Seismic Frequency Resonance for Geothermal Targeting in a Fault-Controlled Reservoir

Seismic Frequency Resonance for Geothermal Targeting in a Fault-Controlled Reservoir | 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 Method Article Seismic Frequency Resonance for Geothermal Targeting in a Fault-Controlled Reservoir Xianfeng Tan, Hanming Zhang, Chunfeng Liu, Yiguo Xue, Haisheng Li, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7500830/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Seismic Frequency Resonance Exploration (SFRE) was deployed along two 980-m profiles (L1, L2) in the Linyi South sector of the Jiyang Depression to evaluate its capability for delineating targets in a fault-controlled geothermal reservoir. Continuous ambient-noise data were processed using frequency-domain stacking, active–passive spectral matching, and resonance-based apparent-impedance inversion, yielding images to ~ 2 km depth. The sections consistently resolve four stratigraphic units and the southwest-dipping Fault F1; pronounced impedance reductions within the fault damage zone indicate intense fracturing and enhanced permeability. Within the Guantao Formation, SFRE reveals two zones of elevated geothermal prospectivity at intersections with F1, implying structural connectivity with underlying Cambrian–Ordovician carbonates and sustained recharge. On this basis, two borehole locations are proposed—ZK1 (~ 1600 m) and ZK2 (~ 1650 m)—with expected wellhead temperatures of 55–65°C. Cross-line agreement between L1 and L2 demonstrates method robustness under strong cultural noise and complex near-surface conditions. Remaining uncertainties primarily reflect sensitivity to shallow heterogeneity and the current two-dimensional acquisition geometry, which motivate denser profiling and multi-method joint inversion. Overall, the results establish SFRE as a fast, source-free, and noise-resilient approach for prioritizing drilling targets and characterizing reservoir–fault interactions in fault-controlled geothermal systems. Seismic Frequency Resonance (SFRE) fault-controlled geothermal system Guantao Formation drilling target selection Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Geothermal energy is increasingly recognized as a clean, sustainable and versatile source of renewable energy by many nations. Unlike intermittent wind or solar power, geothermal can provide continuous baseload electricity and heat with minimal greenhouse gas emissions (Jolie et al. 2021; Hu et al. 2022 ). In 2022, only 32 countries were operating geothermal power plants, with a combined installed capacity of about 16.3 GW generating ~ 96.6 TWh per year – a mere 0.3% of global electricity production. This indicates vast untapped potential: recent assessments suggest that advanced technologies (e.g. Enhanced Geothermal Systems) could enable hundreds of gigawatts of geothermal power worldwide (Franzmann et al. 2025). Geothermal energy’s share is rapidly growing in some countries – for instance, it now supplies over 60% of electricity in Kenya and more than 25% in Iceland (Gutiérrez-Negrín 2024 ). China also possesses enormous geothermal resources (about 7.9% of the world’s total, by one estimate), yet geothermal accounts for only a small fraction of China’s current energy mix (Zhu et al. 2015 ; Xia and Zhang 2019 ). China is a global leader in direct-use heating applications of medium-low temperature geothermal, but development of deep high-temperature geothermal for power generation has progressed slowly (Pang et al. 2020 ; Xia and Zhang 2019 ). Nonetheless, the outlook is changing under carbon neutrality goals – by 2020 China’s annual geothermal utilization reached the equivalent of 40 million tons of standard coal saved, and policy support is increasing for geothermal in the national energy strategy (Wang et al. 2020b ; Liu et al. 2021 ). This context underscores the importance of efficient geothermal exploration and exploitation strategies. Because geothermal reservoirs are hidden beneath the surface, geophysical exploration methods play a crucial role in identifying and characterizing viable geothermal targets before expensive drilling is undertaken (Kana et al. 2015 ). Geophysical surveys can infer subsurface temperature anomalies, fluid-saturated zones, fault structures and lithology contrasts from the surface, thereby reducing exploration risk. Among these techniques, electrical and electromagnetic (EM) methods are particularly effective for geothermal exploration. Hot geothermal fluids and alternation minerals typically reduce the resistivity of rocks, so methods such as Magnetotellurics (MT) and Controlled-Source AMT can map conductive zones that often correspond to geothermal reservoirs or upflow pathways (Kana et al. 2015 ; Arafa-Hamed et al. 2023). For instance, a recent MT survey in the Western Desert of Egypt detected a deep low-resistivity anomaly interpreted as a heat source and reservoir at > 3 km depth (Arafa-Hamed et al. 2023). In volcanic geothermal fields, seismological methods have also been used to image fluid pathways – e.g., seismic attenuation tomography and shear-wave anisotropy can reveal zones of partial melt or high fluid content beneath volcanoes (Hudson et al. 2022). Active seismic reflection/refraction surveys remain invaluable for delineating subsurface structure, stratigraphy, and fault networks in geothermal areas (De Giorgi and Leucci 2015 ; Sircar et al. 2015 ). High-resolution seismic data can identify the location and offset of faults that act as conduits for geothermal fluids or boundaries of reservoirs. For example, in a low-enthalpy system in Italy, integrated seismic and electrical imaging delineated a shallow faulted carbonate reservoir for geothermal water supply (De Giorgi and Leucci 2015 ). Similarly, Sircar et al. ( 2015 ) reported a successful case in the Dholera geothermal field (India) where a combination of seismic, gravity, and MT methods identified a concealed fault-controlled aquifer. Potential field methods like gravity and magnetic surveys complement geothermal exploration by mapping subsurface density and magnetization anomalies caused by structures such as intrusions, basins, or hydrothermal alteration zones. These data can indicate geothermal favorability (for instance, gravity lows may signify deep heat-induced fracturing or magma chambers). However, on their own, gravity/magnetic methods are non-unique; thus they are often used in conjunction with EM or seismic results (Kana et al. 2015 ). In practice, integrated geophysical approaches are the most effective, as each method provides different subsurface information that can be correlated for a more reliable interpretation. A notable example is the recent geothermal exploration in Reshi Town, Hunan Province, China, where a suite of geophysical techniques was applied in tandem (Ahmed et al. 2024). In that study, researchers combined induced polarization (IP) resistivity sounding, MT profiling, and a joint analysis of multiple survey lines to map the geothermal system comprehensively. The MT data identified deep low-resistivity zones (plausible hot water-bearing horizons), while IP helped detect chargeability anomalies associated with mineralized fault zones, and a shallow joint profiling method imaged near-surface fault traces (Ahmed et al. 2024). Drilling at the indicated targets subsequently confirmed hot water in fractured zones and validated the geophysical predictions (Ahmed et al. 2024). Another case in northern China demonstrated the value of integrating novel passive seismic techniques: Tian et al. ( 2022 ) employed a microtremor (ambient seismic noise) survey along with MT to successfully locate a buried paleo-channel and geothermal reservoir in the Langfang area of Hebei. Their multi-method mapping delineated a deep permeable paleo-river channel filled with geothermal fluids, as well as the major fault controlling upflow (Tian et al. 2022 ). Additionally, seismic frequency resonance (SFR) technology – a recent innovation in exploration seismology – has shown promise for urban geothermal prospecting in China. Qiang et al. ( 2025 ) applied the SFR method (which analyzes characteristic resonant frequencies of subsurface strata) in Xianyang City and were able to detect and outline geothermal anomaly zones beneath the city despite high cultural noise. This technique takes advantage of the natural micro-seismic noise field: distinctive low-frequency resonance peaks can indicate fluid-bearing fracture zones or thermal contrasts at depth (Qiang et al. 2025 ). Likewise, passive seismic monitoring of horizontal-to-vertical spectral ratio (H/V) of ambient noise has been proposed as a tool to sense temporal or spatial changes in geothermal reservoirs (Okamoto et al. 2021 ). Okamoto et al. ( 2021 ) observed H/V spectral anomalies in a Japanese geothermal field correlating with underground fluid activity, suggesting that continuous passive seismic observations might even help monitor geothermal fluid flow and recharge. Apart from dedicated geothermal surveys, it is worth noting that existing oil/gas field data can contribute to geothermal exploration. Many sedimentary basin geothermal systems coincide with petroleum reservoirs or aquifers heated at depth. For example, in the Huabei oilfield of China, the thermal water in deep sandstone layers has been investigated as a geothermal resource in parallel with oil production (Wang et al. 2016 ). Co-produced geothermal energy from oilfields is an attractive concept to improve energy efficiency, and Wang et al. ( 2016 ) discuss strategies for exploiting low-to-medium temperature (70–120°C) water from depleted oil wells for heating and power generation. Such interdisciplinary approaches further underscore the importance of geophysical and engineering data integration to identify accessible heat reservoirs. Overall, advances in geophysical exploration have greatly improved our ability to locate geothermal resources and reduce the risk of drilling non-productive wells. However, significant challenges remain – especially for deep geothermal (HDR/EGS) systems that require engineered reservoirs. In deep crystalline rocks, permeability is inherently low and must be enhanced via hydraulic stimulation (Pang et al. 2020 ). This poses technical difficulties and risks such as induced seismicity, as evidenced by EGS projects worldwide (Li et al. 2022 ). Moreover, the power generation efficiency from current EGS demonstrations is still relatively low, and economic viability often depends on supportive policies or heat co-utilization (Li et al. 2022 ). Ongoing research is tackling these issues by borrowing techniques from the oil/gas industry (such as multi-stage fracturing and reservoir modeling) and by developing innovative concepts like Regenerative EGS, which integrates energy storage to improve output stability (Hou et al. 2024 ). In the meantime, conventional hydrothermal geothermal prospects – especially in favorable geological settings – continue to be the focus of exploration efforts, as they offer the most immediately viable opportunities. In summary, the combination of robust geological understanding and state-of-the-art geophysical exploration is key to unlocking new geothermal resources. By integrating multiple geophysical datasets and learning from both domestic and international case studies, researchers can better characterize geothermal systems and identify sweet spots for development. These efforts ultimately aim to expand geothermal utilization, contributing to a cleaner and more sustainable energy future. 