault depression basin of western Liaoning, Northeast China

Fractal characteristics and controlling factors of coal bearing shale pores in the continental fault depression basin of western Liaoning, Northeast China | 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 Article Fractal characteristics and controlling factors of coal bearing shale pores in the continental fault depression basin of western Liaoning, Northeast China Bin Xiao, Guoji Dong, Zhongying Zhao, Zhenhua Yang, Chaojun Fan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5166141/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 micro-pore system in shale serves as the gas storage location, and the characterization of micro-pore structure and fractal features is crucial for reservoir research. The development of porosity in shale reservoirs exhibits significant complexity and heterogeneity. While the study of porosity development characteristics in marine shale reservoirs has advanced, research on coal-system shale reservoirs lags behind and requires comprehensive investigation into their fractal characteristics and controlling factors. The study focuses on the coal bearing shale of the Cretaceous Shahai Formation in the Fuxin Basin. By conducting comprehensive analyses of total organic carbon (TOC), mineralogy, and low-temperature N 2 adsorption experiments, this study investigated the relationship between pore structure characteristics and fractal properties of coal-forming shale, as well as the impact of organic matter content, maturity, and mineral composition on the fractal dimension. The results show that the TOC content of the Shahai Formation shale varies greatly (averaging 3.41%) and is rich in clay minerals (averaging 40.91%). Shale development features ink bottle-shaped pores with narrow necks and wide body, parallel plate-shaped pores with openings on all sides, and possibly slit-shaped pores formed by clay minerals. The shale pores exhibit a distinct dual fractal characteristic, with average fractal dimensions D1 and D2 of 2.5243 and 2.7001, respectively. The internal structure is more complex than the surface structure. The micropores in shale play the most significant role in determining the fractal dimension, and are primarily responsible for the non-uniformity and complexity of the pore structure. Organic matter contributes more to the enhancement of the complexity of internal pore space than the roughness of pore surfaces. The number of micropores in organic matter significantly increases with the degree of thermal evolution of organic matter. Carbonate minerals present in the form of cementing material promote the development of micropores, reduce the proportion of mesopores and macropores, and increase the complexity of pores. The anti compaction ability of clay mineral particles is weak. During the compaction and diagenesis process, mineral particles tend to be oriented and arranged, reducing pore space and simplifying pore morphology, thus reducing the complexity of pores. Related studies will provide scientific theoretical support for the comprehensive evaluation of coal bearing shale reservoirs and the study of oil and gas accumulation theories. They also have some significance in revealing the pore development mechanism of coal bearing shale and selecting favorable reservoirs. Earth and environmental sciences/Solid earth sciences/Geology Earth and environmental sciences/Solid earth sciences/Sedimentology Physical sciences/Energy science and technology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction In response to the changing global energy landscape and to ensure energy security, shale gas, an important unconventional natural gas resource, has garnered widespread attention worldwide following the North American shale gas revolution 1 , 2 . Over the past decade, China has carried out extensive appraisal and exploration trials for shale gas in various regions, and has achieved industrialized exploitation of marine shale gas in the Sichuan Basin. It has also made certain breakthroughs in the exploration and development of continental shale gas 3 , 4 . For instance, the Yanchang Formation of the Upper Triassic in LP177 well in Ordos Basin was effectively stimulated for shale gas production, achieving an initial test production rate of 2,350 m 3 per day 5 . The XG57 well in the Qikou depression of the Bohai Bay Basin obtained an industrial gas flow of 13.7 × 10 4 m 3 per day from shale gas testing in the third section of the Shahejie Formation of the Paleogene Eocene 6 . China possesses extensive sedimentary basins rich in terrestrial organic-rich shale. The exploitable resources of terrestrial shale gas in China constitute over 30% of the country's total shale gas reserves, and exploration and development efforts have confirmed the considerable resource potential of terrestrial shale gas in China 7 . A large number of Mesozoic small and medium-sized fault basins have developed in Northeast China (Fig. 1 a, b). Thanks to the vigorous volcanic activity during the Cretaceous period, the maturation and gas generation of shale organic matter in this area have been accelerated, providing the prerequisite for shale gas accumulation and enrichment. It is an important area for continental shale gas exploration in China 8 , 9 . The Fuxin Basin is a typical continental fault basin in Northeast China. The Shahai Formation in the Fuxin Basin has favorable geological conditions for the formation of shale gas, and this coal bearing shale is widely distributed in the basin 10 . At present, research on the microscopic pore structure and fractal characteristics of shale reservoirs in the Shahai Formation of the Fuxin Basin is relatively weak, which restricts the fine evaluation and analysis of coal bearing shale reservoirs and the effective assessment of resource reserves, and is not conducive to the exploration and development process of shale oil and gas in the basin. As a kind of unconventional reservoir, shale usually has the characteristics of low porosity and low permeability 11 , 12 . The pore structure and its complexity directly affect the occurrence state of shale gas and are important contents of shale reservoir evaluation 13 . A large number of nanoscale micro pores are developed in shale, and the fracture morphology is complex and interwoven, collectively forming a complex network of pores and fractures. There are certain differences in the occurrence state of shale gas in pores with different pore sizes. Shale gas in micropores and smaller mesopores mainly exists in an adsorbed state, while in macropores, the free gas volume fraction is high 14 , 15 . The volume fraction of adsorbed gas in shale can reach up to about 80%, which is controlled by the complexity of pores 16 . The parameters such as pore volume, specific surface area, and pore size distribution play an important role in characterizing the pore structure 17 . However, due to the influence of multiple factors such as the content and distribution of organic matter and inorganic minerals on the development of shale pores, it has brought difficulties to the quantitative evaluation of shale pore structure 18 . With the introduction of fractal theory, it has gradually become an important method for characterizing the complexity of pore structure in porous materials. In the investigation of shale pore structure, it was observed that organic-rich shale micropores exhibited well-developed heterogeneity and possessed characteristics typical of a porous medium. Consequently, fractal dimension can be employed to quantitatively characterize the complexity of these pores 19 . The fractal dimension is defined as an interval value of 2–3, and the more significant the fractal, the larger the value 20 , 21 . The fractal dimension can quantitatively describe the self similarity of fractal systems and is a key indicator for quantitatively characterizing the heterogeneity and complexity of pore development, which is extremely important for shale reservoir evaluation 22 . At present, research on pore fractals in coal bearing shale reservoirs and their impact on shale gas adsorption control is still relatively weak. Based on this, this study systematically explores the fractal dimension of coal bearing shale in the Shahai Formation of the Fuxin continental fault depression basin and its relationship with mineral composition, organic matter content, maturity, and pore structure, based on the results of low-temperature nitrogen adsorption experiments. This has certain significance for revealing the pore development mechanism of coal bearing shale, micro reservoir evaluation, and favorable reservoir selection. Geological setting The tectonic location of the Fuxin Basin is in the northern part of the North China Plate and the northeastern part of the Yanshan orogenic belt 24 . The Fuxin Basin is a terrestrial fault basin that extends in the NNE-NE direction, with an area of approximately 1500km 2 (Fig. 1 c) 23 . The accumulated sediments were controlled by the Lvshan fault in the eastern basin and the Songling fault in the western basin (Fig. 1 c) 23 . Sedimentary strata on the plane were controlled by faults, forming a structural pattern between depressions and uplifts. From north to south, the basin can be divided into the Xinqiu sag, Fuxin structural belt, Haizhou sag, Dongliang structural belt, Yimatu sag, Qinghemen-Aiyou structural belt, Minjiatun sag, and other structural belts (Fig. 1 c) 23 . The tectonic evolution of the Fuxin Basin has roughly gone through three stages of development: the initial extensional stage (sedimentary period of the Yixian Formation of the Lower Cretaceous), the development stage of fault depression (sedimentary period of the Jiufotang Formation, Shahai Formation, and Fuxin Formation of the Lower Cretaceous), and the extrusion reversal stage (sedimentary period of the Sunjiawan Formation of the Lower Cretaceous) 25 . From bottom to top, the Fuxin Basin has developed the Lower Cretaceous Yixian Formation (K 1 y), Jiufotang Formation (K 1 jf), Shahai Formation (K 1 sh), Fuxin Formation (K 1 f), and Sunjiawan Formation (K 1 s) 26 . Since the early stage of the formation of the Fuxin Basin during the Late Jurassic Yanshanian period, there has been strong volcanic and magmatic activity, which led to the formation of the Yixian Formation during the initial extensional period; During the development period of the fault depression, the Jiufotang Formation was first deposited. During the Yanshan tectonic activity, the strata of this formation were folded and deformed, and the subsidence center shifted eastward, depositing the Shahai Formation and Fuxin Formation; During the extrusion reversal period, the Sunjiawan Formation was deposited 25,26 . The Shahai Formation in the Fuxin Basin is rich in organic coal bearing shale reservoirs, and multiple drilling wells have discovered oil and gas indications, indicating good prospects for shale gas exploration and development. In addition, according to the drilling results of the DY-1 well in the Dongliang tectonic belt of the Fuxin Basin, good gas logging values were directly displayed in the third and fourth sections of the Shahai Formation. On site desorption work confirmed the presence of good desorption gas, and multiple sections of good light oil were shown on the extracted core samples. This directly confirms that the local area has favorable geological conditions for the formation of shale oil and gas. Sample collection and experimental methods A total of 16 shale samples were collected from well DY1, which is located in the southern flank of the Dongliang anticline in the north–central part of the Fuxin Basin (Fig. 1 c). These 16 drilling core samples were mainly collected from the third and fourth sections of the Shahai Formation (Fig. 1 d). Among them, there are 5 shale samples from the third section of the Shahai Formation (K 1 Sh 3 , sample no. Y01-Y05) and 11 shale samples from the fourth section of the Shahai Formation (K 1 Sh 4 , sample no. Y06-Y16). The CS580A carbon sulfur analyzer produced by Eltra, Germany was used to test the total organic carbon (TOC) content of the samples. Before testing, the sample is subjected to low-temperature drying treatment. The dried sample is placed in an agate mortar and ground to 80 mesh or more, and 100mg of powder sample is weighed. The sample was soaked for 24 h to remove carbonate and other inorganic carbon. Rinse the soaked sample with distilled water until the entire sample is neutral. Bake neutral samples at low temperature until dry, and then test them on the machine. According to repeated analysis of standard samples,the accuracy of the TOC content analysis is better than ± 0.5%. The Ro was measured with a Leica MPV–SP equipped with 50 magnification oil immersion lens and 10 magnification eyepiece. The polished core sample was observed microscopically and random reflectance values were measured on the primary vitrinite using two standards (sapphire, 0.6% and gadolinium–gallium–garnet, 1.7%). At least 20 points were counted 9 . The whole rock mineral analysis was carried out using a Japanese Rigaku D/Max 2500 PC powder X-ray diffractometer (XRD). Before experimental testing, the shale sample needs to be crushed into a 200 mesh powder, and 500 mg of the sample should be weighed and filled into a thin sheet with grooves, keeping the surface of the sample flat and consistent with the surface of the sheet. The test was conducted at room temperature, with instrument parameters including Cu target, Kα - ray, X-ray tube voltage and current of 40 kV and 150 mA, scanning speed of 4°/min, step size of 0.02°, starting angle of 2°, and ending angle of 70°. The equipment used for low-temperature nitrogen adsorption testing is the ASAP 2020 fully automatic surface area and pore size distribution analyzer developed by Micromeritics Instrument in the United States 27 . Before testing, the shale sample is crushed into 40–80 mesh and degassed under vacuum conditions at approximately 110 ℃ for about 5 hours to remove adsorbed water and capillary bound water. Then the powder sample was placed into the analyzer for low-temperature nitrogen adsorption measurement. The P/Po (relative pressure) range for N 2 physisorption was from 0.01 to 0.99, where P is the absolute gas vapor pressure, and Po is the saturation pressure. By increasing the relative pressure from 0.01 to 0.99 to reach the saturated vapor pressure of nitrogen and gradually decreasing the pressure, the adsorption capacity of N 2 at different relative pressures P/P 0 was measured 20 . Results Maturation, TOC, and mineral composition. Table 1 shows the TOC and Ro values of the studied representative 16 shale samples from the Shahai Formation. The TOC content of shale samples ranges from 1.53–9.05%, with an average value of 3.41%, indicating an overall high organic matter content. The Ro range of shale samples is 0.48%~1.88%, with an average value of 0.89%. The Ro range of the shales in the third section of the Shahai Formation is 1.01%-1.88%, with an average of 1.48%, indicating that the shales are medium-high mature. The Ro range of shale in the fourth section of the Shahai Formation is 0.48%~0.85%, with an average of 0.62%, indicating that the shales are medium-low mature. From the changing trend of Ro, it can be found that the shale in this study is increasing in maturity with the increasing of burial depth. The mineral compositions of 16 shale samples are listed in Fig. 2 and Table 1 , which reveals that shales in this study are mainly composed of clays, quartz, feldspa, carbonates (calcite and dolomite) and pyrite. The content of clays in shale samples ranges from 11.92–55.28%, with an average of 40.91%. The content of quartz ranged from 16.16–36.07%, with an average of 27.09%. In this study, the feldspar mineral types of shale samples are mainly plagioclase, containing a small amount of k-feldspar. The content of carbonate minerals varies greatly, some shales do not contain carbonate minerals (Y05), while some shales contain 59.94% carbonate minerals (Y02). The pyrite, siderite and halite are only developed in a few shale samples. Table 1 . Organic petrographic characteristics and mineralogical composition of shale samples from Shahai Formation. Sample TOC(%) Ro(%) Clays(%) Quartz(%) Feldspar(%) Calcite(%) Dolomite(%) Pyrite(%) Siderite(%) Halite(%) Y01 2.95 1.88 32.89 27.10 7.92 0.00 29.10 2.99 0.00 0.00 Y02 1.53 1.71 11.92 24.09 7.05 44.96 11.98 0.00 0.00 0.00 Y03 9.05 1.53 24.98 25.15 5.97 32.98 0.00 10.92 0.00 0.00 Y04 8.17 1.29 41.02 33.08 22.03 3.87 0.00 0.00 0.00 0.00 Y05 3.51 1.01 55.28 31.86 11.79 0.00 0.00 0.00 0.00 1.07 Y06 2.41 0.85 