2. Geological Setting 2.1. Regional Tectonics and Faults The study area is located within the Jiyang Depression, a prominent structural unit of the North China Craton. This depression is characterized by alternating uplifts and sags that were shaped by multiple tectonic episodes since the Mesozoic, particularly the Yanshanian and Himalayan movements. These events controlled sedimentary patterns and the development of thick Cenozoic successions. Fault systems are pervasive and exert a first-order control on geothermal reservoirs. The dominant orientations are NNE, NE, and near-EW, with secondary NE-trending structures. Major regional faults, such as the Qihex–Guangrao fault, represent first-order boundaries that separate tectonic subunits and significantly influenced Cenozoic deposition. Secondary faults, including the Cangdong, Bianlinzhen–Yang’erzhuang, Lingxian–Old Yellow River mouth, and Linyi–Huimin faults, delineate third-order structural units and control the distribution of uplifts and depressions. These faults serve as primary pathways for fluid migration and heat transfer, thereby determining the spatial distribution and productivity of geothermal reservoirs in the area. 2.2. Stratigraphy The stratigraphic sequence beneath the study area consists of Quaternary, Neogene, Paleogene, and underlying Paleozoic carbonates, with significant geothermal reservoirs hosted within the Neogene and deeper carbonate units. Quaternary deposits (Q) form the unconsolidated cover, composed of fluvial–lacustrine sediments including sandy clay, silty sand, and interbedded fine sands and clays. They reach a thickness of 600–900 m and act as an effective thermal cap due to their poor thermal conductivity. The Neogene Minghuazhen (Nm) Formation comprises silty clays, sandy mudstones, mudstones, and fine sandstones. These sediments are relatively unconsolidated and provide a low-permeability barrier above the main geothermal reservoirs. The Neogene Guantao (Ng) Formation is the primary porous–fractured geothermal reservoir. It consists of gray to white fine–medium sandstones interbedded with mudstones in the upper part, and thick-bedded conglomerates, gravelly sandstones, and coarse sandstones in the lower part. The reservoir thickness ranges from 300 to 600 m, with an aquifer thickness of 145–280 m. Water temperatures at the wellhead are typically 45–65°C, classifying it as a medium- to low-temperature geothermal system. The Paleogene Dongying Formation hosts fractured reservoirs with variable thicknesses (10–500 m). Its composition of interbedded sandstones and mudstones, together with strong fault control, makes it a secondary but less stable geothermal target. Cambrian–Ordovician carbonates at depth provide karst–fracture reservoirs with large water yields (50–1000 m³/d, occasionally exceeding 3000 m³/d) and elevated temperatures (60–100°C). These reservoirs, controlled by basement structures, offer significant potential but are more deeply buried. 2.3. Caprock and Thermal Regime The geothermal reservoirs in the study area are overlain by thick Cenozoic caprocks that provide effective thermal insulation. The Quaternary Pingyuan Formation, consisting of unconsolidated fluvial and lacustrine sediments such as sandy clays, silty sands, and interbedded fine sands and clays, forms the uppermost seal (Figure. 1). Beneath it, the upper part of the Neogene Minghuazhen Formation is dominated by poorly consolidated mudstones and sandy mudstones, which further enhance the sealing capacity. The cumulative thickness of these caprocks reaches 600–900 m, ensuring low thermal conductivity and preventing vertical heat loss. The geothermal gradient varies between 3.0–4.5°C·100 m⁻¹. Spatial variations are strongly controlled by tectonic units and basement relief: positive structural features (uplifts) generally show higher gradients, while depressions display lower values. In the northwestern sag regions, where the basement is deeply buried, gradients are relatively low. Vertical variations in the geothermal gradient are governed by stratigraphy and lithology, with mudstones exhibiting lower thermal conductivity than sandstones. Consequently, significant differences in geothermal gradients are observed across stratigraphic intervals. 2.4. Hydrothermal Recharge and Circulation The geothermal system in the study area is primarily controlled by deep heat conduction, with low- to medium-temperature geothermal water stored within porous and fractured reservoirs. Heat sources include deep crustal heat flow, tectonic activity, and to a lesser extent, magmatic processes associated with fault evolution. Recharge originates mainly from atmospheric precipitation in the southern Luzhong Mountains and the western Taihang Mountains. Infiltrated meteoric water percolates vertically, migrates laterally through fractures and porous strata, and circulates through deep geological units where it is heated by conduction and minor convective processes. During this circulation, hydrothermal fluids interact with host rocks, dissolving minerals and acquiring trace elements, thereby altering water chemistry. Density-driven convection and hydraulic head gradients maintain slow but continuous groundwater replacement within the geothermal reservoirs. The faults act as preferential channels for recharge and discharge, linking deep thermal sources with overlying porous–fractured formations. This circulation framework explains the observed water chemistry, with Cl–Na and mixed hydrochemical facies dominating, and wellhead temperatures ranging from 45 to 70°C. 3. Methods 3.1. Seismic Frequency Resonance Principle Seismic Frequency Resonance Exploration (SFRE) builds upon the principle that subsurface layers have inherent resonant frequencies governed by their thickness, density, and elastic properties. When the frequency of an incoming seismic wave coincides with the natural frequency of a formation, the amplitude of the response is amplified, producing a resonance effect detectable at the surface. This principle is illustrated in Figure. 2, where a vibrating body exhibits selective amplification when excited at its natural frequency. In geological media, such resonance occurs when seismic waves are reflected or refracted at specific stratigraphic interfaces. The amplitude spectrum at the surface then displays anomalous frequency peaks associated with subsurface impedance contrasts. A schematic of this effect in layered strata is presented in Figure. 3, where resonance leads to amplification of particular frequencies as seismic waves propagate through the subsurface. The behavior of resonance can be described mathematically using multilayer Earth models. For an N -layer medium with velocities V 1 , V 2 , ..., V n , densities ρ 1 , ρ 2 , ..., ρ n , and thicknesses H 1 , H 2 , ..., H n , the surface-recorded wavefield \(\:\varvec{U}\) can be approximated as: $$\:\varvec{U}=\varvec{G}\cdot\:\varvec{M}$$ Where \(\:\varvec{G}\) is the excitation function arising from impedance contrasts, and \(\:\varvec{M}\) is the propagation function representing transmission through overlying layers. A conceptual model of the resonance process is shown in Figure. 4, which highlights how constructive interference at certain frequencies produces enhanced amplitudes observable at the surface. Unlike the Nakamura (HVSR) technique, which infers sediment thickness from microtremor data but has theoretical ambiguities, SFRE explicitly accounts for both body- and surface-wave contributions. By applying frequency-domain stacking to suppress noise, the method establishes a more direct link between resonance peaks and impedance contrasts, offering superior resolution and robustness. 3.2. Survey Design and Acquisition The survey was designed to delineate subsurface structures and geothermal reservoirs to a depth of approximately 2000 m using SFRE. Two survey lines, each 980 m long, were deployed in the southern sector of the Linyi South service area, with a station spacing of 20 m. A total of 100 observation points were acquired, meeting the planned coverage. The acquisition system employed six portable broadband seismographs with three-component sensors. These instruments operated at a sampling interval of 4 ms (250 Hz sampling rate) and were capable of recording both passive ambient noise. To ensure reliable coupling, sensors were semi-buried in the soil, with surface leveling applied in areas of loose sediments or gravel-rich soils. An example of the field deployment is shown in Figure. 5(a), where detectors were placed in shallow pits and stabilized with compacted soil. The observation protocol required a minimum continuous recording length of 27 minutes at each station. Acquisition commenced 15 minutes after powering on the instruments to ensure stable operation. Daily instrument checks and GPS synchronization were performed before data collection. During fieldwork, survey crews monitored the acquisition status in real time via indicator lights and ensured that each station was free from major anthropogenic or environmental disturbances. Representative field conditions are documented in Figure. 5(b), showing the flat alluvial plain terrain and the typical installation of instruments along the survey lines. 3.3. Data Processing and Inversion The processing workflow of the SFRE survey was designed to extract reliable resonance signals from both active and passive seismic records, suppress noise, and derive impedance contrasts associated with geothermal reservoirs. The sequence of operations is: The first step involved energy balancing, applied to compensate for geometric spreading and frequency-dependent attenuation during wave propagation. This correction ensured that amplitude spectra across different stations could be directly compared. Subsequently, resonant-frequency analysis was conducted. Resonance peaks were identified by comparing the input source spectrum with the output response spectrum, highlighting frequency components amplified by subsurface layers. This step allowed for the detection of self-excited frequencies that correspond to specific stratigraphic horizons. To minimize the influence of anthropogenic and environmental noise, frequency matching techniques were applied. By aligning the spectral characteristics of active and passive records, non-geological anomalies were effectively suppressed, isolating signals attributable to subsurface impedance contrasts. The refined spectra were then subjected to frequency stacking, which enhanced resonance peaks while reducing random noise. This statistical averaging reinforced stable features across multiple time segments and spatially distributed measurements. Finally, impedance inversion was performed. By correlating resonance frequencies with the impedance ratios of adjacent layers, two-dimensional cross-sections of resonance impedance inversion were generated along the survey lines. These inversion profiles served as the basis for stratigraphic interpretation and fault delineation. 3.4. Quality Control Ensuring data quality was a central component of the SFRE survey. Multiple procedures were adopted at different stages of acquisition and processing to minimize uncertainties and guarantee reproducibility. Prior to field deployment, an instrument consistency test was conducted on six broadband seismographs. The frequency responses of all units were compared between 0.05 and 150 Hz. Five instruments with amplitude ratios consistently falling within 0.8–1.2 of the mean response were selected for active data collection, while one unit was reserved as a reference base station. A repeat test was performed after the completion of the survey, confirming that all instruments remained within the required tolerance range. During acquisition, real-time monitoring was implemented. Field crews inspected instrument status daily, ensured proper coupling, and validated GPS synchronization. Any anomalous traces were flagged, and re-measurements were conducted immediately when more than 10% of the channels were corrupted. 4. Results 4.1. Line L1 Interpretation Line L1, trending NE–SW with a total length of 980 m, images the subsurface structure to a depth of approximately 2000 m. The resonance impedance inversion profile (Figure. 6(a)) clearly delineates stratigraphy and faulting. Four principal stratigraphic intervals can be distinguished: a. Quaternary deposits (Q, 0–200 m): low-impedance, unconsolidated sediments. b. Neogene Minghuazhen Formation (Nm, ~200–1050 m): relatively low impedances, consistent with silty clays and sandy mudstones. c. Neogene Guantao Formation (Ng, ~1050–1800 m): medium impedance values; the primary porous–fractured geothermal reservoir. d. Cambrian–Ordovician carbonates (>1800 m): high-impedance units, interpreted as karst–fracture aquifers, though not directly penetrated by drilling. A significant fault zone is identified between stations 132 and 138. The profile indicates a southwest-dipping structure with an angle of approximately 65°. This fault, designated F1, is associated with localized impedance reduction, reflecting fractured, water-bearing rocks. Its geometry suggests that F1 serves as a preferential conduit for geothermal fluids, enhancing connectivity within the Guantao Formation and concentrating geothermal potential near the fault zone. 4.2. Line L2 Interpretation Line L2, oriented roughly east–west with the same length and station spacing as L1, provides an additional perspective on the subsurface structure of the study area. The resonance impedance inversion profile (Figure. 6(b)) again delineates stratigraphy to a depth of approximately 2000 m, with consistent layering patterns but locally enhanced structural complexity compared to L1. Four principal stratigraphic intervals are recognized along Line L2: a. Quaternary deposits (Q, 0–180 m): low-impedance unconsolidated sediments forming the surface cover. b. Neogene Minghuazhen Formation (Nm, ~180–1050 m): low impedance values, dominated by silty clay and sandy mudstone. c. Neogene Guantao Formation (Ng, ~1050–1750 m): medium impedance values representing the main geothermal reservoir. d. Cambrian–Ordovician carbonates (>1750 m): high-impedance units interpreted as deep karst–fracture reservoirs. The most prominent structural feature on Line L2 is again Fault F1, identified between stations 162 and 170. Compared to L1, the fault trace appears broader and more steeply inclined, dipping southwest at an estimated angle of 70°. The impedance reduction around the fault zone suggests intense fracturing and possible fluid enrichment. Given its consistent appearance across both lines, F1 is confirmed as a major fault that exerts first-order control on the geothermal system. 4.3. Comparative analysis of deformation characteristics The interpretation of both Lines L1 and L2 consistently identifies a major southwest-dipping fault, designated F1. On Line L1, the fault is imaged between stations 132 and 138 with a dip of ~ 65°, extending from the Quaternary cover through the Neogene and down to the base of the Guantao Formation at ~ 1800 m. On Line L2, the fault appears broader and steeper, located between stations 162 and 170, with a dip angle close to 70°. Despite local variations, both profiles confirm that F1 is a continuous and deeply rooted structure. The integrated interpretation (Figure. 7) suggests that F1 penetrates through the Cenozoic cover and connects with basement structures, thereby acting as a regional conduit for fluid migration. Localized reductions in impedance along the fault zone on both lines indicate intense fracturing and enhanced porosity, consistent with water-bearing features. This structural configuration implies that F1 not only controls the geometry of the Guantao Formation reservoir but also provides vertical connectivity between deep carbonate aquifers and the overlying porous–fractured units. Given its role in channeling hydrothermal fluids, F1 represents the most favorable structural target for geothermal exploration in the study area. The proximity of recommended drilling sites to this fault zone is expected to maximize reservoir productivity and thermal recovery. 4.4. Target Zone and Drilling Sites The integrated interpretation of the resonance inversion profiles highlights the Guantao Formation as the principal geothermal reservoir, with thicknesses of 300–600 m and aquifer intervals of 145–280 m. The southwest-dipping Fault F1 cuts across this reservoir and significantly enhances its permeability, providing pathways for vertical fluid migration. Two zones of elevated geothermal potential were delineated near the intersection of F1 with the Guantao Formation (Figure. 8). These zones are characterized by medium impedance values consistent with porous–fractured sandstones, combined with localized impedance reductions along the fault zone that indicate intense fracturing and improved water-bearing capacity. The structural configuration also suggests connectivity with underlying carbonate reservoirs, which would provide sustained recharge to the system. Based on these features, two drilling sites are recommended: Well ZK1 is proposed near station 135 of Line L1, where F1 intersects the thickest part of the Guantao Formation. The expected depth to the main aquifer is ~ 1600 m, with estimated water temperatures of 55–60°C. Well ZK2 is proposed near station 216 of Line L2, where fault-controlled reservoir development is most pronounced. The anticipated depth is ~ 1650 m, with projected water temperatures of 60–65°C. The location of these wells ensures proximity to both the porous–fractured Guantao Formation and the fractured fault zone, maximizing productivity and thermal recovery. 5. Discussion 5.1. Method Performance and Reliability The application of SFRE in the Linyi South service area demonstrates its ability to achieve both high resolution and considerable depth penetration. Unlike conventional surface-wave dispersion techniques, which rarely image beyond 30 m, SFRE successfully resolved structures to depths of approximately 2000 m. This depth range encompasses not only the Quaternary and Neogene units but also the upper Cambrian–Ordovician carbonates, making the method particularly suited for geothermal exploration in sedimentary basins. The stratigraphic boundaries identified on the resonance profiles correspond well with established regional geology, underscoring the accuracy of the method. The Guantao Formation was consistently delineated as a medium-impedance unit with distinct resonance characteristics, consistent with its role as the primary geothermal reservoir. Furthermore, the reproducibility of results across both Lines L1 and L2 strengthens confidence in the robustness of SFRE. Noise suppression also proved to be a key advantage. Through frequency-domain stacking and active–passive spectral matching, the method reduced cultural and environmental interference that typically hampers seismic surveys in plain areas. The ability to image Fault F1 clearly under these conditions demonstrates the resilience of SFRE and its suitability for complex near-surface environments. Taken together, these observations indicate that SFRE provides reliable and efficient imaging for geothermal target delineation, achieving a balance of resolution, depth, and noise resistance rarely possible with conventional approaches. 