45.94 36.07 16.05 1.94 0.00 0.00 0.00 0.00 Y07 2.48 0.79 47.00 25.14 14.99 1.95 7.92 3.00 0.00 0.00 Y08 2.32 0.72 44.00 30.07 13.93 6.00 6.00 0.00 0.00 0.00 Y09 2.93 0.64 44.00 25.16 14.98 0.88 8.99 5.99 0.00 0.00 Y10 2.45 0.61 42.95 16.16 11.99 0.87 17.07 10.96 0.00 0.00 Y11 4.23 0.56 44.88 33.03 16.95 1.08 1.94 2.12 0.00 0.00 Y12 2.70 0.55 41.00 25.14 18.87 0.00 11.99 3.00 0.00 0.00 Y13 1.98 0.54 42.93 28.17 13.91 7.06 7.93 0.00 0.00 0.00 Y14 1.95 0.53 49.99 26.04 14.99 2.12 2.98 0.00 2.99 0.89 Y15 2.57 0.51 42.93 21.11 11.97 20.99 3.00 0.00 0.00 0.00 Y16 3.40 0.48 42.92 26.05 14.09 12.88 1.06 0.00 3.00 0.00 Note: TOC = total organic carbon; Ro = equivalent vitrinite reflectance. N 2 physisorption and pore structure characteristics. Figure 3 shows the N 2 adsorption and desorption curves for the sixteen shale samples. The N 2 adsorption isotherm of all samples showed reversed S-shaped and have distinct hysteresis loops, which are generally due to capillary condensation, pore blocking, or the ink-bottle effect . Combined with the IUPAC classification , the hysteresis loops of shale samples adsorption-desorption isotherms is clearly exhibiting three types (H3 for Y-14 and Y-16; H4 for Y01, Y03, Y05, Y06, Y07, Y08, Y11, Y13,and Y15; H3-H4 for for Y02, Y04, Y09, Y10, and Y12). The first type is the H3 type adsorption isotherm hysteresis loop, represented by the Y16 sample. This type of adsorption isotherm steadily increases with the increase of relative pressure (P/P0), and suddenly increases when the relative pressure approaches 1. The hysteresis loop is small, and the adsorption curve and desorption curve almost completely overlap (Fig. 3 ). This type of hysteresis loop is generated by the non-rigid plate-like aggregates of irregularly sized particles (such as certain clays) or by a pore network consisting of macroscopic pores filled with partially filled pore fluids 29 . Shales that develop such pores typically have a high content of clay minerals, as the pores formed by clay minerals are usually narrow slit shaped 27 . The second type is the H4 type adsorption isotherm hysteresis loop, represented by the Y03 sample. This type of adsorption isotherm steadily increases with the increase of relative pressure (P/P0). The desorption isotherm slowly decreases in the initial stage of relative pressure reduction, and suddenly decreases when P/P0 reaches 0.5(Fig. 3 ). This is due to the large amount of liquid nitrogen in the ink bottle hole being released and vaporizing at once 29 . This type of adsorption loop indicates that shale is mainly characterized by ink bottle shaped pores with fine necks and wide bodies . The third type is the hysteresis loop of adsorption isotherms between H3 and H4, represented by the Y12 sample. This type of adsorption isotherm exhibits a relatively flat beginning segment, where the adsorption and desorption curves do not overlap, followed by a steep end with an indistinct inflection point in the desorption curve (Fig. 3 ). The hysteresis loop of this type of adsorption isotherm indicates that shale is mainly composed of parallel plate-like pores with uniformly open edges, and there are a small number of ink bottle shaped pores . All the N2 adsorption isotherms indicate that micropore filling mainly occurs at low P/P0 (< 0.5), and the N2 adsorption volume gradually increases to reach the highest values at high P/P0 (≈ 1.0). When the P/P0 approaches 1, the slope of the H3 type N2 adsorption isotherm is significantly higher than that of the H4 type (Fig. 3 ), suggesting that more macropores (> 100 nm in diameter) or microfractures are present in H3 shale than in H4 shale samples. Based on low-temperature N 2 adsorption experiments, the pore structure parameters of shale reservoirs (including total pore volume, average pore diameter, and specific surface area) can be quantitatively analyzed, as shown in Table 2. Based on the Barret-Joyner-Halenda (BJH) model and Brunauer-Emmett-Teller (BET) model , the total pore volume and total specific surface area were obtained to be 0.0107 ~ 0.0240 cm 3 /g (average 0.0176 cm 3 /g) and 4.0959 ~ 15.2736 m 2 /g (average 8.2351 m 2 /g), respectively. Figure 4 shows that the volume proportions of micropores, mesopores, and macropores are 0.11%~5.19% (average 1.77%), 70.44%~81.48% (average 76.49%), and 13.33%~28.25% (average 21.74%), respectively. The pore size of coal bearing shale is generally higher than that of marine shale, with mesopores and macropores as the main pore scale types , . Table 2. Measurement of the physical parameters of shale samples by low-temperature nitrogen adsorption. Sample Total pore volume (cm 3 /g) Average pore diameter (nm) Specific surface area (m 2 /g) D1 D2 Y01 0.0165 5.52 12.53 2.6458 2.7939 Y02 0.0202 6.44 13.06 2.6418 2.7524 Y03 0.0188 5.57 15.27 2.6073 2.8117 Y04 0.0221 8.21 10.11 2.4658 2.7155 Y05 0.0211 7.44 11.14 2.5687 2.7240 Y06 0.0189 9.11 7.70 2.4529 2.7055 Y07 0.0107 11.03 4.10 2.5869 2.7196 Y08 0.0165 7.69 9.92 2.5000 2.7539 Y09 0.0139 11.86 5.18 2.4550 2.6402 Y10 0.0154 14.06 4.70 2.4885 2.6045 Y11 0.0141 10.46 5.78 2.5366 2.7157 Y12 0.0117 10.94 4.60 2.5345 2.6832 Y13 0.0196 10.49 7.24 2.4915 2.6808 Y14 0.0172 13.50 4.87 2.4671 2.5973 Y15 0.0217 10.64 7.60 2.4361 2.6638 Y16 0.0240 11.58 7.95 2.5110 2.6395 Note: D1 and D2 = Surface fractal dimension from N 2 physisorption. Fractal dimension features. The quantitative evaluation of fractal geometry is described using the fractal dimension D. Currently, based on nitrogen adsorption/desorption data, the FHH (Frenkel-Halsey-Hill) method is widely used for fractal characterization of porous media , . This FHH method is defined as: Ln(V) = (D-3) × Ln(Ln(P 0 /P) + Constant (1) Where V is the amount of gas that has been adsorbing; P represents equilibrium pressure; P 0 is the saturated vapor pressure; D is the surface fractal dimension. Based on N 2 adsorption data and FHH model, we can plot two different linear segments at P/P0. With P/P0 = 0.5 as the boundary, the pore fractal dimension is D1 when P/P0 < 0.5, and D2 when P/P0 ≥ 0.5. The fractal dimension values D1 and D2 can be quantitatively obtained by linearly fitting the slope of a line between Ln(V) and Ln(Ln(P0/P)) (Fig. 5 ). The linear fitting coefficient is above 0.94, indicating a good fitting effect and significant fractal characteristics. The calculation results show that the coal bearing shale of the Shahai Formation exhibits significant pore fractal characteristics, with strong heterogeneity and roughness. The calculated fractal dimensions D1 and D2 are between 2.4361 and 2.6458 (with an average of 2.5243) and 2.5973 to 2.8117 (with an average of 2.7001), respectively. D2 is generally higher than D1, indicating that compared to the surface structure, the internal characteristics of pores are more complex. Discussion The size of fractal dimension is influenced by multiple factors. Generally speaking, any factors that affect the development of micro pores will have an impact on the fractal dimension, which can be divided into two aspects: organic pore development factors and inorganic pore development factors. The pore structure directly affects the gas occurrence state and total gas content. The relative size of pore volume and specific surface area can reflect the gas adsorption capacity of pores, while the fractal dimension of shale essentially reflects the complexity of pores 38 , 39 . Therefore, there is a natural intrinsic relationship between specific surface area, pore volume, and fractal dimension. The effect of pore structure on fractal characteristics. In order to explore the influence of shale pore structure on fractal characteristics, this study systematically analyzed the correlation between fractal dimension and pore volume, specific surface area and average pore diameter (Fig. 6 ). There is no significant correlation between the total pore volume of shale and fractal dimensions D1 and D2, with correlation coefficients of 0.0228 and 0.0005, respectively (Fig. 6 a). The micropore volume shows a good positive correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.3309 and 0.4844, respectively (Fig. 6 b). There is no significant correlation between mesoporous volume and fractal dimensions D1 and D2, with correlation coefficients of 0.0127 and 0.0170, respectively (Fig. 6 c). The macro pore volume shows a good negative correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.1747 and 0.2865, respectively (Fig. 6 d). The percentage of micropore volume shows a good positive correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.3918 and 0.5465, respectively (Fig. 6 e). There is no significant correlation between mesoporous volume percentage and fractal dimension D1, but a weak positive correlation with D2, with correlation coefficients of 0.0230 and 0.2879, respectively (Fig. 6 f). The macro pore volume percentage shows a weak negative correlation with fractal dimension D1, and a strong negative correlation with D2, with correlation coefficients of 0.1218 and 0.4581, respectively (Fig. 6 g). The specific surface area shows a good positive correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.3219 and 0.6129, respectively (Fig. 6 h). The average pore size of shale ranges from 5.52nm to 14.06nm, with an average of 9.66nm. The average pore size shows a strong negative correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.4065 and 0.8851, respectively (Fig. 6 i). The correlation coefficients between the volume percentages of micropores, mesopores, and macropores and fractal dimension show good positive correlation, weak correlation, and negative correlation, respectively, indicating that micropores in shale contribute the most to fractal dimension and are the main cause of heterogeneity and complexity in pore structure. As the volume of micropores increases, the pore structure of shale becomes more complex, and the specific surface area also increases, enhancing its ability to adsorb gases. This is mainly related to the pore diameter of shale. Micropore diameters below 2nm contribute less than 10% to the pore volume, but micropores can provide over 80% of the specific surface area 20 . Therefore, the presence of micropores has a significant impact on the amount of adsorbed gas. On the one hand, micropores have a larger specific surface area and provide more gas active adsorption sites, which can accommodate a greater amount of adsorbed gas; On the other hand, shale, as a porous medium, the smaller the pore size, the stronger the adsorption potential (Ea) of hydrocarbon gases on the inner walls of the pores, that is, the tighter the gas adsorption, and the stronger the adsorption capacity of the pores 40 . Therefore, according to the size of the pore size, the strength of gas adsorption capacity in shale pores is micropores > mesopores > macropores 41 . At the same time, there is a good correlation between the fractal dimension of shale pores and the specific surface area (Fig. 6 h), indicating that the pore adsorption capacity can be characterized by the size of the fractal dimension. The larger the fractal dimension of shale, the more developed the micropores in shale, which can provide more gas adsorption sites and greater adsorption potential. The pores have stronger adsorption capacity for shale gas, resulting in a higher proportion of adsorbed gas content in shale. In addition, there is a high negative correlation between the fractal dimension values D1 and D2 of pores and the average pore diameter (Fig. 6 i), that is, as the average pore diameter decreases, the fractal dimension values increase. Due to the irregularity of pores, the pore volume cannot be directly characterized by the average pore size, but pores with smaller average pore sizes tend to have a decreasing pore volume. The smaller the pore diameter, the larger the pore specific surface area, resulting in an increase in the fractal dimension of the pores 11 . Therefore, it can be inferred that small pore size is an important reason for the non-uniformity of shale pore structure. The effect of organic matter content and maturity on fractal characteristics. There is a strong linear correlation between the fractal dimensions D1 and D2 of the coal bearing shale in the Shahai Formation of the research area, with a correlation coefficient of 0.5026 (Fig. 7 a). This indicates that there is a good correspondence between the heterogeneity and complexity of the pore surface and internal space of coal bearing shale, that is, the more complex the pore surface of shale, the more complex the internal structure of the pores. From Fig. 7 b, it can be seen that there is no significant correlation between D1 and TOC content in the coal bearing shale of the Shahai Formation, while D2 shows a weak positive correlation with TOC content. This indicates that organic matter increases the internal spatial complexity of pore structures more than the surface roughness of pores. This is because organic matter usually develops micropores, which enhances the heterogeneity of the internal space of the pores 42 . The more complex the pore structure of shale, the higher the fractal dimension of the pores, and the enhanced the adsorption capacity of shale, which is more conducive to the storage of natural gas 43 , 44 . The good correlation between TOC content and micropore volume and specific surface area (Fig. 8 ) indicates that organic matter has a high contribution to micropores. At different stages of organic matter thermal evolution, there may be differences in the degree of organic pore development, pore size, and pore morphology 45 . Therefore, the degree of thermal evolution of organic matter has a certain controlling effect on the complexity of pores. As mentioned earlier, the organic matter in the shale of the Shahai Formation in the study area is in the low to high maturity stage. The correlation coefficients between the thermal evolution degree of shale samples in the study area and the pore fractal dimensions D1 and D2 are 0.5318 and 0.5914, respectively (Fig. 7 c). On the one hand, in the shale maturity to the early stage of high maturity, as the Ro value increases, the number of micropores in the organic matter significantly increases, and the organic matter undergoes aromatization, thereby increasing the roughness of the pore walls, which increases the specific surface area of the pores 46 . The good positive correlation between Ro and micropore volume and specific surface area shown in Fig. 8 also confirms the above inference. On the other hand, as the burial depth increases, the enhancement of organic matter aromatization also leads to a decrease in pore support capacity. Under the pressure of the overlying strata, the pores undergo irregular deformation, increasing the complexity of the pores and resulting in an increase in the fractal dimension of shale 31 . The effect of mineral components on fractal characteristics. The main inorganic minerals in the coal bearing shale of the Shahai Formation are clay minerals, quartz, feldspar, and carbonate minerals. By analyzing the correlation between mineral content and fractal dimension, the results showed a negative correlation between clay mineral content and shale fractal dimensions D1 and D2, with correlation coefficients of 0.3509 and 0.2659, respectively (Fig. 7 d). This may be due to the increase in clay mineral content in shale of the Shahai Formation, which leads to a decrease in the volume of micropores and mesopores in the shale (Fig. 8 ). There is a good positive correlation between brittle minerals and shale fractal dimensions D1 and D2, with correlation coefficients of 0.3509 and 0.2659, respectively (Fig. 7 e); The content of feldspar minerals is negatively correlated with fractal dimensions D1 and D2, with correlation coefficients of 0.3870 and 0.1837, respectively (Fig. 7 g); The content of carbonate minerals is positively correlated with fractal dimensions D1 and D2, with correlation coefficients of 0.3287 and 0.1289, respectively (Fig. 7 h). The brittle minerals here mainly include quartz, feldspar, carbonate minerals, and a small amount of pyrite. There is a good positive correlation between the content of brittle minerals and fractal dimension. This is significantly different from marine shale 47 , 48 . The reason may be that the brittle minerals in marine shale are mainly quartz, feldspar, and pyrite, with only a small amount of carbonate minerals. These brittle minerals usually have regular crystal structures, with pore scales mostly consisting of mesopores and macropores, which are relatively homogeneous and reduce the fractal characteristics of pore structures 49 . However, carbonate minerals are more