5.2. Fault-Controlled Reservoir Mechanism The integrated results confirm that Fault F1 plays a decisive role in controlling the geothermal system of the study area. This southwest-dipping structure cuts through the Cenozoic cover and connects with the carbonate basement, creating vertical pathways for hydrothermal circulation. The localized impedance reductions observed along its trace reflect zones of intense fracturing, which enhance permeability and fluid storage capacity. Within the Guantao Formation, the fault acts as a structural framework that links otherwise disconnected porous–fractured sandstones, transforming them into a hydraulically integrated reservoir system. The spatial coincidence of resonance anomalies with the fault zone further highlights its significance in localizing geothermal potential. The structural connectivity with the Cambrian–Ordovician carbonates also suggests that F1 enables recharge from deeper karst aquifers, ensuring a sustainable supply of heat and fluid to the Neogene reservoirs. This dual role of F1—as a fluid conduit and as a reservoir-enhancing structure—is consistent with global examples of fault-controlled geothermal systems. What distinguishes this study is that SFRE provides direct geophysical evidence of such mechanisms, validating both the method’s interpretive power and the central role of fault analysis in geothermal exploration. 5.3. Uncertainties Despite the encouraging results, several factors introduce uncertainty into this study. One important concern is the sensitivity of resonance responses to near-surface conditions. Variations in soil compaction, surface heterogeneity, and cultural noise may distort spectral amplitudes, particularly at higher frequencies. Although frequency-domain stacking and active–passive matching helped mitigate these effects, residual distortions cannot be fully excluded. A further limitation arises from the simplified stratigraphic assumptions used in impedance interpretation. The Guantao Formation is internally heterogeneous, with interbedded conglomerates, sandstones, and mudstones. Such lithologic variability may generate resonance peaks that are difficult to separate from structural signals, leading to ambiguity in mapping reservoir boundaries where impedance contrasts are weak. The restricted survey coverage also constrains the interpretation. With only two lines available, the results provide robust two-dimensional sections but cannot resolve the full three-dimensional geometry of the geothermal system. While consistency between L1 and L2 strengthens confidence in the findings, lateral variations beyond these profiles remain unconstrained. Denser survey grids or joint inversion with complementary geophysical methods would be required to confirm reservoir continuity. Instrument performance represents another source of uncertainty. Although pre- and post-field consistency tests confirmed acceptable stability, subtle drift or calibration errors may still influence resonance frequency estimation. Taken together, these uncertainties do not undermine the first-order reliability of SFRE imaging, but they highlight the need for drilling and well testing to validate detailed reservoir parameters such as porosity, permeability, and fluid saturation. 6. Conclusions This study demonstrates the effectiveness of Seismic Frequency Resonance Exploration (SFRE) for delineating geothermal targets in fault-controlled reservoirs. The main conclusions are: (1) Methodological validation: SFRE successfully imaged stratigraphic units and fault structures to depths of approximately 2000 m under complex near-surface conditions. The method achieved a balance of resolution, depth penetration, and noise resistance that surpasses conventional geophysical techniques. (2) Reservoir characterization: The Guantao Formation was identified as the primary porous–fractured geothermal reservoir, with a thickness of 300–600 m and aquifer intervals of 145–280 m. Resonance signatures clearly distinguished this unit from overlying mudstone-dominated formations and underlying carbonates. (3) Fault control: Fault F1, dipping southwest at 65–70°, was consistently imaged on both survey lines. The fault zone exhibits reduced impedance values, indicating intense fracturing and fluid enrichment. F1 provides vertical connectivity between deep carbonate aquifers and Neogene reservoirs, acting simultaneously as a conduit and a reservoir-enhancing structure. (4) Target delineation and drilling recommendations: Two geothermal target zones were delineated at the intersections of F1 with the Guantao Formation. Based on these results, drilling sites ZK1 (~ 1600 m, 55–60°C) and ZK2 (~ 1650 m, 60–65°C) were proposed to maximize productivity and thermal recovery. Overall, the study confirms SFRE as a robust and practical method for geothermal exploration in fault-controlled systems, with potential applicability to similar settings worldwide. Declarations Ethics approval and consent to participate Not applicable. Consent for publication All authors approved the final manuscript and the submission to this journal. Competing interests The authors declare that they have no conflict interests. Funding Key Technologies for Multi-Source Energy Integration and Full-Scenario Utilization in Net-Zero Highways under the Dual-Carbon Strategy (JS2024B004). Author Contribution Xianfeng Tan: Writing-Original draft preparation, Reviewing, Editing. Hanming Zhang: Conceptualization, Methodology, Reviewing, Editing. Chunfeng Liu: Reviewing, Editing. Yiguo Xue: Reviewing, Editing. Haisheng Li: Reviewing, Editing. Linzhi Lang: Reviewing, Editing. Xinjian Lv: Reviewing, Editing. Fanmeng Kong: Reviewing, Editing. Data Availability The data used to support the fundings of this study are available from the corresponding author upon request. 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Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 11 May, 2026 Reviewers agreed at journal 13 Apr, 2026 Reviewers agreed at journal 12 Jan, 2026 Reviewers invited by journal 06 Jan, 2026 Editor assigned by journal 13 Dec, 2025 Submission checks completed at journal 16 Sep, 2025 First submitted to journal 31 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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4","display":"","copyAsset":false,"role":"figure","size":41949,"visible":true,"origin":"","legend":"\u003cp\u003eMulti-layer Earth model illustrating resonance response.\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7500830/v1/f02afb1f04f82535c20fce85.jpeg"},{"id":100005697,"identity":"7919a759-fd8a-4dc4-aeec-6a01c7dbed3b","added_by":"auto","created_at":"2026-01-12 05:35:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":968568,"visible":true,"origin":"","legend":"\u003cp\u003eField Layout Diagram \u003cstrong\u003ea\u003c/strong\u003eGeophone Layout \u003cstrong\u003eb\u003c/strong\u003e Survey Line Operation.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7500830/v1/73193e0d1e74713d2af1fdb3.png"},{"id":100361650,"identity":"b68507b9-0b15-47f2-853b-a5dc0c33d219","added_by":"auto","created_at":"2026-01-16 07:45:26","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":871170,"visible":true,"origin":"","legend":"\u003cp\u003eResonance impedance inversion profile along \u003cstrong\u003ea\u003c/strong\u003e Line L1 \u003cstrong\u003eb\u003c/strong\u003e Line L2.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7500830/v1/2c4d2f3647d8722764cb4716.png"},{"id":100005685,"identity":"a6c4450f-261e-44bf-99bf-174d6c69bcef","added_by":"auto","created_at":"2026-01-12 05:35:25","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":939280,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic Diagram of the F1 Fault Plane Location\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7500830/v1/87ea4acf7f993b12c095d5d6.png"},{"id":100361428,"identity":"5816ed4c-0852-42d0-b314-e7bf8052dc31","added_by":"auto","created_at":"2026-01-16 07:45:08","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":712566,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea\u003c/strong\u003e Delineated geothermal target zones and \u003cstrong\u003eb\u003c/strong\u003erecommended drilling sites (ZK1 ZK2) in relation to Fault F1.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7500830/v1/3aefe21e827d56d03d591a9f.png"},{"id":100380893,"identity":"99a00981-5557-4991-8a0e-e3b640d24ad6","added_by":"auto","created_at":"2026-01-16 10:36:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5468208,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7500830/v1/839ed3e8-4f75-4088-9d43-e11387906323.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Seismic Frequency Resonance for Geothermal Targeting in a Fault-Controlled Reservoir","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eGeothermal energy is increasingly recognized as a clean, sustainable and versatile source of renewable energy by many nations. Unlike intermittent wind or solar power, geothermal can provide continuous baseload electricity and heat with minimal greenhouse gas emissions (Jolie et al. 2021; Hu et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In 2022, only 32 countries were operating geothermal power plants, with a combined installed capacity of about 16.3 GW generating\u0026thinsp;~\u0026thinsp;96.6 TWh per year \u0026ndash; a mere 0.3% of global electricity production. This indicates vast untapped potential: recent assessments suggest that advanced technologies (e.g. Enhanced Geothermal Systems) could enable hundreds of gigawatts of geothermal power worldwide (Franzmann et al. 2025). Geothermal energy\u0026rsquo;s share is rapidly growing in some countries \u0026ndash; for instance, it now supplies over 60% of electricity in Kenya and more than 25% in Iceland (Guti\u0026eacute;rrez-Negr\u0026iacute;n \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). China also possesses enormous geothermal resources (about 7.9% of the world\u0026rsquo;s total, by one estimate), yet geothermal accounts for only a small fraction of China\u0026rsquo;s current energy mix (Zhu et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Xia and Zhang \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). China is a global leader in direct-use heating applications of medium-low temperature geothermal, but development of deep high-temperature geothermal for power generation has progressed slowly (Pang et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xia and Zhang \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Nonetheless, the outlook is changing under carbon neutrality goals \u0026ndash; by 2020 China\u0026rsquo;s annual geothermal utilization reached the equivalent of 40\u0026nbsp;million tons of standard coal saved, and policy support is increasing for geothermal in the national energy strategy (Wang et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This context underscores the importance of efficient geothermal exploration and exploitation strategies.\u003c/p\u003e \u003cp\u003eBecause geothermal reservoirs are hidden beneath the surface, geophysical exploration methods play a crucial role in identifying and characterizing viable geothermal targets before expensive drilling is undertaken (Kana et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Geophysical surveys can infer subsurface temperature anomalies, fluid-saturated zones, fault structures and lithology contrasts from the surface, thereby reducing exploration risk. Among these techniques, electrical and electromagnetic (EM) methods are particularly effective for geothermal exploration. Hot geothermal fluids and alternation minerals typically reduce the resistivity of rocks, so methods such as Magnetotellurics (MT) and Controlled-Source AMT can map conductive zones that often correspond to geothermal reservoirs or upflow pathways (Kana et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Arafa-Hamed et al. 2023). For instance, a recent MT survey in the Western Desert of Egypt detected a deep low-resistivity anomaly interpreted as a heat source and reservoir at \u0026gt;\u0026thinsp;3 km depth (Arafa-Hamed et al. 2023). In volcanic geothermal fields, seismological methods have also been used to image fluid pathways \u0026ndash; e.g., seismic attenuation tomography and shear-wave anisotropy can reveal zones of partial melt or high fluid content beneath volcanoes (Hudson et al. 2022). Active seismic reflection/refraction surveys remain invaluable for delineating subsurface structure, stratigraphy, and fault networks in geothermal areas (De Giorgi and Leucci \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sircar et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). High-resolution seismic data can identify the location and offset of faults that act as conduits for geothermal fluids or boundaries of reservoirs. For example, in a low-enthalpy system in Italy, integrated seismic and electrical imaging delineated a shallow faulted carbonate reservoir for geothermal water supply (De Giorgi and Leucci \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Similarly, Sircar et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) reported a successful case in the Dholera geothermal field (India) where a combination of seismic, gravity, and MT methods identified a concealed fault-controlled aquifer. Potential field methods like gravity and magnetic surveys complement geothermal exploration by mapping subsurface density and magnetization anomalies caused by structures such as intrusions, basins, or hydrothermal alteration zones. These data can indicate geothermal favorability (for instance, gravity lows may signify deep heat-induced fracturing or magma chambers). However, on their own, gravity/magnetic methods are non-unique; thus they are often used in conjunction with EM or seismic results (Kana et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn practice, integrated geophysical approaches are the most effective, as each method provides different subsurface information that can be correlated for a more reliable interpretation. A notable example is the recent geothermal exploration in Reshi Town, Hunan Province, China, where a suite of geophysical techniques was applied in tandem (Ahmed et al. 2024). In that study, researchers combined induced polarization (IP) resistivity sounding, MT profiling, and a joint analysis of multiple survey lines to map the geothermal system comprehensively. The MT data identified deep low-resistivity zones (plausible hot water-bearing horizons), while IP helped detect chargeability anomalies associated with mineralized fault zones, and a shallow joint profiling method imaged near-surface fault traces (Ahmed et al. 2024). Drilling at the indicated targets subsequently confirmed hot water in fractured zones and validated the geophysical predictions (Ahmed et al. 2024). Another case in northern China demonstrated the value of integrating novel passive seismic techniques: Tian et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) employed a microtremor (ambient seismic noise) survey along with MT to successfully locate a buried paleo-channel and geothermal reservoir in the Langfang area of Hebei. Their multi-method mapping delineated a deep permeable paleo-river channel filled with geothermal fluids, as well as the major fault controlling upflow (Tian et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, seismic frequency resonance (SFR) technology \u0026ndash; a recent innovation in exploration seismology \u0026ndash; has shown promise for urban geothermal prospecting in China. Qiang et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) applied the SFR method (which analyzes characteristic resonant frequencies of subsurface strata) in Xianyang City and were able to detect and outline geothermal anomaly zones beneath the city despite high cultural noise. This technique takes advantage of the natural micro-seismic noise field: distinctive low-frequency resonance peaks can indicate fluid-bearing fracture zones or thermal contrasts at depth (Qiang et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Likewise, passive seismic monitoring of horizontal-to-vertical spectral ratio (H/V) of ambient noise has been proposed as a tool to sense temporal or spatial changes in geothermal reservoirs (Okamoto et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Okamoto et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) observed H/V spectral anomalies in a Japanese geothermal field correlating with underground fluid activity, suggesting that continuous passive seismic observations might even help monitor geothermal fluid flow and recharge.\u003c/p\u003e \u003cp\u003eApart from dedicated geothermal surveys, it is worth noting that existing oil/gas field data can contribute to geothermal exploration. Many sedimentary basin geothermal systems coincide with petroleum reservoirs or aquifers heated at depth. For example, in the Huabei oilfield of China, the thermal water in deep sandstone layers has been investigated as a geothermal resource in parallel with oil production (Wang et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Co-produced geothermal energy from oilfields is an attractive concept to improve energy efficiency, and Wang et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) discuss strategies for exploiting low-to-medium temperature (70\u0026ndash;120\u0026deg;C) water from depleted oil wells for heating and power generation. Such interdisciplinary approaches further underscore the importance of geophysical and engineering data integration to identify accessible heat reservoirs.\u003c/p\u003e \u003cp\u003eOverall, advances in geophysical exploration have greatly improved our ability to locate geothermal resources and reduce the risk of drilling non-productive wells. However, significant challenges remain \u0026ndash; especially for deep geothermal (HDR/EGS) systems that require engineered reservoirs. In deep crystalline rocks, permeability is inherently low and must be enhanced via hydraulic stimulation (Pang et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This poses technical difficulties and risks such as induced seismicity, as evidenced by EGS projects worldwide (Li et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, the power generation efficiency from current EGS demonstrations is still relatively low, and economic viability often depends on supportive policies or heat co-utilization (Li et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Ongoing research is tackling these issues by borrowing techniques from the oil/gas industry (such as multi-stage fracturing and reservoir modeling) and by developing innovative concepts like Regenerative EGS, which integrates energy storage to improve output stability (Hou et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In the meantime, conventional hydrothermal geothermal prospects \u0026ndash; especially in favorable geological settings \u0026ndash; continue to be the focus of exploration efforts, as they offer the most immediately viable opportunities. In summary, the combination of robust geological understanding and state-of-the-art geophysical exploration is key to unlocking new geothermal resources. By integrating multiple geophysical datasets and learning from both domestic and international case studies, researchers can better characterize geothermal systems and identify sweet spots for development. These efforts ultimately aim to expand geothermal utilization, contributing to a cleaner and more sustainable energy future.\u003c/p\u003e"},{"header":"2. Geological Setting","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Regional Tectonics and Faults\u003c/h2\u003e \u003cp\u003eThe study area is located within the Jiyang Depression, a prominent structural unit of the North China Craton. This depression is characterized by alternating uplifts and sags that were shaped by multiple tectonic episodes since the Mesozoic, particularly the Yanshanian and Himalayan movements. These events controlled sedimentary patterns and the development of thick Cenozoic successions.