developed in the coal bearing shale of the Shahai Formation (Fig. 2 ), and there is a good positive correlation between carbonate mineral content and micropore volume (Fig. 8 ), which mainly contributes to increasing the complexity of pore structure. As a direct carrier for the development of inorganic pores, the type and content of diagenetic minerals affect the development and distribution of pores, and there are significant differences in the types of pores developed in different types of minerals (Fig. 9 ). Vertical fractures can be observed from some drilling cores, with calcite filling inside the fractures (Fig. 9 a). After scanning electron microscopy observation of coal bearing shale samples from the Shahai Formation, it was found that there were relatively few nano pores in the organic matter (Fig. 9 ). Nano scale pores are mainly composed of intergranular pores between mineral particles such as pyrite and quartz (Fig. 9 b, c, d), and intragranular pores within carbonate mineral particles (Fig. 9 e, f, g). In addition, nanoscale and micrometer scale organic matter pores can be observed within the organic matter (Fig. 9 h, i), as well as organic matter shrinkage cracks and matrix cracks developed at the edges of the organic matter (Fig. 9 j, k, l). Clay minerals, as one of the important inorganic minerals, are important carriers of shale pores. The content of clay minerals is negatively correlated with the fractal dimensions D1 and D2 of shale (Fig. 7 d). Combined with the negative correlation between clay mineral content and shale pore volume and specific surface area (Fig. 8 ), it indicates that the development of clay minerals has an inhibitory effect on the increase of micropores. The reason may be that shale has a high content of clay minerals, with small clay mineral particles and weak compaction resistance. During long-term compaction and diagenesis, clay mineral particles tend to be oriented, reducing pore space and simplifying pore morphology. The compaction effect leads to a decrease in the number of micropores, with mesopores and macropores developing mainly. The development of clay minerals leads to a large number of microcracks in shale, with wide fracture widths (Fig. 9 c, k), which also results in a negative correlation between the volume fraction of clay minerals and the fractal dimension of shale. Quartz has strong resistance to compaction and dissolution, and the pores developed within quartz are limited 50 , with smaller pore sizes (Fig. 9 d). Regarding the influence of quartz on the development of shale micropores, different scholars hold different views in the actual research process. Some studies suggest a negative correlation between quartz content and shale pore complexity 51 . However, the results of this study showed a weak positive correlation between quartz content and shale fractal dimension D2 (Fig. 7 f), which may be due to the biogenesis of siliceous minerals in the coal bearing shale of the Shahai Formation in the study area. In the early Cretaceous, the Fuxin Basin was in an extensional environment, with deepening lake water and widespread development of diatomaceous plankton, which converted soluble silicon in the water into amorphous silicon to form bones 9 . These organisms have complex siliceous shells. After the death and deposition of the organisms, their soft tissues are transformed into organic matter and distributed in the biological cavities. The residual biological siliceous skeleton increases the brittleness of shale, while the irregular intergranular pores formed by the accumulation of siliceous debris in the biological cavities also increase the complexity of the pores. Based on the correlation analysis between TOC content and quartz content, it can be concluded that there is a good positive correlation between the two, indicating the presence of a certain amount of biogenic quartz in the shale of the Shahai Formation (Fig. 8 ). The irregular accumulation of siliceous biological skeletons and siliceous debris leads to the complexity of pore structure. As an aluminosilicate mineral, feldspar is easily dissolved and eroded by fluids under burial conditions 52 . Therefore, under the dissolution of formation fluids, feldspar is prone to form mesopores and macropores with larger pore sizes. In addition, feldspar has strong brittleness, which can lead to the development of cleavage cracks under geological conditions, thereby increasing the equivalent pore size of pores, resulting in a negative correlation between feldspar content and pore fractal dimensions D1 and D2 (Fig. 7 g). The content of carbonate minerals is positively correlated with the fractal dimension of shale pores (Fig. 7 h). The presence of carbonate minerals in shale has a "duality" in the development of pores: during diagenesis, some precipitated carbonate minerals fill the pores in the form of cement, causing pore blockage and reduction in pore size. In this case, micropores are usually retained, the proportion of mesopores and macropores is reduced, and the complexity of pores is increased 53 . During the burial process, carbonate minerals, as easily soluble components, form dissolution pores under the dissolution of formation fluids and organic acids, usually dominated by mesopores and macropores, which reduces the proportion of micropore development 53 . Carbonate mineral dissolution is usually stronger than cementation in ancient marine shale 54 . However, as shown in Fig. 8 , there is a significant positive correlation between carbonate minerals and micropores in the shale samples of the study area. Based on this, it is speculated that the mineral cementation of carbonate rocks in shallow buried Mesozoic continental shale is stronger than dissolution. Carbonate minerals in the form of cement promote the development of micropores. Therefore, there is a weak positive correlation between carbonate mineral content and shale fractal dimension. Conclusions (1) The shale TOC content of the Shahai Formation in the Fuxin Basin varies greatly (with an average of 3.41%) and is rich in clay minerals (with an average of 40.91%). The nitrogen adsorption shows that the shale pore structure contains ink bottle shaped pores with fine necks and wide tubes, parallel plate-like pores with openings on all sides, and possibly narrow slit shaped pores formed by clay minerals. (2) The shale pores of the Shahai Formation have obvious dual fractal characteristics. The average values of fractal dimensions D1 and D2 are 2.5243 and 2.7001, respectively. D2 is generally larger than D1, and the fractal dimension values are more concentrated, reflecting that the internal structure of pores is more complex than the surface structure. (3) The micropores in the Shahai Formation shale contribute the most to the fractal dimension, which is the main reason for the heterogeneity and complexity of the pore structure. The smaller the pore size, the larger the pore specific surface area and the more complex the pore structure, resulting in an increase in the fractal dimension of the pore. This can provide more gas adsorption sites and greater adsorption potential, which is beneficial for shale gas enrichment. (4) The increase in internal spatial complexity of pore structure by organic matter in Shahai Formation shale is stronger than the increase in surface roughness of pores. As the Ro value increases, the number of micropores in organic matter significantly increases with the degree of thermal evolution of organic matter. (5) The carbonate minerals and clay minerals in the shale of the Shahai Formation have a significant impact on the fractal dimension of pores. On the one hand, carbonate minerals in the form of cement promote the development of micropores, reduce the proportion of mesopores and macropores, and increase the complexity of pores. On the other hand, the anti compaction ability of clay mineral particles is weak. During the compaction and diagenesis process, mineral particles tend to be orientation arranged, reducing pore space and simplifying pore morphology, thus reducing the complexity of pores structure. Declarations Author Contribution B.X. and G.J.D. wrote the main mauscript text. Z.Y.Z. designed the research. Z.H.Y. and C.J.F. collected and analyzed samples. C.H.J. discussed the results. S.L. supervised the fndings of this work. All authors reviewed the manuscript. Acknowledgement This work was supported by the Project of the Natural Science Foundation of Liaoning Province (Grant No. 2022-BS-328), and the National Natural Science Foundation of China (Grant No. 52174117 and 42274129). Data Availability All data generated or analysed during this study are included in this published article [and its supplementary information files]. References Nie, H. K. et al. Deep shale gas in the Ordovician-Silurian Wufeng–Longmaxi formations of the Sichuan Basin, SW China: Insights from reservoir characteristics, preservation conditions and development strategies. J. Asian. Earth. Sci . 244 , 1-21 (2023). Qiu, Z. et al. Revisiting paleoenvironmental changes on the Upper Yangtze Block during the Ordovician-Silurian transition: New insights from elemental geochemistry. Sediment. Geol. 450 , 1-16 (2023). Xiao, B. et al. Elemental geochemical characteristics of Shales from Wufeng−Longmaxi Formations in the southern margin of the Qinling Orogenic Belt, China: Implications for depositional controls on organic matter. ACS Omega (2024). DOI: 10.1021/acsomega.4c01129. Zhao, Z. Y. et al. Heat-Induced Pore Structure Evolution in the Triassic Chang 7 Shale, Ordos Basin, China: Experimental Simulation of In Situ Conversion Process. J. Mar. Sci. Eng. 11 (7), 1163 (2023). Jiang C. F., Cheng Y. Q., Fan B. J. & Gao S. L. Progress in and challenges to geologic research terrestrial shale in China: A case study from the 7th member of the Upper Triassic Yanchang Fm in the Yanchang exploration block, Ordos Basin. Natur. Gas Ind. 34 (2), 27-33 (2014). He, J. H., Ding, W. L., Li, R. N., Wang, R. Y. & Zhao, W. Forming condition of the continental shale gas of Shahejie Formation in the central-north Huanghua Depression and its resource prospect. Pet. Geol. Recovery Effic. 23 (1), 22-30 (2016). Zou, C. N. et al. Advances, challenges, and countermeasures in shale gas exploration of underexplored plays, sequences and new types in China. Oil Gas Geol. 45 (2), 309-326 (2024). Wu, Y. J., Jia, J. L., Qin, J. Y. & Wang, X. M. The intrusion characteristics of Cenozoic diabase in the middle and northern Fuxin basin and its influence on source rocks. Acta Geol. Sin. 96 (3),1026-1040 (2022). Xie, W. Q. et al. Formation and evolution of coal-and oil-bearing source rocks in the Lower Cretaceous Shahai Formation in the Fuxin Basin (NE China): Evidence from organic and inorganic geochemical analyses. J. Pet. Sci. Eng. 202 , 108544 (2021). Zhao, Q. et al. Potential of continental shale gas accumulation in medium-and small-sized fault basins in eastern China: A case study from the Fuxin Basin. Natur. Gas Ind. 38 (5), 26-33 (2018). Zhang, M. T. et al. Factors Controlling the Pore Development of Low-Mature Marine-Continental Transitional Shale: A Case Study of the Upper Permian Longtan Shale, Western Guizhou, South China. J. Mar. Sci. Eng. 11(10), 1862 (2023). Xiao, B. et al. Rare Earth Element Characteristics of Shales from Wufeng–Longmaxi Formations in Deep-Buried Areas of the Northern Sichuan Basin, Southern China: Implications for Provenance, Depositional Conditions, and Paleoclimate. ACS Omega 9(2), 2088-2103 (2024). Xiao, B. et al. Late Ordovician-Early Silurian extension of the northern margin of the Upper Yangtze Platform (South China) and its impact on organic matter accumulation. J. Pet. Sci. Eng. 220 , 111238 (2023). Jiao, Y. F. et al. Characteristics and Genesis of Pore-Fracture System in Alkaline Lake Shale, Junggar Basin, China. Appl. Sci. 14 (12), 5239 (2024). Kang, Z. Q. et al. Characterization of fracture and percolation processes in oil shale under conduction and convection heating modes based on micro-CT technology. J. Anal. Appl. Pyrolysis 181 , 106601(2024). Zhu, B. Y. et al. Complexity and Heterogeneity Evaluation of Pore Structures in the Deep Marine Shale Reservoirs of the Longmaxi Formation, China. J. Mar. Sci. Eng. 11 (8), 1613 (2023). Xu, J. et al. Micro-pore structure characteristics and quantitative characterization of Silurian Longmaxi shale in western Hubei and Hunan areas. Nat. Gas Geosci. 32 (4), 611-622 (2021). Xu, C. X. et al. Study on the Difference of Microscopic Adsorption Mechanism of Shale Gas in Mineral Pores. Spec. Oil Gas Reservoirs 27 (4), 79-84 (2020). Zhang, H. et al. Using Fractal Theory to Study the Influence of Movable Oil on the Pore Structure of Different Types of Shale: A Case Study of the Fengcheng Formation Shale in Well X of Mahu Sag, Junggar Basin, China. Fractal and Fractional 8 (4), 242 (2024). Tian, X. et al. Evolution of fractal characteristics in shales with increasing thermal maturity: Evidence from neutron scattering, N 2 physisorption, and FE-SEM imaging. Energy 298 , 131342 (2024). Zhao, C. X. et al. Characterization and fractal characteristics of nano-scale pore structure in shale gas reservoirs: a case study of the deep Longmaxi Formation, Zigong region, Southern Sichuan Basin, China. Frontiers in Earth Science 12 , 1410437 (2024). Wang, T. et al. Pore structure and fractal characteristics of transitional shales with different lithofacies from the eastern margin of the Ordos Basin. Energy Sci. Eng. 11 (11), 3979-4000 (2023). Chen, D. Y. et al. Characteristics of lacustrine shale reservoir and its effect on methane adsorption capacity in fuxin basin. Energy Fuels 32 (11), 11105-11117 (2018). Chen, G. et al. Sedimentary and organic matter characteristics of Lower Cretaceous Jiufotang Formation in western Liaoning Province. Geol. Bull. China 38 (2-3), 426-436 (2019). Zhu, Z. M., Yan, J. F., Shen, B. & Zhou, J. Y. Co-existing formation of multi-energy resources in the Fuxin Basin: Analysis from tectonic-thermal events. Adv. Earth Sci. 22 (5), 468-479 (2007). Wang, X. R., Lu, A. P. & Zhang, X. Y. The features of oil- and gas-bearing strata in the Fuxin Basin. Journal of Stratigraphy 31 (4), 385-390 (2007). Zhang, J. Z. et al. Pore structure and fractal characteristics of coal-bearing Cretaceous Nenjiang shales from Songliao Basin, Northeast China. Nat. Gas Geosci. 35 (1), 119-132 (2024). Han, M. L. et al. Influence of structural damage on evaluation of microscopic pore structure in marine continental transitional shale of the Southern North China Basin: a method based on the lowtemperature N 2 adsorption experiment. Petrol. Sci. 19 (1),100-115 (2022). Thommes, M. et al. Physisorption of gases, with special reference to the evaluation of surface area and pore size distribution (IUPAC Technical Report). Pure Appl. Chem. 87 (9-10), 1051-1069 (2022). Li, Z. et al. The Impacts of Matrix Compositions on Nanopore Structure and Fractal Characteristics of Lacustrine Shales from the Changling Fault Depression, Songliao Basin, China. Minerals 9 (2), 127 (2019). Yu, K. et al. Fractal Characteristics and Heterogeneity of the Nanopore Structure of Marine Shale in Southern North China. Minerals 9 (4), 242 (2019). Barrett, E. P., Joyner, L.G. & Halenda, P. P. The Determination of Pore Volume and Area Distributions in Porous Substances. I.Computations from Nitrogen Isotherms. J. Am. Chem. Soc. 73 , 373-380 (1951). Brunauer, S., Emmett, P. H. & Teller, E. Adsorption of Gases in Multimolecular Layers. J. Am. Chem. Soc. 60 , 309-319 (1938). Xie, W. D., Wang, M., Wang, H. & Duan, H. Y. Multi-scale fractal characteristics of pores in transitional shale gas reservoir. Nat. Gas Geosci. 33(3), 451-460 (2022). Li, X. M. et al. Micro-pore structure and fractal characteristics of deep shale from Wufeng Formation to Longmaxi Formation in Jingmen exploration area, Hubei Province. Nat. Gas Geosci. 33 (4), 629-641 (2022). Liu, K., Ostadhassan, M., Jang, H.W., Zakharova, N. V. & Shokouhimehr, M. Comparison of Fractal Dimensions from Nitrogen Adsorption Data in Shale via Different Models. RSC Adv. 11 , 2298-2306 (2021). Neimark, A. A New Approach to the Determination of the Surface Fractal Dimension of Porous Solids. Phys. A 191 , 258-262 (1992). Fan, C. J. et al. Scale Effect of Coal Porosity and Permeability Characteristics Based on CT 3D Reconstruction from a Microperspective. Energy Fuels 38 , 1813-1821 (2024). Xiao, B., Xiong, L., Zhao, Z. H. & Fu, X. Sedimentary tectonic pattern of Wufeng and Longmaxi Formations in the northern margin of Sichuan Basin, South China. Int. Geol. Rev. 64 , 2166-2185 (2022). Han, Y. H. et al. Study on the multifractal characterization and seepage of the shale matrix: A case study of the Longmaxi Formation in southwestern Sichuan Basin, China. Geoenergy Sci. Eng. 238 , 212924 (2024). Du, W. et al. Multi-Scale Pore Structure Characterization of Silurian Marine Shale and Its Coupling Relationship With Material Composition: A Case Study in the Northern Guizhou Area. Frontiers in Earth Science 10 , 930650 (2022). Loucks, R. G., Reed, R. M., Ruppel, S. C. & Hammes, U. Spectrum of pore types and net-works in mudrocks and a descriptive classification for matrix-related mudrock pores. AAPG Bulletin 96 (6), 1071-1098 (2012). Fu, X., Liu, X., Wu, Q. X., Xiao, B. & Fan, C. J. Influence of magma intrusion on coal geochemical characteristics: a case study of Tiefa Daxing coal mine. Sci. Rep. 14 (1),7396 (2024). Fu, H. J. et al. Pore Structure and Multi-Scale Fractal Characteristics of Adsorbed Pores in Marine Shale: A Case Study of the Lower Silurian Longmaxi Shale in the Sichuan Basin, China. J. Earth Sci. 33 (5), 1278-1290 (2022). Liu, J., Bai, X. & Elsworth, D. Evolution of pore systems in low-maturity oil shales during thermal upgrading-Quantified by dynamic SEM and machine learning. Pet. Sci. 21 (3), 1739-1750 (2024). Zhang, C. H., Zhu, Y. M., Liu, Y., Chen, J. K. & Li, Z. Y. Pore and Fractal Characteristics of Shale in Different Maturity． Fault-Block Oil & Gas Field 23 (05), 583-588 (2016). Chen, J. K., Zhu, Y. M., Cui, Z. B. & Zhang, C. H. Pore structure and fractal characteristics of Longmaxi shale in southern Sichuan Basin. Lithol. Reservoirs 30 (1), 55-62 (2018). Liang, Z. K. et al. Relationship between multifractal characteristics of pore size and lithofacies of shale of Shahezi Formation in Changling fault depression, Songliao Basin. Lithol. Reservoirs 32 (6), 22-35 (2020). Zheng, S. S. et al. Characteristics of microscopic pore structures and main controlling factors of Wufeng-Longmaxi Formation shale in southern Sichuan Basin. Lithol. Reservoirs 31 (3), 55-65 (2019). Zhang, J. Z. et al. Quantitative characterization of pore-fracture system of organic-rich marine-continental shale reservoirs: A case study of the Upper Permian Longtan Formation, Southern Sichuan Basin, China. Fuel 200 , 272-281 (2017). Cao, T. T. et al. Characteristics of Shale Pores, Fractal Dimension and Their Controlling Factors Determined by Nitrogen Adsorption and Mercury Injection Methods. Pet. Geol. Recovery Effic. 23 (2), 1-8 (2016). Luo, R. et al. Effect of Mineral Dissolution by Organic Acids on Pore Structure of Shale Reservoir. J. China Univ. Pet., Ed. Nat. Sci. 41 (2), 49-59 (2017). He, S. et al. Shale Reservoir Characteristics and Influencing Actors of Wufeng-Longmaxi Formation in Dingshan Area, Southeast Sichuan. Reservoir Evaluation and Development 9 (4), 61-67,78 (2019). Xie, W., Wang, M., Wang, H., Ma, R. Y. & Duan, H. Y. Diagenesis of shale and its control on pore structure, a case study from typical marine, transitional and continental shales. Front. Earth Sci. 15 (2), 378-394 (2021). Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.xlsx 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5166141","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":378415624,"identity":"e205275b-7fde-4e22-a6d8-d455c3026b01","order_by":0,"name":"Bin Xiao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIie3PIQvCQBTA8SeDrZxevRU/wxNhY7AP88bgmmA0CIbBDKJmv8U+wvRgltkNhrPYLaJFXLAp22yG+4V35f7cPQDD+ENoVYMA+rblbDVNwvbJkDssRl3KFsn7jDZr8NxzumtOfKdbCD0NO5kCOSE7Bz5fUG0SJL0YqZAWqk5xJHYCUR6y+o8pNtBkKxurV44kLoBi1JhgTs9qKvDGVM02yUBHqRJuAh4QtUiChA0xWknkFosF5ZI17uLz0nPvt3CW8v32+niGfT5f1icf2G/XDcMwjK9eWRtGxkSIjuYAAAAASUVORK5CYII=","orcid":"","institution":"Liaoning Technical University","correspondingAuthor":true,"prefix":"","firstName":"Bin","middleName":"","lastName":"Xiao","suffix":""},{"id":378415625,"identity":"ca3a3f87-e29a-4002-bd28-569675ec7230","order_by":1,"name":"Guoji Dong","email":"","orcid":"","institution":"Liaoning Technical University","correspondingAuthor":false,"prefix":"","firstName":"Guoji","middleName":"","lastName":"Dong","suffix":""},{"id":378415626,"identity":"732be14f-bb4e-47e7-b628-0c2384d849de","order_by":2,"name":"Zhongying Zhao","email":"","orcid":"","institution":"Research Institute of Petroleum Exploration and Development","correspondingAuthor":false,"prefix":"","firstName":"Zhongying","middleName":"","lastName":"Zhao","suffix":""},{"id":378415628,"identity":"3e6c8cc5-1a89-4072-bbf9-57d063369c1d","order_by":3,"name":"Zhenhua Yang","email":"","orcid":"","institution":"Liaoning Technical University","correspondingAuthor":false,"prefix":"","firstName":"Zhenhua","middleName":"","lastName":"Yang","suffix":""},{"id":378415630,"identity":"24d37957-7b3c-4126-a617-15b342677300","order_by":4,"name":"Chaojun Fan","email":"","orcid":"","institution":"Liaoning Technical University","correspondingAuthor":false,"prefix":"","firstName":"Chaojun","middleName":"","lastName":"Fan","suffix":""},{"id":378415633,"identity":"f83655ad-2112-4af6-a520-6554151858ea","order_by":5,"name":"Chunhao Jiang","email":"","orcid":"","institution":"Liaoning Technical University","correspondingAuthor":false,"prefix":"","firstName":"Chunhao","middleName":"","lastName":"Jiang","suffix":""},{"id":378415635,"identity":"910910e3-9c91-4c16-9e58-a4863a41b9e3","order_by":6,"name":"Sheng Li","email":"","orcid":"","institution":"Liaoning Geology Engineering Vocational College","correspondingAuthor":false,"prefix":"","firstName":"Sheng","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-09-27 15:23:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5166141/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5166141/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70573791,"identity":"a67c2950-80bf-40f4-969a-7ee6c09c34bc","added_by":"auto","created_at":"2024-12-04 14:03:01","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2347408,"visible":true,"origin":"","legend":"\u003cp\u003e(a)The geographical location of the western Liaoning fault depression basin group in Northeast China. (b)The geographical location of Fuxin Basin, modified after Xie et al.\u003csup\u003e9\u003c/sup\u003e. (c)Tectonic background and sampling drilling well distribution of Fuxin Basin, modified after Chen et al.\u003ca href=\"#_edn1\" title=\"\"\u003e\u003csup\u003e9\u003c/sup\u003e\u003c/a\u003e. (d)Drilling stratigraphic profile and sample distribution of DY-1 Well.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/4c03be0ca5022e7a99da13d7.jpg"},{"id":70573792,"identity":"5d44cb46-f0dc-4af1-aa67-3470b99bc3e8","added_by":"auto","created_at":"2024-12-04 14:03:01","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":449788,"visible":true,"origin":"","legend":"\u003cp\u003eMineralogical composition of sixteen shale samples in Shahai Formation from the DY-1 Well.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/c96e09e66a979b0b01afda72.jpg"},{"id":70572924,"identity":"50f035ed-3a17-4a9f-a551-52d1fe0ba189","added_by":"auto","created_at":"2024-12-04 13:55:01","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1257073,"visible":true,"origin":"","legend":"\u003cp\u003eLow-pressure N\u003csub\u003e2\u003c/sub\u003e adsorption/desorption isotherms of shale samples. (a) Sample 01; (b) Sample 02; (c) Sample 03; (d) Sample 04; (e) Sample 05; (f) Sample 06; (g) Sample 07; (h) Sample 08; (i) Sample 09; (j) Sample 10; (k) Sample 11; (l) Sample 12; (m) Sample 13; (n) Sample 14; (o) Sample 15; (p) Sample 16.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/9f4a2dc0069f7724dd1237a2.jpg"},{"id":70572916,"identity":"7cc2c0ee-55b0-4a3f-acfa-531a2bace9ce","added_by":"auto","created_at":"2024-12-04 13:55:01","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":339502,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage distribution of different pore sizes in Shahai Formation shale from the DY-1 Well.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/b5ba56e6a5374a0419da13d3.jpg"},{"id":70572920,"identity":"3fd32533-b959-49d8-bb91-c6cedd25b153","added_by":"auto","created_at":"2024-12-04 13:55:01","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1252604,"visible":true,"origin":"","legend":"\u003cp\u003ePlots of Ln V vs Ln (Ln Po/P) from N\u003csub\u003e2\u003c/sub\u003e adsorption isotherm data. (a) Sample 01; (b) Sample 02; (c) Sample 03; (d) Sample 04; (e) Sample 05; (f) Sample 06; (g) Sample 07; (h) Sample 08; (i) Sample 09; (j) Sample 10; (k) Sample 11; (l) Sample 12; (m) Sample 13; (n) Sample 14; (o) Sample 15; (p) Sample 16.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/0fe9e668ad6f0448657ef659.jpg"},{"id":70572926,"identity":"af2e3c89-3a5c-4b8a-b45e-e55ff3430672","added_by":"auto","created_at":"2024-12-04 13:55:01","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2253653,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between fractal dimension and total pore, micropore, mesoporous volume and specific surface area of Shahai Formation shale. (a)Fractal dimension vs Total pore volume; (b)Fractal dimension vs Micropores volume; (c)Fractal dimension vs Mesopores volume; (d)Fractal dimension vs Macropores volume; (e)Fractal dimension vs Volume percentage of micropores; (f)Fractal dimension vs Volume percentage of mesopores; (g)Fractal dimension vs Volume percentage of macropores; (h)Fractal dimension vs Specific surface area; (i)Fractal dimension vs Average pore diameter.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/0aa5b9638d02f74d30cb21de.jpg"},{"id":70573794,"identity":"bc8754f4-b938-4508-90ed-90a588e337b1","added_by":"auto","created_at":"2024-12-04 14:03:01","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1891935,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between fractal dimension and matrix components of Shahai Formation shale. (a)Fractal dimension D\u003csub\u003e1\u003c/sub\u003e vs D\u003csub\u003e2\u003c/sub\u003e; (b)Fractal dimension vs TOC; (c)Fractal dimension vs Ro; (d)Fractal dimension vs Clays; (e)Fractal dimension vs Brittle mineral; (f)Fractal dimension vs Quartz; (g)Fractal dimension vs Feldspar; (h)Fractal dimension vs Carbonate minerals.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/9a2eed12286b873a9ba788d9.jpg"},{"id":70572917,"identity":"9a783793-59f4-460f-8596-b2d81234354c","added_by":"auto","created_at":"2024-12-04 13:55:01","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2148036,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap showing the correlation between the volume of pores and mineral composition, as well as TOC content.\u003c/p\u003e","description":"","filename":"Figure8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/eb80d81bc75517a887a83d68.jpg"},{"id":70573793,"identity":"5278a9ca-2349-4e7c-a37b-df51aedddf8a","added_by":"auto","created_at":"2024-12-04 14:03:01","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":4161768,"visible":true,"origin":"","legend":"\u003cp\u003eCharacteristics of pore and fracture development in shale of DY-1 Well. OM-Organic matter. Macro photos of the rock core: (a)Horizontal bedding and progressive bedding are developed on sample Y15, with vertical cracks filled with calcite. FE-SEM images of shale samples: (b)The intergranular pores of pyrite crystals in sample Y10. (c)The intergranular pores between pyrite framboids and complexes of clay-OM in sample Y09. (d)The intergranular pores of quartz particles in sample Y06. (e)Intragranular dissolution pores and intergranular pores of dolomite particles in sample Y10. (f)Intragranular dissolution pores of dolomite particles in sample Y12. (g)Intragranular dissolution pores of calcite particles in sample Y03. (h)The irregular pores inside the organic matter in sample Y11. (i)The irregular pores inside the organic matter in sample Y04. (j)The shrinkage fractures inside organic matter in sample Y03. (k)Matrix fractures in sample Y03. (l)Organic matter shrinkage fractures in sample Y03.\u003c/p\u003e","description":"","filename":"Figure9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/695f8d52f404a626c7ccf1c5.jpg"},{"id":79058111,"identity":"d315d698-3176-46f1-bc9c-c2d09ba5fac5","added_by":"auto","created_at":"2025-03-24 00:46:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":17143851,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/49e7e8c7-4350-42c5-9b30-39afaec87059.pdf"},{"id":70573795,"identity":"6786f7f5-07dc-45cc-a15a-508f9900b13a","added_by":"auto","created_at":"2024-12-04 14:03:01","extension":"xlsx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":29697,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5166141/v1/3f8a3a936605b6f6bcb606e6.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Fractal characteristics and controlling factors of coal bearing shale pores in the continental fault depression basin of western Liaoning, Northeast China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn response to the changing global energy landscape and to ensure energy security, shale gas, an important unconventional natural gas resource, has garnered widespread attention worldwide following the North American shale gas revolution\u003csup\u003e1\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e2\u003c/sup\u003e. Over the past decade, China has carried out extensive appraisal and exploration trials for shale gas in various regions, and has achieved industrialized exploitation of marine shale gas in the Sichuan Basin. It has also made certain breakthroughs in the exploration and development of continental shale gas\u003csup\u003e3\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e4\u003c/sup\u003e. For instance, the Yanchang Formation of the Upper Triassic in LP177 well in Ordos Basin was effectively stimulated for shale gas production, achieving an initial test production rate of 2,350 m\u003csup\u003e3\u003c/sup\u003e per day\u003csup\u003e5\u003c/sup\u003e. The XG57 well in the Qikou depression of the Bohai Bay Basin obtained an industrial gas flow of 13.7 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e m\u003csup\u003e3\u003c/sup\u003e per day from shale gas testing in the third section of the Shahejie Formation of the Paleogene Eocene\u003csup\u003e6\u003c/sup\u003e. China possesses extensive sedimentary basins rich in terrestrial organic-rich shale. The exploitable resources of terrestrial shale gas in China constitute over 30% of the country's total shale gas reserves, and exploration and development efforts have confirmed the considerable resource potential of terrestrial shale gas in China\u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA large number of Mesozoic small and medium-sized fault basins have developed in Northeast China (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, b). Thanks to the vigorous volcanic activity during the Cretaceous period, the maturation and gas generation of shale organic matter in this area have been accelerated, providing the prerequisite for shale gas accumulation and enrichment. It is an important area for continental shale gas exploration in China\u003csup\u003e8\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e9\u003c/sup\u003e. The Fuxin Basin is a typical continental fault basin in Northeast China. The Shahai Formation in the Fuxin Basin has favorable geological conditions for the formation of shale gas, and this coal bearing shale is widely distributed in the basin\u003csup\u003e10\u003c/sup\u003e. At present, research on the microscopic pore structure and fractal characteristics of shale reservoirs in the Shahai Formation of the Fuxin Basin is relatively weak, which restricts the fine evaluation and analysis of coal bearing shale reservoirs and the effective assessment of resource reserves, and is not conducive to the exploration and development process of shale oil and gas in the basin.