\u003c/p\u003e \u003cp\u003eFault systems are pervasive and exert a first-order control on geothermal reservoirs. The dominant orientations are NNE, NE, and near-EW, with secondary NE-trending structures. Major regional faults, such as the Qihex\u0026ndash;Guangrao fault, represent first-order boundaries that separate tectonic subunits and significantly influenced Cenozoic deposition. Secondary faults, including the Cangdong, Bianlinzhen\u0026ndash;Yang\u0026rsquo;erzhuang, Lingxian\u0026ndash;Old Yellow River mouth, and Linyi\u0026ndash;Huimin faults, delineate third-order structural units and control the distribution of uplifts and depressions. These faults serve as primary pathways for fluid migration and heat transfer, thereby determining the spatial distribution and productivity of geothermal reservoirs in the area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Stratigraphy\u003c/h2\u003e \u003cp\u003eThe stratigraphic sequence beneath the study area consists of Quaternary, Neogene, Paleogene, and underlying Paleozoic carbonates, with significant geothermal reservoirs hosted within the Neogene and deeper carbonate units.\u003c/p\u003e \u003cp\u003eQuaternary deposits (Q) form the unconsolidated cover, composed of fluvial\u0026ndash;lacustrine sediments including sandy clay, silty sand, and interbedded fine sands and clays. They reach a thickness of 600\u0026ndash;900 m and act as an effective thermal cap due to their poor thermal conductivity.\u003c/p\u003e \u003cp\u003eThe Neogene Minghuazhen (Nm) Formation comprises silty clays, sandy mudstones, mudstones, and fine sandstones. These sediments are relatively unconsolidated and provide a low-permeability barrier above the main geothermal reservoirs.\u003c/p\u003e \u003cp\u003eThe Neogene Guantao (Ng) Formation is the primary porous\u0026ndash;fractured geothermal reservoir. It consists of gray to white fine\u0026ndash;medium sandstones interbedded with mudstones in the upper part, and thick-bedded conglomerates, gravelly sandstones, and coarse sandstones in the lower part. The reservoir thickness ranges from 300 to 600 m, with an aquifer thickness of 145\u0026ndash;280 m. Water temperatures at the wellhead are typically 45\u0026ndash;65\u0026deg;C, classifying it as a medium- to low-temperature geothermal system.\u003c/p\u003e \u003cp\u003eThe Paleogene Dongying Formation hosts fractured reservoirs with variable thicknesses (10\u0026ndash;500 m). Its composition of interbedded sandstones and mudstones, together with strong fault control, makes it a secondary but less stable geothermal target.\u003c/p\u003e \u003cp\u003eCambrian\u0026ndash;Ordovician carbonates at depth provide karst\u0026ndash;fracture reservoirs with large water yields (50\u0026ndash;1000 m\u0026sup3;/d, occasionally exceeding 3000 m\u0026sup3;/d) and elevated temperatures (60\u0026ndash;100\u0026deg;C). These reservoirs, controlled by basement structures, offer significant potential but are more deeply buried.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Caprock and Thermal Regime\u003c/h2\u003e \u003cp\u003eThe geothermal reservoirs in the study area are overlain by thick Cenozoic caprocks that provide effective thermal insulation. The Quaternary Pingyuan Formation, consisting of unconsolidated fluvial and lacustrine sediments such as sandy clays, silty sands, and interbedded fine sands and clays, forms the uppermost seal (Figure. 1). Beneath it, the upper part of the Neogene Minghuazhen Formation is dominated by poorly consolidated mudstones and sandy mudstones, which further enhance the sealing capacity. The cumulative thickness of these caprocks reaches 600\u0026ndash;900 m, ensuring low thermal conductivity and preventing vertical heat loss.\u003c/p\u003e \u003cp\u003eThe geothermal gradient varies between 3.0\u0026ndash;4.5\u0026deg;C\u0026middot;100 m⁻\u0026sup1;. Spatial variations are strongly controlled by tectonic units and basement relief: positive structural features (uplifts) generally show higher gradients, while depressions display lower values. In the northwestern sag regions, where the basement is deeply buried, gradients are relatively low. Vertical variations in the geothermal gradient are governed by stratigraphy and lithology, with mudstones exhibiting lower thermal conductivity than sandstones. Consequently, significant differences in geothermal gradients are observed across stratigraphic intervals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Hydrothermal Recharge and Circulation\u003c/h2\u003e \u003cp\u003eThe geothermal system in the study area is primarily controlled by deep heat conduction, with low- to medium-temperature geothermal water stored within porous and fractured reservoirs. Heat sources include deep crustal heat flow, tectonic activity, and to a lesser extent, magmatic processes associated with fault evolution.\u003c/p\u003e \u003cp\u003eRecharge originates mainly from atmospheric precipitation in the southern Luzhong Mountains and the western Taihang Mountains. Infiltrated meteoric water percolates vertically, migrates laterally through fractures and porous strata, and circulates through deep geological units where it is heated by conduction and minor convective processes. During this circulation, hydrothermal fluids interact with host rocks, dissolving minerals and acquiring trace elements, thereby altering water chemistry.\u003c/p\u003e \u003cp\u003eDensity-driven convection and hydraulic head gradients maintain slow but continuous groundwater replacement within the geothermal reservoirs. The faults act as preferential channels for recharge and discharge, linking deep thermal sources with overlying porous\u0026ndash;fractured formations. This circulation framework explains the observed water chemistry, with Cl\u0026ndash;Na and mixed hydrochemical facies dominating, and wellhead temperatures ranging from 45 to 70\u0026deg;C.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Seismic Frequency Resonance Principle\u003c/h2\u003e \u003cp\u003eSeismic Frequency Resonance Exploration (SFRE) builds upon the principle that subsurface layers have inherent resonant frequencies governed by their thickness, density, and elastic properties. When the frequency of an incoming seismic wave coincides with the natural frequency of a formation, the amplitude of the response is amplified, producing a resonance effect detectable at the surface. This principle is illustrated in Figure. 2, where a vibrating body exhibits selective amplification when excited at its natural frequency.\u003c/p\u003e \u003cp\u003eIn geological media, such resonance occurs when seismic waves are reflected or refracted at specific stratigraphic interfaces. The amplitude spectrum at the surface then displays anomalous frequency peaks associated with subsurface impedance contrasts. A schematic of this effect in layered strata is presented in Figure. 3, where resonance leads to amplification of particular frequencies as seismic waves propagate through the subsurface.\u003c/p\u003e \u003cp\u003eThe behavior of resonance can be described mathematically using multilayer Earth models. For an \u003cem\u003eN\u003c/em\u003e-layer medium with velocities \u003cem\u003eV\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e, \u003cem\u003eV\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e, ..., \u003cem\u003eV\u003c/em\u003e\u003csub\u003en\u003c/sub\u003e, densities \u003cem\u003eρ\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e, \u003cem\u003eρ\u003c/em\u003e \u003csub\u003e2\u003c/sub\u003e, ..., \u003cem\u003eρ\u003c/em\u003e\u003csub\u003en\u003c/sub\u003e, and thicknesses \u003cem\u003eH\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e, \u003cem\u003eH\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e, ..., \u003cem\u003eH\u003c/em\u003e\u003csub\u003en\u003c/sub\u003e, the surface-recorded wavefield \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{U}\\)\u003c/span\u003e\u003c/span\u003e can be approximated as:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{U}=\\varvec{G}\\cdot\\:\\varvec{M}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{G}\\)\u003c/span\u003e\u003c/span\u003e is the excitation function arising from impedance contrasts, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{M}\\)\u003c/span\u003e\u003c/span\u003e is the propagation function representing transmission through overlying layers. A conceptual model of the resonance process is shown in Figure. 4, which highlights how constructive interference at certain frequencies produces enhanced amplitudes observable at the surface.\u003c/p\u003e \u003cp\u003eUnlike the Nakamura (HVSR) technique, which infers sediment thickness from microtremor data but has theoretical ambiguities, SFRE explicitly accounts for both body- and surface-wave contributions. By applying frequency-domain stacking to suppress noise, the method establishes a more direct link between resonance peaks and impedance contrasts, offering superior resolution and robustness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Survey Design and Acquisition\u003c/h2\u003e \u003cp\u003eThe survey was designed to delineate subsurface structures and geothermal reservoirs to a depth of approximately 2000 m using SFRE. Two survey lines, each 980 m long, were deployed in the southern sector of the Linyi South service area, with a station spacing of 20 m. A total of 100 observation points were acquired, meeting the planned coverage.\u003c/p\u003e \u003cp\u003eThe acquisition system employed six portable broadband seismographs with three-component sensors. These instruments operated at a sampling interval of 4 ms (250 Hz sampling rate) and were capable of recording both passive ambient noise. To ensure reliable coupling, sensors were semi-buried in the soil, with surface leveling applied in areas of loose sediments or gravel-rich soils. An example of the field deployment is shown in Figure. 5(a), where detectors were placed in shallow pits and stabilized with compacted soil.