\u003c/p\u003e \u003cp\u003eAs a kind of unconventional reservoir, shale usually has the characteristics of low porosity and low permeability\u003csup\u003e11\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e12\u003c/sup\u003e. The pore structure and its complexity directly affect the occurrence state of shale gas and are important contents of shale reservoir evaluation\u003csup\u003e13\u003c/sup\u003e. A large number of nanoscale micro pores are developed in shale, and the fracture morphology is complex and interwoven, collectively forming a complex network of pores and fractures. There are certain differences in the occurrence state of shale gas in pores with different pore sizes. Shale gas in micropores and smaller mesopores mainly exists in an adsorbed state, while in macropores, the free gas volume fraction is high\u003csup\u003e14\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e15\u003c/sup\u003e. The volume fraction of adsorbed gas in shale can reach up to about 80%, which is controlled by the complexity of pores\u003csup\u003e16\u003c/sup\u003e. The parameters such as pore volume, specific surface area, and pore size distribution play an important role in characterizing the pore structure\u003csup\u003e17\u003c/sup\u003e. However, due to the influence of multiple factors such as the content and distribution of organic matter and inorganic minerals on the development of shale pores, it has brought difficulties to the quantitative evaluation of shale pore structure\u003csup\u003e18\u003c/sup\u003e. With the introduction of fractal theory, it has gradually become an important method for characterizing the complexity of pore structure in porous materials. In the investigation of shale pore structure, it was observed that organic-rich shale micropores exhibited well-developed heterogeneity and possessed characteristics typical of a porous medium. Consequently, fractal dimension can be employed to quantitatively characterize the complexity of these pores\u003csup\u003e19\u003c/sup\u003e. The fractal dimension is defined as an interval value of 2\u0026ndash;3, and the more significant the fractal, the larger the value\u003csup\u003e20\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e21\u003c/sup\u003e. The fractal dimension can quantitatively describe the self similarity of fractal systems and is a key indicator for quantitatively characterizing the heterogeneity and complexity of pore development, which is extremely important for shale reservoir evaluation\u003csup\u003e22\u003c/sup\u003e. At present, research on pore fractals in coal bearing shale reservoirs and their impact on shale gas adsorption control is still relatively weak. Based on this, this study systematically explores the fractal dimension of coal bearing shale in the Shahai Formation of the Fuxin continental fault depression basin and its relationship with mineral composition, organic matter content, maturity, and pore structure, based on the results of low-temperature nitrogen adsorption experiments. This has certain significance for revealing the pore development mechanism of coal bearing shale, micro reservoir evaluation, and favorable reservoir selection.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Geological setting","content":"\u003cp\u003eThe tectonic location of the Fuxin Basin is in the northern part of the North China Plate and the northeastern part of the Yanshan orogenic belt\u003csup\u003e24\u003c/sup\u003e. The Fuxin Basin is a terrestrial fault basin that extends in the NNE-NE direction, with an area of approximately 1500km\u003csup\u003e2\u003c/sup\u003e(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec)\u003csup\u003e23\u003c/sup\u003e. The accumulated sediments were controlled by the Lvshan fault in the eastern basin and the Songling fault in the western basin (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec)\u003csup\u003e23\u003c/sup\u003e. Sedimentary strata on the plane were controlled by faults, forming a structural pattern between depressions and uplifts. From north to south, the basin can be divided into the Xinqiu sag, Fuxin structural belt, Haizhou sag, Dongliang structural belt, Yimatu sag, Qinghemen-Aiyou structural belt, Minjiatun sag, and other structural belts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec)\u003csup\u003e23\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe tectonic evolution of the Fuxin Basin has roughly gone through three stages of development: the initial extensional stage (sedimentary period of the Yixian Formation of the Lower Cretaceous), the development stage of fault depression (sedimentary period of the Jiufotang Formation, Shahai Formation, and Fuxin Formation of the Lower Cretaceous), and the extrusion reversal stage (sedimentary period of the Sunjiawan Formation of the Lower Cretaceous)\u003csup\u003e25\u003c/sup\u003e. From bottom to top, the Fuxin Basin has developed the Lower Cretaceous Yixian Formation (K\u003csub\u003e1\u003c/sub\u003ey), Jiufotang Formation (K\u003csub\u003e1\u003c/sub\u003ejf), Shahai Formation (K\u003csub\u003e1\u003c/sub\u003esh), Fuxin Formation (K\u003csub\u003e1\u003c/sub\u003ef), and Sunjiawan Formation (K\u003csub\u003e1\u003c/sub\u003es)\u003csup\u003e26\u003c/sup\u003e. Since the early stage of the formation of the Fuxin Basin during the Late Jurassic Yanshanian period, there has been strong volcanic and magmatic activity, which led to the formation of the Yixian Formation during the initial extensional period; During the development period of the fault depression, the Jiufotang Formation was first deposited. During the Yanshan tectonic activity, the strata of this formation were folded and deformed, and the subsidence center shifted eastward, depositing the Shahai Formation and Fuxin Formation; During the extrusion reversal period, the Sunjiawan Formation was deposited\u003csup\u003e25,26\u003c/sup\u003e. The Shahai Formation in the Fuxin Basin is rich in organic coal bearing shale reservoirs, and multiple drilling wells have discovered oil and gas indications, indicating good prospects for shale gas exploration and development. In addition, according to the drilling results of the DY-1 well in the Dongliang tectonic belt of the Fuxin Basin, good gas logging values were directly displayed in the third and fourth sections of the Shahai Formation. On site desorption work confirmed the presence of good desorption gas, and multiple sections of good light oil were shown on the extracted core samples. This directly confirms that the local area has favorable geological conditions for the formation of shale oil and gas.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSample collection and experimental methods\u003c/h2\u003e \u003cp\u003eA total of 16 shale samples were collected from well DY1, which is located in the southern flank of the Dongliang anticline in the north\u0026ndash;central part of the Fuxin Basin (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). These 16 drilling core samples were mainly collected from the third and fourth sections of the Shahai Formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Among them, there are 5 shale samples from the third section of the Shahai Formation (K\u003csub\u003e1\u003c/sub\u003eSh\u003csub\u003e3\u003c/sub\u003e, sample no. Y01-Y05) and 11 shale samples from the fourth section of the Shahai Formation (K\u003csub\u003e1\u003c/sub\u003eSh\u003csub\u003e4\u003c/sub\u003e, sample no. Y06-Y16).\u003c/p\u003e \u003cp\u003eThe CS580A carbon sulfur analyzer produced by Eltra, Germany was used to test the total organic carbon (TOC) content of the samples. Before testing, the sample is subjected to low-temperature drying treatment. The dried sample is placed in an agate mortar and ground to 80 mesh or more, and 100mg of powder sample is weighed. The sample was soaked for 24 h to remove carbonate and other inorganic carbon. Rinse the soaked sample with distilled water until the entire sample is neutral. Bake neutral samples at low temperature until dry, and then test them on the machine. According to repeated analysis of standard samples,the accuracy of the TOC content analysis is better than \u0026plusmn;\u0026thinsp;0.5%. The Ro was measured with a Leica MPV\u0026ndash;SP equipped with 50 magnification oil immersion lens and 10 magnification eyepiece. The polished core sample was observed microscopically and random reflectance values were measured on the primary vitrinite using two standards (sapphire, 0.6% and gadolinium\u0026ndash;gallium\u0026ndash;garnet, 1.7%). At least 20 points were counted\u003csup\u003e9\u003c/sup\u003e. The whole rock mineral analysis was carried out using a Japanese Rigaku D/Max 2500 PC powder X-ray diffractometer (XRD). Before experimental testing, the shale sample needs to be crushed into a 200 mesh powder, and 500 mg of the sample should be weighed and filled into a thin sheet with grooves, keeping the surface of the sample flat and consistent with the surface of the sheet. The test was conducted at room temperature, with instrument parameters including Cu target, Kα - ray, X-ray tube voltage and current of 40 kV and 150 mA, scanning speed of 4\u0026deg;/min, step size of 0.02\u0026deg;, starting angle of 2\u0026deg;, and ending angle of 70\u0026deg;. The equipment used for low-temperature nitrogen adsorption testing is the ASAP 2020 fully automatic surface area and pore size distribution analyzer developed by Micromeritics Instrument in the United States\u003csup\u003e27\u003c/sup\u003e. Before testing, the shale sample is crushed into 40\u0026ndash;80 mesh and degassed under vacuum conditions at approximately 110 ℃ for about 5 hours to remove adsorbed water and capillary bound water. Then the powder sample was placed into the analyzer for low-temperature nitrogen adsorption measurement. The P/Po (relative pressure) range for N\u003csub\u003e2\u003c/sub\u003e physisorption was from 0.01 to 0.99, where P is the absolute gas vapor pressure, and Po is the saturation pressure. By increasing the relative pressure from 0.01 to 0.99 to reach the saturated vapor pressure of nitrogen and gradually decreasing the pressure, the adsorption capacity of N\u003csub\u003e2\u003c/sub\u003e at different relative pressures P/P\u003csub\u003e0\u003c/sub\u003e was measured\u003csup\u003e20\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eMaturation, TOC, and mineral composition.\u003c/strong\u003e Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the TOC and Ro values of the studied representative 16 shale samples from the Shahai Formation. The TOC content of shale samples ranges from 1.53\u0026ndash;9.05%, with an average value of 3.41%, indicating an overall high organic matter content. The Ro range of shale samples is 0.48%~1.88%, with an average value of 0.89%. The Ro range of the shales in the third section of the Shahai Formation is 1.01%-1.88%, with an average of 1.48%, indicating that the shales are medium-high mature. The Ro range of shale in the fourth section of the Shahai Formation is 0.48%~0.85%, with an average of 0.62%, indicating that the shales are medium-low mature. From the changing trend of Ro, it can be found that the shale in this study is increasing in maturity with the increasing of burial depth.\u003c/p\u003e\n\u003cp\u003eThe mineral compositions of 16 shale samples are listed in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, which reveals that shales in this study are mainly composed of clays, quartz, feldspa, carbonates (calcite and dolomite) and pyrite. The content of clays in shale samples ranges from 11.92\u0026ndash;55.28%, with an average of 40.91%. The content of quartz ranged from 16.16\u0026ndash;36.07%, with an average of 27.09%. In this study, the feldspar mineral types of shale samples are mainly plagioclase, containing a small amount of k-feldspar. The content of carbonate minerals varies greatly, some shales do not contain carbonate minerals (Y05), while some shales contain 59.94% carbonate minerals (Y02). The pyrite, siderite and halite are only developed in a few shale samples.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. Organic petrographic characteristics and mineralogical composition of shale samples from Shahai Formation.\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Taba\" border=\"1\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTOC(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRo(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eClays(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eQuartz(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFeldspar(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCalcite(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eDolomite(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePyrite(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSiderite(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eHalite(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e32.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e29.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e44.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e25.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e32.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e41.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e55.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e31.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.07\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e45.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e36.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e47.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e25.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e44.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e44.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e25.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e42.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17.07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e44.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e41.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e25.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.54\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e42.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e28.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e49.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e26.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.89\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e42.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e20.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e42.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e26.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14.09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"11\"\u003eNote: TOC\u0026thinsp;=\u0026thinsp;total organic carbon; Ro\u0026thinsp;=\u0026thinsp;equivalent vitrinite reflectance.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e \u003csub\u003e \u003cstrong\u003e2\u003c/strong\u003e \u003c/sub\u003e \u003cstrong\u003ephysisorption and pore structure characteristics.\u003c/strong\u003e Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows the N\u003csub\u003e2\u003c/sub\u003e adsorption and desorption curves for the sixteen shale samples. The N\u003csub\u003e2\u003c/sub\u003e adsorption isotherm of all samples showed reversed S-shaped and have distinct hysteresis loops, which are generally due to capillary condensation, pore blocking, or the ink-bottle effect\u003ca id=\"#FNLinkFn28\" class=\"FNLink\" href=\"#Fn28\"\u003e\u003c/a\u003e. Combined with the IUPAC classification\u003ca id=\"#FNLinkFn29\" class=\"FNLink\" href=\"#Fn29\"\u003e\u003c/a\u003e, the hysteresis loops of shale samples adsorption-desorption isotherms is clearly exhibiting three types (H3 for Y-14 and Y-16; H4 for Y01, Y03, Y05, Y06, Y07, Y08, Y11, Y13,and Y15; H3-H4 for for Y02, Y04, Y09, Y10, and Y12). The first type is the H3 type adsorption isotherm hysteresis loop, represented by the Y16 sample. This type of adsorption isotherm steadily increases with the increase of relative pressure (P/P0), and suddenly increases when the relative pressure approaches 1. The hysteresis loop is small, and the adsorption curve and desorption curve almost completely overlap (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). This type of hysteresis loop is generated by the non-rigid plate-like aggregates of irregularly sized particles (such as certain clays) or by a pore network consisting of macroscopic pores filled with partially filled pore fluids\u003csup\u003e29\u003c/sup\u003e. Shales that develop such pores typically have a high content of clay minerals, as the pores formed by clay minerals are usually narrow slit shaped\u003csup\u003e27\u003c/sup\u003e. The second type is the H4 type adsorption isotherm hysteresis loop, represented by the Y03 sample. This type of adsorption isotherm steadily increases with the increase of relative pressure (P/P0). The desorption isotherm slowly decreases in the initial stage of relative pressure reduction, and suddenly decreases when P/P0 reaches 0.5(Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). This is due to the large amount of liquid nitrogen in the ink bottle hole being released and vaporizing at once\u003csup\u003e29\u003c/sup\u003e. This type of adsorption loop indicates that shale is mainly characterized by ink bottle shaped pores with fine necks and wide bodies\u003ca id=\"#FNLinkFn30\" class=\"FNLink\" href=\"#Fn30\"\u003e\u003c/a\u003e. The third type is the hysteresis loop of adsorption isotherms between H3 and H4, represented by the Y12 sample. This type of adsorption isotherm exhibits a relatively flat beginning segment, where the adsorption and desorption curves do not overlap, followed by a steep end with an indistinct inflection point in the desorption curve (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The hysteresis loop of this type of adsorption isotherm indicates that shale is mainly composed of parallel plate-like pores with uniformly open edges, and there are a small number of ink bottle shaped pores\u003ca id=\"#FNLinkFn31\" class=\"FNLink\" href=\"#Fn31\"\u003e\u003c/a\u003e. All the N2 adsorption isotherms indicate that micropore filling mainly occurs at low P/P0 (\u0026lt;\u0026thinsp;0.5), and the N2 adsorption volume gradually increases to reach the highest values at high P/P0 (\u0026asymp;\u0026thinsp;1.0). When the P/P0 approaches 1, the slope of the H3 type N2 adsorption isotherm is significantly higher than that of the H4 type (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), suggesting that more macropores (\u0026gt;\u0026thinsp;100 nm in diameter) or microfractures are present in H3 shale than in H4 shale samples.\u003c/p\u003e\n\u003cp\u003eBased on low-temperature N\u003csub\u003e2\u003c/sub\u003e adsorption experiments, the pore structure parameters of shale reservoirs (including total pore volume, average pore diameter, and specific surface area) can be quantitatively analyzed, as shown in Table\u0026nbsp;2. Based on the Barret-Joyner-Halenda (BJH) model\u003ca id=\"#FNLinkFn32\" class=\"FNLink\" href=\"#Fn32\"\u003e\u003c/a\u003e and Brunauer-Emmett-Teller (BET) model\u003ca id=\"#FNLinkFn33\" class=\"FNLink\" href=\"#Fn33\"\u003e\u003c/a\u003e, the total pore volume and total specific surface area were obtained to be 0.0107\u0026thinsp;~\u0026thinsp;0.0240 cm\u003csup\u003e3\u003c/sup\u003e/g (average 0.0176 cm\u003csup\u003e3\u003c/sup\u003e/g) and 4.0959\u0026thinsp;~\u0026thinsp;15.2736 m\u003csup\u003e2\u003c/sup\u003e/g (average 8.2351 m\u003csup\u003e2\u003c/sup\u003e/g), respectively. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e shows that the volume proportions of micropores, mesopores, and macropores are 0.11%~5.19% (average 1.77%), 70.44%~81.48% (average 76.49%), and 13.33%~28.25% (average 21.74%), respectively. The pore size of coal bearing shale is generally higher than that of marine shale, with mesopores and macropores as the main pore scale types\u003ca id=\"#FNLinkFn34\" class=\"FNLink\" href=\"#Fn34\"\u003e\u003c/a\u003e\u003csup\u003e,\u003c/sup\u003e\u003ca id=\"#FNLinkFn35\" class=\"FNLink\" href=\"#Fn35\"\u003e\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003cstrong\u003eTable\u0026nbsp;2.\u003c/strong\u003e Measurement of the physical parameters of shale samples by low-temperature nitrogen adsorption.\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tabb\" border=\"1\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSample\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTotal pore volume (cm\u003csup\u003e3\u003c/sup\u003e/g)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAverage pore diameter (nm)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSpecific surface area (m\u003csup\u003e2\u003c/sup\u003e/g)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eD2\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0165\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.6458\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.7939\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0202\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.6418\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.7524\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0188\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.6073\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.8117\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0221\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.4658\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.7155\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0211\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.5687\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.7240\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0189\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.4529\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.7055\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY07\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0107\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.5869\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.7196\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0165\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.5000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.7539\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY09\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0139\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.4550\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.6402\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0154\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.4885\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.6045\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0141\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.5366\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.7157\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0117\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.5345\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.6832\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0196\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.4915\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.6808\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0172\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.4671\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.5973\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0217\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.4361\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.6638\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eY16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0240\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.5110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.6395\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003eNote: D1 and D2\u0026thinsp;=\u0026thinsp;Surface fractal dimension from N\u003csub\u003e2\u003c/sub\u003e physisorption.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eFractal dimension features.\u003c/strong\u003e The quantitative evaluation of fractal geometry is described using the fractal dimension D. Currently, based on nitrogen adsorption/desorption data, the FHH (Frenkel-Halsey-Hill) method is widely used for fractal characterization of porous media\u003ca id=\"#FNLinkFn36\" class=\"FNLink\" href=\"#Fn36\"\u003e\u003c/a\u003e\u003csup\u003e,\u003c/sup\u003e\u003ca id=\"#FNLinkFn37\" class=\"FNLink\" href=\"#Fn37\"\u003e\u003c/a\u003e. This FHH method is defined as:\u003c/p\u003e\n\u003cp\u003eLn(V) = (D-3) \u0026times; Ln(Ln(P\u003csub\u003e0\u003c/sub\u003e/P)\u0026thinsp;+\u0026thinsp;Constant (1)\u003c/p\u003e\n\u003cp\u003eWhere V is the amount of gas that has been adsorbing; P represents equilibrium pressure; P\u003csub\u003e0\u003c/sub\u003e is the saturated vapor pressure; D is the surface fractal dimension. Based on N\u003csub\u003e2\u003c/sub\u003e adsorption data and FHH model, we can plot two different linear segments at P/P0. With P/P0\u0026thinsp;=\u0026thinsp;0.5 as the boundary, the pore fractal dimension is D1 when P/P0\u0026thinsp;\u0026lt;\u0026thinsp;0.5, and D2 when P/P0\u0026thinsp;\u0026ge;\u0026thinsp;0.5.\u003c/p\u003e\n\u003cp\u003eThe fractal dimension values D1 and D2 can be quantitatively obtained by linearly fitting the slope of a line between Ln(V) and Ln(Ln(P0/P)) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). The linear fitting coefficient is above 0.94, indicating a good fitting effect and significant fractal characteristics. The calculation results show that the coal bearing shale of the Shahai Formation exhibits significant pore fractal characteristics, with strong heterogeneity and roughness. The calculated fractal dimensions D1 and D2 are between 2.4361 and 2.6458 (with an average of 2.5243) and 2.5973 to 2.8117 (with an average of 2.7001), respectively. D2 is generally higher than D1, indicating that compared to the surface structure, the internal characteristics of pores are more complex.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe size of fractal dimension is influenced by multiple factors. Generally speaking, any factors that affect the development of micro pores will have an impact on the fractal dimension, which can be divided into two aspects: organic pore development factors and inorganic pore development factors. The pore structure directly affects the gas occurrence state and total gas content. The relative size of pore volume and specific surface area can reflect the gas adsorption capacity of pores, while the fractal dimension of shale essentially reflects the complexity of pores\u003csup\u003e38\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e39\u003c/sup\u003e. Therefore, there is a natural intrinsic relationship between specific surface area, pore volume, and fractal dimension.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe effect of pore structure on fractal characteristics.\u003c/b\u003e In order to explore the influence of shale pore structure on fractal characteristics, this study systematically analyzed the correlation between fractal dimension and pore volume, specific surface area and average pore diameter (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). There is no significant correlation between the total pore volume of shale and fractal dimensions D1 and D2, with correlation coefficients of 0.0228 and 0.0005, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). The micropore volume shows a good positive correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.3309 and 0.4844, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). There is no significant correlation between mesoporous volume and fractal dimensions D1 and D2, with correlation coefficients of 0.0127 and 0.0170, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). The macro pore volume shows a good negative correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.1747 and 0.2865, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). The percentage of micropore volume shows a good positive correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.3918 and 0.5465, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee). There is no significant correlation between mesoporous volume percentage and fractal dimension D1, but a weak positive correlation with D2, with correlation coefficients of 0.0230 and 0.2879, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ef). The macro pore volume percentage shows a weak negative correlation with fractal dimension D1, and a strong negative correlation with D2, with correlation coefficients of 0.1218 and 0.4581, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eg). The specific surface area shows a good positive correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.3219 and 0.6129, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eh). The average pore size of shale ranges from 5.52nm to 14.06nm, with an average of 9.66nm. The average pore size shows a strong negative correlation with fractal dimensions D1 and D2, with correlation coefficients of 0.4065 and 0.8851, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ei).\u003c/p\u003e \u003cp\u003eThe correlation coefficients between the volume percentages of micropores, mesopores, and macropores and fractal dimension show good positive correlation, weak correlation, and negative correlation, respectively, indicating that micropores in shale contribute the most to fractal dimension and are the main cause of heterogeneity and complexity in pore structure. As the volume of micropores increases, the pore structure of shale becomes more complex, and the specific surface area also increases, enhancing its ability to adsorb gases. This is mainly related to the pore diameter of shale. Micropore diameters below 2nm contribute less than 10% to the pore volume, but micropores can provide over 80% of the specific surface area\u003csup\u003e20\u003c/sup\u003e. Therefore, the presence of micropores has a significant impact on the amount of adsorbed gas. On the one hand, micropores have a larger specific surface area and provide more gas active adsorption sites, which can accommodate a greater amount of adsorbed gas; On the other hand, shale, as a porous medium, the smaller the pore size, the stronger the adsorption potential (Ea) of hydrocarbon gases on the inner walls of the pores, that is, the tighter the gas adsorption, and the stronger the adsorption capacity of the pores\u003csup\u003e40\u003c/sup\u003e. Therefore, according to the size of the pore size, the strength of gas adsorption capacity in shale pores is micropores\u0026thinsp;\u0026gt;\u0026thinsp;mesopores\u0026thinsp;\u0026gt;\u0026thinsp;macropores\u003csup\u003e41\u003c/sup\u003e. At the same time, there is a good correlation between the fractal dimension of shale pores and the specific surface area (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eh), indicating that the pore adsorption capacity can be characterized by the size of the fractal dimension. The larger the fractal dimension of shale, the more developed the micropores in shale, which can provide more gas adsorption sites and greater adsorption potential. The pores have stronger adsorption capacity for shale gas, resulting in a higher proportion of adsorbed gas content in shale. In addition, there is a high negative correlation between the fractal dimension values D1 and D2 of pores and the average pore diameter (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ei), that is, as the average pore diameter decreases, the fractal dimension values increase. Due to the irregularity of pores, the pore volume cannot be directly characterized by the average pore size, but pores with smaller average pore sizes tend to have a decreasing pore volume. The smaller the pore diameter, the larger the pore specific surface area, resulting in an increase in the fractal dimension of the pores\u003csup\u003e11\u003c/sup\u003e. Therefore, it can be inferred that small pore size is an important reason for the non-uniformity of shale pore structure.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eThe effect of organic matter content and maturity on fractal characteristics.\u003c/b\u003e There is a strong linear correlation between the fractal dimensions D1 and D2 of the coal bearing shale in the Shahai Formation of the research area, with a correlation coefficient of 0.5026 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). This indicates that there is a good correspondence between the heterogeneity and complexity of the pore surface and internal space of coal bearing shale, that is, the more complex the pore surface of shale, the more complex the internal structure of the pores. From Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb, it can be seen that there is no significant correlation between D1 and TOC content in the coal bearing shale of the Shahai Formation, while D2 shows a weak positive correlation with TOC content. This indicates that organic matter increases the internal spatial complexity of pore structures more than the surface roughness of pores. This is because organic matter usually develops micropores, which enhances the heterogeneity of the internal space of the pores\u003csup\u003e42\u003c/sup\u003e. The more complex the pore structure of shale, the higher the fractal dimension of the pores, and the enhanced the adsorption capacity of shale, which is more conducive to the storage of natural gas\u003csup\u003e43\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e44\u003c/sup\u003e. The good correlation between TOC content and micropore volume and specific surface area (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) indicates that organic matter has a high contribution to micropores.