\u003c/p\u003e \u003cp\u003eThe observation protocol required a minimum continuous recording length of 27 minutes at each station. Acquisition commenced 15 minutes after powering on the instruments to ensure stable operation. Daily instrument checks and GPS synchronization were performed before data collection. During fieldwork, survey crews monitored the acquisition status in real time via indicator lights and ensured that each station was free from major anthropogenic or environmental disturbances.\u003c/p\u003e \u003cp\u003eRepresentative field conditions are documented in Figure. 5(b), showing the flat alluvial plain terrain and the typical installation of instruments along the survey lines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Data Processing and Inversion\u003c/h2\u003e \u003cp\u003eThe processing workflow of the SFRE survey was designed to extract reliable resonance signals from both active and passive seismic records, suppress noise, and derive impedance contrasts associated with geothermal reservoirs. The sequence of operations is:\u003c/p\u003e \u003cp\u003eThe first step involved energy balancing, applied to compensate for geometric spreading and frequency-dependent attenuation during wave propagation. This correction ensured that amplitude spectra across different stations could be directly compared.\u003c/p\u003e \u003cp\u003eSubsequently, resonant-frequency analysis was conducted. Resonance peaks were identified by comparing the input source spectrum with the output response spectrum, highlighting frequency components amplified by subsurface layers. This step allowed for the detection of self-excited frequencies that correspond to specific stratigraphic horizons.\u003c/p\u003e \u003cp\u003eTo minimize the influence of anthropogenic and environmental noise, frequency matching techniques were applied. By aligning the spectral characteristics of active and passive records, non-geological anomalies were effectively suppressed, isolating signals attributable to subsurface impedance contrasts.\u003c/p\u003e \u003cp\u003eThe refined spectra were then subjected to frequency stacking, which enhanced resonance peaks while reducing random noise. This statistical averaging reinforced stable features across multiple time segments and spatially distributed measurements.\u003c/p\u003e \u003cp\u003eFinally, impedance inversion was performed. By correlating resonance frequencies with the impedance ratios of adjacent layers, two-dimensional cross-sections of resonance impedance inversion were generated along the survey lines. These inversion profiles served as the basis for stratigraphic interpretation and fault delineation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Quality Control\u003c/h2\u003e \u003cp\u003eEnsuring data quality was a central component of the SFRE survey. Multiple procedures were adopted at different stages of acquisition and processing to minimize uncertainties and guarantee reproducibility.\u003c/p\u003e \u003cp\u003ePrior to field deployment, an instrument consistency test was conducted on six broadband seismographs. The frequency responses of all units were compared between 0.05 and 150 Hz. Five instruments with amplitude ratios consistently falling within 0.8\u0026ndash;1.2 of the mean response were selected for active data collection, while one unit was reserved as a reference base station. A repeat test was performed after the completion of the survey, confirming that all instruments remained within the required tolerance range.\u003c/p\u003e \u003cp\u003eDuring acquisition, real-time monitoring was implemented. Field crews inspected instrument status daily, ensured proper coupling, and validated GPS synchronization. Any anomalous traces were flagged, and re-measurements were conducted immediately when more than 10% of the channels were corrupted.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1. Line L1 Interpretation\u003c/h2\u003e\n \u003cp\u003eLine L1, trending NE\u0026ndash;SW with a total length of 980 m, images the subsurface structure to a depth of approximately 2000 m. The resonance impedance inversion profile (Figure. 6(a)) clearly delineates stratigraphy and faulting. Four principal stratigraphic intervals can be distinguished:\u003c/p\u003e\n \u003cp\u003ea. Quaternary deposits (Q, 0\u0026ndash;200 m): low-impedance, unconsolidated sediments.\u003c/p\u003e\n \u003cp\u003eb. Neogene Minghuazhen Formation (Nm, ~200\u0026ndash;1050 m): relatively low impedances, consistent with silty clays and sandy mudstones.\u003c/p\u003e\n \u003cp\u003ec. Neogene Guantao Formation (Ng, ~1050\u0026ndash;1800 m): medium impedance values; the primary porous\u0026ndash;fractured geothermal reservoir.\u003c/p\u003e\n \u003cp\u003ed. Cambrian\u0026ndash;Ordovician carbonates (\u0026gt;1800 m): high-impedance units, interpreted as karst\u0026ndash;fracture aquifers, though not directly penetrated by drilling.\u003c/p\u003e\n \u003cp\u003eA significant fault zone is identified between stations 132 and 138. The profile indicates a southwest-dipping structure with an angle of approximately 65\u0026deg;. This fault, designated F1, is associated with localized impedance reduction, reflecting fractured, water-bearing rocks. Its geometry suggests that F1 serves as a preferential conduit for geothermal fluids, enhancing connectivity within the Guantao Formation and concentrating geothermal potential near the fault zone.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e4.2. Line L2 Interpretation\u003c/h2\u003e\n \u003cp\u003eLine L2, oriented roughly east\u0026ndash;west with the same length and station spacing as L1, provides an additional perspective on the subsurface structure of the study area. The resonance impedance inversion profile (Figure. 6(b)) again delineates stratigraphy to a depth of approximately 2000 m, with consistent layering patterns but locally enhanced structural complexity compared to L1.\u003c/p\u003e\n \u003cp\u003eFour principal stratigraphic intervals are recognized along Line L2:\u003c/p\u003e\n \u003cp\u003ea. Quaternary deposits (Q, 0\u0026ndash;180 m): low-impedance unconsolidated sediments forming the surface cover.\u003c/p\u003e\n \u003cp\u003eb. Neogene Minghuazhen Formation (Nm, ~180\u0026ndash;1050 m): low impedance values, dominated by silty clay and sandy mudstone.\u003c/p\u003e\n \u003cp\u003ec. Neogene Guantao Formation (Ng, ~1050\u0026ndash;1750 m): medium impedance values representing the main geothermal reservoir.\u003c/p\u003e\n \u003cp\u003ed. Cambrian\u0026ndash;Ordovician carbonates (\u0026gt;1750 m): high-impedance units interpreted as deep karst\u0026ndash;fracture reservoirs.\u003c/p\u003e\n \u003cp\u003eThe most prominent structural feature on Line L2 is again Fault F1, identified between stations 162 and 170. Compared to L1, the fault trace appears broader and more steeply inclined, dipping southwest at an estimated angle of 70\u0026deg;. The impedance reduction around the fault zone suggests intense fracturing and possible fluid enrichment. Given its consistent appearance across both lines, F1 is confirmed as a major fault that exerts first-order control on the geothermal system.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e4.3. Comparative analysis of deformation characteristics\u003c/h2\u003e\n \u003cp\u003eThe interpretation of both Lines L1 and L2 consistently identifies a major southwest-dipping fault, designated F1. On Line L1, the fault is imaged between stations 132 and 138 with a dip of ~\u0026thinsp;65\u0026deg;, extending from the Quaternary cover through the Neogene and down to the base of the Guantao Formation at ~\u0026thinsp;1800 m. On Line L2, the fault appears broader and steeper, located between stations 162 and 170, with a dip angle close to 70\u0026deg;. Despite local variations, both profiles confirm that F1 is a continuous and deeply rooted structure.\u003c/p\u003e\n \u003cp\u003eThe integrated interpretation (Figure. 7) suggests that F1 penetrates through the Cenozoic cover and connects with basement structures, thereby acting as a regional conduit for fluid migration. Localized reductions in impedance along the fault zone on both lines indicate intense fracturing and enhanced porosity, consistent with water-bearing features. This structural configuration implies that F1 not only controls the geometry of the Guantao Formation reservoir but also provides vertical connectivity between deep carbonate aquifers and the overlying porous\u0026ndash;fractured units.\u003c/p\u003e\n \u003cp\u003eGiven its role in channeling hydrothermal fluids, F1 represents the most favorable structural target for geothermal exploration in the study area. The proximity of recommended drilling sites to this fault zone is expected to maximize reservoir productivity and thermal recovery.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e4.4. Target Zone and Drilling Sites\u003c/h2\u003e\n \u003cp\u003eThe integrated interpretation of the resonance inversion profiles highlights the Guantao Formation as the principal geothermal reservoir, with thicknesses of 300\u0026ndash;600 m and aquifer intervals of 145\u0026ndash;280 m. The southwest-dipping Fault F1 cuts across this reservoir and significantly enhances its permeability, providing pathways for vertical fluid migration. Two zones of elevated geothermal potential were delineated near the intersection of F1 with the Guantao Formation (Figure. 8). These zones are characterized by medium impedance values consistent with porous\u0026ndash;fractured sandstones, combined with localized impedance reductions along the fault zone that indicate intense fracturing and improved water-bearing capacity. The structural configuration also suggests connectivity with underlying carbonate reservoirs, which would provide sustained recharge to the system.\u003c/p\u003e\n \u003cp\u003eBased on these features, two drilling sites are recommended:\u003c/p\u003e\n \u003cp\u003eWell ZK1 is proposed near station 135 of Line L1, where F1 intersects the thickest part of the Guantao Formation. The expected depth to the main aquifer is ~\u0026thinsp;1600 m, with estimated water temperatures of 55\u0026ndash;60\u0026deg;C.