\u003c/p\u003e \u003cp\u003eAt different stages of organic matter thermal evolution, there may be differences in the degree of organic pore development, pore size, and pore morphology\u003csup\u003e45\u003c/sup\u003e. Therefore, the degree of thermal evolution of organic matter has a certain controlling effect on the complexity of pores. As mentioned earlier, the organic matter in the shale of the Shahai Formation in the study area is in the low to high maturity stage. The correlation coefficients between the thermal evolution degree of shale samples in the study area and the pore fractal dimensions D1 and D2 are 0.5318 and 0.5914, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec). On the one hand, in the shale maturity to the early stage of high maturity, as the Ro value increases, the number of micropores in the organic matter significantly increases, and the organic matter undergoes aromatization, thereby increasing the roughness of the pore walls, which increases the specific surface area of the pores\u003csup\u003e46\u003c/sup\u003e. The good positive correlation between Ro and micropore volume and specific surface area shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e also confirms the above inference. On the other hand, as the burial depth increases, the enhancement of organic matter aromatization also leads to a decrease in pore support capacity. Under the pressure of the overlying strata, the pores undergo irregular deformation, increasing the complexity of the pores and resulting in an increase in the fractal dimension of shale\u003csup\u003e31\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eThe effect of mineral components on fractal characteristics.\u003c/b\u003e The main inorganic minerals in the coal bearing shale of the Shahai Formation are clay minerals, quartz, feldspar, and carbonate minerals. By analyzing the correlation between mineral content and fractal dimension, the results showed a negative correlation between clay mineral content and shale fractal dimensions D1 and D2, with correlation coefficients of 0.3509 and 0.2659, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed). This may be due to the increase in clay mineral content in shale of the Shahai Formation, which leads to a decrease in the volume of micropores and mesopores in the shale (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). There is a good positive correlation between brittle minerals and shale fractal dimensions D1 and D2, with correlation coefficients of 0.3509 and 0.2659, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ee); The content of feldspar minerals is negatively correlated with fractal dimensions D1 and D2, with correlation coefficients of 0.3870 and 0.1837, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eg); The content of carbonate minerals is positively correlated with fractal dimensions D1 and D2, with correlation coefficients of 0.3287 and 0.1289, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eh). The brittle minerals here mainly include quartz, feldspar, carbonate minerals, and a small amount of pyrite. There is a good positive correlation between the content of brittle minerals and fractal dimension. This is significantly different from marine shale\u003csup\u003e47\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e48\u003c/sup\u003e. The reason may be that the brittle minerals in marine shale are mainly quartz, feldspar, and pyrite, with only a small amount of carbonate minerals. These brittle minerals usually have regular crystal structures, with pore scales mostly consisting of mesopores and macropores, which are relatively homogeneous and reduce the fractal characteristics of pore structures\u003csup\u003e49\u003c/sup\u003e. However, carbonate minerals are more developed in the coal bearing shale of the Shahai Formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), and there is a good positive correlation between carbonate mineral content and micropore volume (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), which mainly contributes to increasing the complexity of pore structure.\u003c/p\u003e \u003cp\u003eAs a direct carrier for the development of inorganic pores, the type and content of diagenetic minerals affect the development and distribution of pores, and there are significant differences in the types of pores developed in different types of minerals (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Vertical fractures can be observed from some drilling cores, with calcite filling inside the fractures (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea). After scanning electron microscopy observation of coal bearing shale samples from the Shahai Formation, it was found that there were relatively few nano pores in the organic matter (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Nano scale pores are mainly composed of intergranular pores between mineral particles such as pyrite and quartz (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb, c, d), and intragranular pores within carbonate mineral particles (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ee, f, g). In addition, nanoscale and micrometer scale organic matter pores can be observed within the organic matter (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eh, i), as well as organic matter shrinkage cracks and matrix cracks developed at the edges of the organic matter (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ej, k, l).\u003c/p\u003e \u003cp\u003eClay minerals, as one of the important inorganic minerals, are important carriers of shale pores. The content of clay minerals is negatively correlated with the fractal dimensions D1 and D2 of shale (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed). Combined with the negative correlation between clay mineral content and shale pore volume and specific surface area (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), it indicates that the development of clay minerals has an inhibitory effect on the increase of micropores. The reason may be that shale has a high content of clay minerals, with small clay mineral particles and weak compaction resistance. During long-term compaction and diagenesis, clay mineral particles tend to be oriented, reducing pore space and simplifying pore morphology. The compaction effect leads to a decrease in the number of micropores, with mesopores and macropores developing mainly. The development of clay minerals leads to a large number of microcracks in shale, with wide fracture widths (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ec, k), which also results in a negative correlation between the volume fraction of clay minerals and the fractal dimension of shale.\u003c/p\u003e \u003cp\u003eQuartz has strong resistance to compaction and dissolution, and the pores developed within quartz are limited\u003csup\u003e50\u003c/sup\u003e, with smaller pore sizes (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ed). Regarding the influence of quartz on the development of shale micropores, different scholars hold different views in the actual research process. Some studies suggest a negative correlation between quartz content and shale pore complexity\u003csup\u003e51\u003c/sup\u003e. However, the results of this study showed a weak positive correlation between quartz content and shale fractal dimension D2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ef), which may be due to the biogenesis of siliceous minerals in the coal bearing shale of the Shahai Formation in the study area. In the early Cretaceous, the Fuxin Basin was in an extensional environment, with deepening lake water and widespread development of diatomaceous plankton, which converted soluble silicon in the water into amorphous silicon to form bones\u003csup\u003e9\u003c/sup\u003e. These organisms have complex siliceous shells. After the death and deposition of the organisms, their soft tissues are transformed into organic matter and distributed in the biological cavities. The residual biological siliceous skeleton increases the brittleness of shale, while the irregular intergranular pores formed by the accumulation of siliceous debris in the biological cavities also increase the complexity of the pores. Based on the correlation analysis between TOC content and quartz content, it can be concluded that there is a good positive correlation between the two, indicating the presence of a certain amount of biogenic quartz in the shale of the Shahai Formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The irregular accumulation of siliceous biological skeletons and siliceous debris leads to the complexity of pore structure.\u003c/p\u003e \u003cp\u003eAs an aluminosilicate mineral, feldspar is easily dissolved and eroded by fluids under burial conditions\u003csup\u003e52\u003c/sup\u003e. Therefore, under the dissolution of formation fluids, feldspar is prone to form mesopores and macropores with larger pore sizes. In addition, feldspar has strong brittleness, which can lead to the development of cleavage cracks under geological conditions, thereby increasing the equivalent pore size of pores, resulting in a negative correlation between feldspar content and pore fractal dimensions D1 and D2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eg).\u003c/p\u003e \u003cp\u003eThe content of carbonate minerals is positively correlated with the fractal dimension of shale pores (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eh). The presence of carbonate minerals in shale has a \"duality\" in the development of pores: during diagenesis, some precipitated carbonate minerals fill the pores in the form of cement, causing pore blockage and reduction in pore size. In this case, micropores are usually retained, the proportion of mesopores and macropores is reduced, and the complexity of pores is increased\u003csup\u003e53\u003c/sup\u003e. During the burial process, carbonate minerals, as easily soluble components, form dissolution pores under the dissolution of formation fluids and organic acids, usually dominated by mesopores and macropores, which reduces the proportion of micropore development\u003csup\u003e53\u003c/sup\u003e. Carbonate mineral dissolution is usually stronger than cementation in ancient marine shale\u003csup\u003e54\u003c/sup\u003e. However, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, there is a significant positive correlation between carbonate minerals and micropores in the shale samples of the study area. Based on this, it is speculated that the mineral cementation of carbonate rocks in shallow buried Mesozoic continental shale is stronger than dissolution. Carbonate minerals in the form of cement promote the development of micropores. Therefore, there is a weak positive correlation between carbonate mineral content and shale fractal dimension.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e(1) The shale TOC content of the Shahai Formation in the Fuxin Basin varies greatly (with an average of 3.41%) and is rich in clay minerals (with an average of 40.91%). The nitrogen adsorption shows that the shale pore structure contains ink bottle shaped pores with fine necks and wide tubes, parallel plate-like pores with openings on all sides, and possibly narrow slit shaped pores formed by clay minerals.\u003c/p\u003e \u003cp\u003e(2) The shale pores of the Shahai Formation have obvious dual fractal characteristics. The average values of fractal dimensions D1 and D2 are 2.5243 and 2.7001, respectively. D2 is generally larger than D1, and the fractal dimension values are more concentrated, reflecting that the internal structure of pores is more complex than the surface structure.\u003c/p\u003e \u003cp\u003e(3) The micropores in the Shahai Formation shale contribute the most to the fractal dimension, which is the main reason for the heterogeneity and complexity of the pore structure. The smaller the pore size, the larger the pore specific surface area and the more complex the pore structure, resulting in an increase in the fractal dimension of the pore. This can provide more gas adsorption sites and greater adsorption potential, which is beneficial for shale gas enrichment.\u003c/p\u003e \u003cp\u003e(4) The increase in internal spatial complexity of pore structure by organic matter in Shahai Formation shale is stronger than the increase in surface roughness of pores. As the Ro value increases, the number of micropores in organic matter significantly increases with the degree of thermal evolution of organic matter.\u003c/p\u003e \u003cp\u003e(5) The carbonate minerals and clay minerals in the shale of the Shahai Formation have a significant impact on the fractal dimension of pores. On the one hand, carbonate minerals in the form of cement promote the development of micropores, reduce the proportion of mesopores and macropores, and increase the complexity of pores. On the other hand, the anti compaction ability of clay mineral particles is weak. During the compaction and diagenesis process, mineral particles tend to be orientation arranged, reducing pore space and simplifying pore morphology, thus reducing the complexity of pores structure.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eB.X. and G.J.D. wrote the main mauscript text. Z.Y.Z. designed the research. Z.H.Y. and C.J.F. collected and analyzed samples. C.H.J. discussed the results. S.L. supervised the fndings of this work. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis work was supported by the Project of the Natural Science Foundation of Liaoning Province (Grant No. 2022-BS-328), and the National Natural Science Foundation of China (Grant No. 52174117 and 42274129).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated or analysed during this study are included in this published article [and its supplementary information files].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNie, H. K. et al. Deep shale gas in the Ordovician-Silurian Wufeng\u0026ndash;Longmaxi formations of the Sichuan Basin, SW China: Insights from reservoir characteristics, preservation conditions and development strategies. \u003cem\u003eJ. Asian. Earth. Sci\u003c/em\u003e.\u003cstrong\u003e 244\u003c/strong\u003e, 1-21 (2023).\u003c/li\u003e\n\u003cli\u003eQiu, Z. et al. Revisiting paleoenvironmental changes on the Upper Yangtze Block during the Ordovician-Silurian transition: New insights from elemental geochemistry. \u003cem\u003eSediment. Geol.\u003c/em\u003e \u003cstrong\u003e450\u003c/strong\u003e, 1-16 (2023).\u003c/li\u003e\n\u003cli\u003eXiao, B. et al. Elemental geochemical characteristics of Shales from Wufeng\u0026minus;Longmaxi Formations in the southern margin of the Qinling Orogenic Belt, China: Implications for depositional controls on organic matter. \u003cem\u003eACS Omega\u003c/em\u003e (2024). DOI: 10.1021/acsomega.4c01129.\u003c/li\u003e\n\u003cli\u003eZhao, Z. Y. et al. Heat-Induced Pore Structure Evolution in the Triassic Chang 7 Shale, Ordos Basin, China: Experimental Simulation of In Situ Conversion Process. \u003cem\u003eJ. Mar. Sci. Eng.\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e(7), 1163 (2023).\u003c/li\u003e\n\u003cli\u003eJiang C. F., Cheng Y. Q., Fan B. J. \u0026amp; Gao S. L. Progress in and challenges to geologic research terrestrial shale in China: A case study from the 7th member of the Upper Triassic Yanchang Fm in the Yanchang exploration block, Ordos Basin. \u003cem\u003eNatur. Gas Ind.\u003c/em\u003e \u003cstrong\u003e34\u003c/strong\u003e(2), 27-33 (2014).\u003c/li\u003e\n\u003cli\u003eHe, J. H., Ding, W. L., Li, R. N., Wang, R. Y. \u0026amp; Zhao, W. Forming condition of the continental shale gas of Shahejie Formation in the central-north Huanghua Depression and its resource prospect. \u003cem\u003ePet. Geol. Recovery Effic.\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e(1), 22-30 (2016).\u003c/li\u003e\n\u003cli\u003eZou, C. N. et al. Advances, challenges, and countermeasures in shale gas exploration of underexplored plays, sequences and new types in China. \u003cem\u003eOil Gas Geol.\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e(2), 309-326 (2024).\u003c/li\u003e\n\u003cli\u003eWu, Y. J., Jia, J. L., Qin, J. Y. \u0026amp; Wang, X. M. The intrusion characteristics of Cenozoic diabase in the middle and northern Fuxin basin and its influence on source rocks. \u003cem\u003eActa Geol. Sin.\u003c/em\u003e \u003cstrong\u003e96\u003c/strong\u003e(3),1026-1040 (2022).\u003c/li\u003e\n\u003cli\u003eXie, W. Q. et al. Formation and evolution of coal-and oil-bearing source rocks in the Lower Cretaceous Shahai Formation in the Fuxin Basin (NE China): Evidence from organic and inorganic geochemical analyses. \u003cem\u003eJ. Pet. Sci. Eng.\u003c/em\u003e \u003cstrong\u003e202\u003c/strong\u003e, 108544 (2021).\u003c/li\u003e\n\u003cli\u003eZhao, Q. et al. Potential of continental shale gas accumulation in medium-and small-sized fault basins in eastern China: A case study from the Fuxin Basin. \u003cem\u003eNatur. Gas Ind.\u003c/em\u003e \u003cstrong\u003e38\u003c/strong\u003e(5), 26-33 (2018).\u003c/li\u003e\n\u003cli\u003eZhang, M. T. et al. Factors Controlling the Pore Development of Low-Mature Marine-Continental Transitional Shale: A Case Study of the Upper Permian Longtan Shale, Western Guizhou, South China. \u003cem\u003eJ. Mar. Sci. Eng.\u003c/em\u003e 11(10), 1862 (2023).\u003c/li\u003e\n\u003cli\u003eXiao, B. et al. Rare Earth Element Characteristics of Shales from Wufeng\u0026ndash;Longmaxi Formations in Deep-Buried Areas of the Northern Sichuan Basin, Southern China: Implications for Provenance, Depositional Conditions, and Paleoclimate. \u003cem\u003eACS Omega\u003c/em\u003e 9(2), 2088-2103 (2024).\u003c/li\u003e\n\u003cli\u003eXiao, B. et al. Late Ordovician-Early Silurian extension of the northern margin of the Upper Yangtze Platform (South China) and its impact on organic matter accumulation. \u003cem\u003eJ. Pet. Sci. Eng.\u003c/em\u003e \u003cstrong\u003e220\u003c/strong\u003e, 111238 (2023).\u003c/li\u003e\n\u003cli\u003eJiao, Y. F. et al. Characteristics and Genesis of Pore-Fracture System in Alkaline Lake Shale, Junggar Basin, China. \u003cem\u003eAppl. Sci.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e(12), 5239 (2024).\u003c/li\u003e\n\u003cli\u003eKang, Z. Q. et al. Characterization of fracture and percolation processes in oil shale under conduction and convection heating modes based on micro-CT technology. \u003cem\u003eJ. Anal. Appl. Pyrolysis\u003c/em\u003e \u003cstrong\u003e181\u003c/strong\u003e, 106601(2024).\u003c/li\u003e\n\u003cli\u003eZhu, B. Y. et al. Complexity and Heterogeneity Evaluation of Pore Structures in the Deep Marine Shale Reservoirs of the Longmaxi Formation, China. \u003cem\u003eJ. Mar. Sci. Eng.\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e(8), 1613 (2023).\u003c/li\u003e\n\u003cli\u003eXu, J. et al. Micro-pore structure characteristics and quantitative characterization of Silurian Longmaxi shale in western Hubei and Hunan areas. \u003cem\u003eNat. Gas Geosci.\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e(4), 611-622 (2021).\u003c/li\u003e\n\u003cli\u003eXu, C. X. et al. Study on the Difference of Microscopic Adsorption Mechanism of Shale Gas in Mineral Pores. \u003cem\u003eSpec. Oil Gas Reservoirs\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e(4), 79-84 (2020).\u003c/li\u003e\n\u003cli\u003eZhang, H. et al. Using Fractal Theory to Study the Influence of Movable Oil on the Pore Structure of Different Types of Shale: A Case Study of the Fengcheng Formation Shale in Well X of Mahu Sag, Junggar Basin, China. \u003cem\u003eFractal and Fractional\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e(4), 242 (2024).\u003c/li\u003e\n\u003cli\u003eTian, X. et al. Evolution of fractal characteristics in shales with increasing thermal maturity: Evidence from neutron scattering, N\u003csub\u003e2\u003c/sub\u003e physisorption, and FE-SEM imaging. \u003cem\u003eEnergy\u003c/em\u003e \u003cstrong\u003e298\u003c/strong\u003e, 131342 (2024).\u003c/li\u003e\n\u003cli\u003eZhao, C. X. et al. Characterization and fractal characteristics of nano-scale pore structure in shale gas reservoirs: a case study of the deep Longmaxi Formation, Zigong region, Southern Sichuan Basin, China. \u003cem\u003eFrontiers in Earth Science\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 1410437 (2024).\u003c/li\u003e\n\u003cli\u003eWang, T. et al. Pore structure and fractal characteristics of transitional shales with different lithofacies from the eastern margin of the Ordos Basin. \u003cem\u003eEnergy Sci. Eng.\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e(11), 3979-4000 (2023).\u003c/li\u003e\n\u003cli\u003eChen, D. Y. et al. Characteristics of lacustrine shale reservoir and its effect on methane adsorption capacity in fuxin basin. \u003cem\u003eEnergy Fuels\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e(11), 11105-11117 (2018).\u003c/li\u003e\n\u003cli\u003eChen, G. et al. Sedimentary and organic matter characteristics of Lower Cretaceous Jiufotang Formation in western Liaoning Province. \u003cem\u003eGeol. Bull. China\u003c/em\u003e \u003cstrong\u003e38\u003c/strong\u003e(2-3), 426-436 (2019).\u003c/li\u003e\n\u003cli\u003eZhu, Z. M., Yan, J. F., Shen, B. \u0026amp; Zhou, J. Y. Co-existing formation of multi-energy resources in the Fuxin Basin: Analysis from tectonic-thermal events. \u003cem\u003eAdv. Earth Sci.\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e(5), 468-479 (2007).\u003c/li\u003e\n\u003cli\u003eWang, X. R., Lu, A. P. \u0026amp; Zhang, X. Y. The features of oil- and gas-bearing strata in the Fuxin Basin. \u003cem\u003eJournal of Stratigraphy\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e(4), 385-390 (2007).\u003c/li\u003e\n\u003cli\u003eZhang, J. Z. et al. Pore structure and fractal characteristics of coal-bearing Cretaceous Nenjiang shales from Songliao Basin, Northeast China. \u003cem\u003eNat. Gas Geosci.\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e(1), 119-132 (2024).\u003c/li\u003e\n\u003cli\u003eHan, M. L. et al. Influence of structural damage on evaluation of microscopic pore structure in marine continental transitional shale of the Southern North China Basin: a method based on the lowtemperature N\u003csub\u003e2\u003c/sub\u003e adsorption experiment. \u003cem\u003ePetrol. Sci.\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e(1),100-115 (2022).\u003c/li\u003e\n\u003cli\u003eThommes, M. et al. Physisorption of gases, with special reference to the evaluation of surface area and pore size distribution (IUPAC Technical Report). \u003cem\u003ePure Appl. Chem.\u003c/em\u003e \u003cstrong\u003e87\u003c/strong\u003e(9-10), 1051-1069 (2022).\u003c/li\u003e\n\u003cli\u003eLi, Z. et al. The Impacts of Matrix Compositions on Nanopore Structure and Fractal Characteristics of Lacustrine Shales from the Changling Fault Depression, Songliao Basin, China. \u003cem\u003eMinerals \u003c/em\u003e\u003cstrong\u003e9\u003c/strong\u003e(2), 127 (2019).\u003c/li\u003e\n\u003cli\u003eYu, K. et al. Fractal Characteristics and Heterogeneity of the Nanopore Structure of Marine Shale in Southern North China. \u003cem\u003eMinerals\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e(4), 242 (2019).\u003c/li\u003e\n\u003cli\u003eBarrett, E. P., Joyner, L.G. \u0026amp; Halenda, P. P. The Determination of Pore Volume and Area Distributions in Porous Substances. I.Computations from Nitrogen Isotherms. \u003cem\u003eJ. Am. Chem. Soc.\u003c/em\u003e \u003cstrong\u003e73\u003c/strong\u003e, 373-380 (1951).\u003c/li\u003e\n\u003cli\u003eBrunauer, S., Emmett, P. H. \u0026amp; Teller, E. Adsorption of Gases in Multimolecular Layers. \u003cem\u003eJ. Am. Chem. Soc.\u003c/em\u003e \u003cstrong\u003e60\u003c/strong\u003e, 309-319 (1938).\u003c/li\u003e\n\u003cli\u003eXie, W. D., Wang, M., Wang, H. \u0026amp; Duan, H. Y. Multi-scale fractal characteristics of pores in transitional shale gas reservoir. \u003cem\u003eNat. Gas Geosci.\u003c/em\u003e 33(3), 451-460 (2022).\u003c/li\u003e\n\u003cli\u003eLi, X. M. et al. Micro-pore structure and fractal characteristics of deep shale from Wufeng Formation to Longmaxi Formation in Jingmen exploration area, Hubei Province. \u003cem\u003eNat. Gas Geosci. \u003c/em\u003e\u003cstrong\u003e33\u003c/strong\u003e(4), 629-641 (2022).\u003c/li\u003e\n\u003cli\u003eLiu, K., Ostadhassan, M., Jang, H.W., Zakharova, N. V. \u0026amp; Shokouhimehr, M. Comparison of Fractal Dimensions from Nitrogen Adsorption Data in Shale via Different Models. \u003cem\u003eRSC Adv.\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 2298-2306 (2021).\u003c/li\u003e\n\u003cli\u003eNeimark, A. A New Approach to the Determination of the Surface Fractal Dimension of Porous Solids. \u003cem\u003ePhys. A\u003c/em\u003e \u003cstrong\u003e191\u003c/strong\u003e, 258-262 (1992).\u003c/li\u003e\n\u003cli\u003eFan, C. J. et al. Scale Effect of Coal Porosity and Permeability Characteristics Based on CT 3D Reconstruction from a Microperspective. \u003cem\u003eEnergy Fuels\u003c/em\u003e \u003cstrong\u003e38\u003c/strong\u003e, 1813-1821 (2024).\u003c/li\u003e\n\u003cli\u003eXiao, B., Xiong, L., Zhao, Z. H. \u0026amp; Fu, X. Sedimentary tectonic pattern of Wufeng and Longmaxi Formations in the northern margin of Sichuan Basin, South China. \u003cem\u003eInt. Geol. Rev.\u003c/em\u003e \u003cstrong\u003e64\u003c/strong\u003e, 2166-2185 (2022).\u003c/li\u003e\n\u003cli\u003eHan, Y. H. et al. Study on the multifractal characterization and seepage of the shale matrix: A case study of the Longmaxi Formation in southwestern Sichuan Basin, China. \u003cem\u003eGeoenergy Sci. Eng. \u003c/em\u003e\u003cstrong\u003e238\u003c/strong\u003e, 212924 (2024).\u003c/li\u003e\n\u003cli\u003eDu, W. et al. Multi-Scale Pore Structure Characterization of Silurian Marine Shale and Its Coupling Relationship With Material Composition: A Case Study in the Northern Guizhou Area. \u003cem\u003eFrontiers in Earth Science\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 930650 (2022).\u003c/li\u003e\n\u003cli\u003eLoucks, R. G., Reed, R. M., Ruppel, S. C. \u0026amp; Hammes, U. Spectrum of pore types and net-works in mudrocks and a descriptive classification for matrix-related mudrock pores. \u003cem\u003eAAPG Bulletin\u003c/em\u003e \u003cstrong\u003e96\u003c/strong\u003e(6), 1071-1098 (2012).\u003c/li\u003e\n\u003cli\u003eFu, X., Liu, X., Wu, Q. X., Xiao, B. \u0026amp; Fan, C. J. Influence of magma intrusion on coal geochemical characteristics: a case study of Tiefa Daxing coal mine. \u003cem\u003eSci. Rep.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e(1),7396 (2024).\u003c/li\u003e\n\u003cli\u003eFu, H. J. et al. Pore Structure and Multi-Scale Fractal Characteristics of Adsorbed Pores in Marine Shale: A Case Study of the Lower Silurian Longmaxi Shale in the Sichuan Basin, China. \u003cem\u003eJ. Earth Sci.\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e(5), 1278-1290 (2022).\u003c/li\u003e\n\u003cli\u003eLiu, J., Bai, X. \u0026amp; Elsworth, D. Evolution of pore systems in low-maturity oil shales during thermal upgrading-Quantified by dynamic SEM and machine learning. \u003cem\u003ePet. Sci.\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e(3), 1739-1750 (2024).\u003c/li\u003e\n\u003cli\u003eZhang, C. H., Zhu, Y. M., Liu, Y.,\u0026nbsp; Chen, J. K. \u0026amp; Li, Z. Y. Pore and Fractal Characteristics of Shale in Different Maturity．\u003cem\u003eFault-Block Oil \u0026amp; Gas Field\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e(05), 583-588 (2016).\u003c/li\u003e\n\u003cli\u003eChen, J. K., Zhu, Y. M., Cui, Z. B. \u0026amp; Zhang, C. H. Pore structure and fractal characteristics of Longmaxi shale in southern Sichuan Basin. \u003cem\u003eLithol. Reservoirs\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e(1), 55-62 (2018).\u003c/li\u003e\n\u003cli\u003eLiang, Z. K. et al. Relationship between multifractal characteristics of pore size and lithofacies of shale of Shahezi Formation in Changling fault depression, Songliao Basin. \u003cem\u003eLithol. Reservoirs \u003c/em\u003e\u003cstrong\u003e32\u003c/strong\u003e(6), 22-35 (2020).\u003c/li\u003e\n\u003cli\u003eZheng, S. S. et al. Characteristics of microscopic pore structures and main controlling factors of Wufeng-Longmaxi Formation shale in southern Sichuan Basin. \u003cem\u003eLithol. Reservoirs \u003c/em\u003e\u003cstrong\u003e31\u003c/strong\u003e(3), 55-65 (2019).\u003c/li\u003e\n\u003cli\u003eZhang, J. Z. et al. Quantitative characterization of pore-fracture system of organic-rich marine-continental shale reservoirs: A case study of the Upper Permian Longtan Formation, Southern Sichuan Basin, China. \u003cem\u003eFuel\u003c/em\u003e \u003cstrong\u003e200\u003c/strong\u003e, 272-281 (2017).\u003c/li\u003e\n\u003cli\u003eCao, T. T. et al. Characteristics of Shale Pores, Fractal Dimension and Their Controlling Factors Determined by Nitrogen Adsorption and Mercury Injection Methods. \u003cem\u003ePet. Geol. Recovery Effic.\u003c/em\u003e \u003cstrong\u003e23\u003c/strong\u003e(2), 1-8 (2016).\u003c/li\u003e\n\u003cli\u003eLuo, R. et al. Effect of Mineral Dissolution by Organic Acids on Pore Structure of Shale Reservoir. \u003cem\u003eJ. China Univ. Pet., Ed. Nat. Sci.\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e(2), 49-59 (2017).\u003c/li\u003e\n\u003cli\u003eHe, S. et al. Shale Reservoir Characteristics and Influencing Actors of Wufeng-Longmaxi Formation in Dingshan Area, Southeast Sichuan. \u003cem\u003eReservoir Evaluation and Development\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e(4), 61-67,78 (2019).\u003c/li\u003e\n\u003cli\u003eXie, W., Wang, M., Wang, H., Ma, R. Y. \u0026amp; Duan, H. Y. Diagenesis of shale and its control on pore structure, a case study from typical marine, transitional and continental shales. \u003cem\u003eFront. Earth Sci.\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e(2), 378-394 (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-5166141/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5166141/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe micro-pore system in shale serves as the gas storage location, and the characterization of micro-pore structure and fractal features is crucial for reservoir research. The development of porosity in shale reservoirs exhibits significant complexity and heterogeneity. While the study of porosity development characteristics in marine shale reservoirs has advanced, research on coal-system shale reservoirs lags behind and requires comprehensive investigation into their fractal characteristics and controlling factors. The study focuses on the coal bearing shale of the Cretaceous Shahai Formation in the Fuxin Basin. By conducting comprehensive analyses of total organic carbon (TOC), mineralogy, and low-temperature N\u003csub\u003e2\u003c/sub\u003e adsorption experiments, this study investigated the relationship between pore structure characteristics and fractal properties of coal-forming shale, as well as the impact of organic matter content, maturity, and mineral composition on the fractal dimension. The results show that the TOC content of the Shahai Formation shale varies greatly (averaging 3.41%) and is rich in clay minerals (averaging 40.91%). Shale development features ink bottle-shaped pores with narrow necks and wide body, parallel plate-shaped pores with openings on all sides, and possibly slit-shaped pores formed by clay minerals. The shale pores exhibit a distinct dual fractal characteristic, with average fractal dimensions D1 and D2 of 2.5243 and 2.7001, respectively. The internal structure is more complex than the surface structure. The micropores in shale play the most significant role in determining the fractal dimension, and are primarily responsible for the non-uniformity and complexity of the pore structure. Organic matter contributes more to the enhancement of the complexity of internal pore space than the roughness of pore surfaces. The number of micropores in organic matter significantly increases with the degree of thermal evolution of organic matter. Carbonate minerals present in the form of cementing material promote the development of micropores, reduce the proportion of mesopores and macropores, and increase the complexity of pores. The anti compaction ability of clay mineral particles is weak. During the compaction and diagenesis process, mineral particles tend to be oriented and arranged, reducing pore space and simplifying pore morphology, thus reducing the complexity of pores. Related studies will provide scientific theoretical support for the comprehensive evaluation of coal bearing shale reservoirs and the study of oil and gas accumulation theories. They also have some significance in revealing the pore development mechanism of coal bearing shale and selecting favorable reservoirs.\u003c/p\u003e","manuscriptTitle":"Fractal characteristics and controlling factors of coal bearing shale pores in the continental fault depression basin of western Liaoning, Northeast China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-04 13:54:56","doi":"10.21203/rs.3.rs-5166141/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":"838f07ac-123e-4cba-a1d8-896938454152","owner":[],"postedDate":"December 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":40296820,"name":"Earth and environmental sciences/Solid earth sciences/Geology"},{"id":40296821,"name":"Earth and environmental sciences/Solid earth sciences/Sedimentology"},{"id":40296822,"name":"Physical sciences/Energy science and technology"}],"tags":[],"updatedAt":"2025-03-24T00:38:10+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-04 13:54:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5166141","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5166141","identity":"rs-5166141","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}