\u003c/p\u003e\n \u003cp\u003eWell ZK2 is proposed near station 216 of Line L2, where fault-controlled reservoir development is most pronounced. The anticipated depth is ~\u0026thinsp;1650 m, with projected water temperatures of 60\u0026ndash;65\u0026deg;C.\u003c/p\u003e\n \u003cp\u003eThe location of these wells ensures proximity to both the porous\u0026ndash;fractured Guantao Formation and the fractured fault zone, maximizing productivity and thermal recovery.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e5.1. Method Performance and Reliability\u003c/h2\u003e \u003cp\u003eThe application of SFRE in the Linyi South service area demonstrates its ability to achieve both high resolution and considerable depth penetration. Unlike conventional surface-wave dispersion techniques, which rarely image beyond 30 m, SFRE successfully resolved structures to depths of approximately 2000 m. This depth range encompasses not only the Quaternary and Neogene units but also the upper Cambrian\u0026ndash;Ordovician carbonates, making the method particularly suited for geothermal exploration in sedimentary basins.\u003c/p\u003e \u003cp\u003eThe stratigraphic boundaries identified on the resonance profiles correspond well with established regional geology, underscoring the accuracy of the method. The Guantao Formation was consistently delineated as a medium-impedance unit with distinct resonance characteristics, consistent with its role as the primary geothermal reservoir. Furthermore, the reproducibility of results across both Lines L1 and L2 strengthens confidence in the robustness of SFRE.\u003c/p\u003e \u003cp\u003eNoise suppression also proved to be a key advantage. Through frequency-domain stacking and active\u0026ndash;passive spectral matching, the method reduced cultural and environmental interference that typically hampers seismic surveys in plain areas. The ability to image Fault F1 clearly under these conditions demonstrates the resilience of SFRE and its suitability for complex near-surface environments.\u003c/p\u003e \u003cp\u003eTaken together, these observations indicate that SFRE provides reliable and efficient imaging for geothermal target delineation, achieving a balance of resolution, depth, and noise resistance rarely possible with conventional approaches.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e5.2. Fault-Controlled Reservoir Mechanism\u003c/h2\u003e \u003cp\u003eThe integrated results confirm that Fault F1 plays a decisive role in controlling the geothermal system of the study area. This southwest-dipping structure cuts through the Cenozoic cover and connects with the carbonate basement, creating vertical pathways for hydrothermal circulation. The localized impedance reductions observed along its trace reflect zones of intense fracturing, which enhance permeability and fluid storage capacity.\u003c/p\u003e \u003cp\u003eWithin the Guantao Formation, the fault acts as a structural framework that links otherwise disconnected porous\u0026ndash;fractured sandstones, transforming them into a hydraulically integrated reservoir system. The spatial coincidence of resonance anomalies with the fault zone further highlights its significance in localizing geothermal potential. The structural connectivity with the Cambrian\u0026ndash;Ordovician carbonates also suggests that F1 enables recharge from deeper karst aquifers, ensuring a sustainable supply of heat and fluid to the Neogene reservoirs.\u003c/p\u003e \u003cp\u003eThis dual role of F1\u0026mdash;as a fluid conduit and as a reservoir-enhancing structure\u0026mdash;is consistent with global examples of fault-controlled geothermal systems. What distinguishes this study is that SFRE provides direct geophysical evidence of such mechanisms, validating both the method\u0026rsquo;s interpretive power and the central role of fault analysis in geothermal exploration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e5.3. Uncertainties\u003c/h2\u003e \u003cp\u003eDespite the encouraging results, several factors introduce uncertainty into this study. One important concern is the sensitivity of resonance responses to near-surface conditions. Variations in soil compaction, surface heterogeneity, and cultural noise may distort spectral amplitudes, particularly at higher frequencies. Although frequency-domain stacking and active\u0026ndash;passive matching helped mitigate these effects, residual distortions cannot be fully excluded.\u003c/p\u003e \u003cp\u003eA further limitation arises from the simplified stratigraphic assumptions used in impedance interpretation. The Guantao Formation is internally heterogeneous, with interbedded conglomerates, sandstones, and mudstones. Such lithologic variability may generate resonance peaks that are difficult to separate from structural signals, leading to ambiguity in mapping reservoir boundaries where impedance contrasts are weak.\u003c/p\u003e \u003cp\u003eThe restricted survey coverage also constrains the interpretation. With only two lines available, the results provide robust two-dimensional sections but cannot resolve the full three-dimensional geometry of the geothermal system. While consistency between L1 and L2 strengthens confidence in the findings, lateral variations beyond these profiles remain unconstrained. Denser survey grids or joint inversion with complementary geophysical methods would be required to confirm reservoir continuity.\u003c/p\u003e \u003cp\u003eInstrument performance represents another source of uncertainty. Although pre- and post-field consistency tests confirmed acceptable stability, subtle drift or calibration errors may still influence resonance frequency estimation.\u003c/p\u003e \u003cp\u003eTaken together, these uncertainties do not undermine the first-order reliability of SFRE imaging, but they highlight the need for drilling and well testing to validate detailed reservoir parameters such as porosity, permeability, and fluid saturation.\u003c/p\u003e \u003c/div\u003e"},{"header":"6. Conclusions","content":"\u003cp\u003eThis study demonstrates the effectiveness of Seismic Frequency Resonance Exploration (SFRE) for delineating geothermal targets in fault-controlled reservoirs. The main conclusions are:\u003c/p\u003e \u003cp\u003e(1) Methodological validation: SFRE successfully imaged stratigraphic units and fault structures to depths of approximately 2000 m under complex near-surface conditions. The method achieved a balance of resolution, depth penetration, and noise resistance that surpasses conventional geophysical techniques.\u003c/p\u003e \u003cp\u003e(2) Reservoir characterization: The Guantao Formation was identified as the primary porous\u0026ndash;fractured geothermal reservoir, with a thickness of 300\u0026ndash;600 m and aquifer intervals of 145\u0026ndash;280 m. Resonance signatures clearly distinguished this unit from overlying mudstone-dominated formations and underlying carbonates.\u003c/p\u003e \u003cp\u003e(3) Fault control: Fault F1, dipping southwest at 65\u0026ndash;70\u0026deg;, was consistently imaged on both survey lines. The fault zone exhibits reduced impedance values, indicating intense fracturing and fluid enrichment. F1 provides vertical connectivity between deep carbonate aquifers and Neogene reservoirs, acting simultaneously as a conduit and a reservoir-enhancing structure.\u003c/p\u003e \u003cp\u003e(4) Target delineation and drilling recommendations: Two geothermal target zones were delineated at the intersections of F1 with the Guantao Formation. Based on these results, drilling sites ZK1 (~\u0026thinsp;1600 m, 55\u0026ndash;60\u0026deg;C) and ZK2 (~\u0026thinsp;1650 m, 60\u0026ndash;65\u0026deg;C) were proposed to maximize productivity and thermal recovery.\u003c/p\u003e \u003cp\u003eOverall, the study confirms SFRE as a robust and practical method for geothermal exploration in fault-controlled systems, with potential applicability to similar settings worldwide.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors approved the final manuscript and the submission to this journal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKey Technologies for Multi-Source Energy Integration and Full-Scenario Utilization in Net-Zero Highways under the Dual-Carbon Strategy (JS2024B004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXianfeng Tan: Writing-Original draft preparation, Reviewing, Editing. Hanming Zhang: Conceptualization, Methodology, Reviewing, Editing. Chunfeng Liu: Reviewing, Editing. Yiguo Xue: Reviewing, Editing. Haisheng Li: Reviewing, Editing. Linzhi Lang: Reviewing, Editing. Xinjian Lv: Reviewing, Editing. Fanmeng Kong: Reviewing, Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used to support the fundings of this study are available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBenti NE, Woldegiyorgis TA, Geffe CA, Gurmesa GS, Chaka MD, Mekonnen YS (2023) Overview of geothermal resources utilization in Ethiopia: potentials, opportunities, and challenges. 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Energy 93:466\u0026ndash;483. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.energy.2015.09.0475\u003c/span\u003e\u003cspan address=\"10.1016/j.energy.2015.09.0475\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"geomechanics-and-geophysics-for-geo-energy-and-geo-resources","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gggg","sideBox":"Learn more about [Geomechanics and Geophysics for Geo-Energy and Geo-Resources](http://link.springer.com/journal/40948)","snPcode":"40948","submissionUrl":"https://submission.nature.com/new-submission/40948/3","title":"Geomechanics and Geophysics for Geo-Energy and Geo-Resources","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Seismic Frequency Resonance (SFRE), fault-controlled geothermal system, Guantao Formation, drilling target selection","lastPublishedDoi":"10.21203/rs.3.rs-7500830/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7500830/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSeismic Frequency Resonance Exploration (SFRE) was deployed along two 980-m profiles (L1, L2) in the Linyi South sector of the Jiyang Depression to evaluate its capability for delineating targets in a fault-controlled geothermal reservoir. Continuous ambient-noise data were processed using frequency-domain stacking, active\u0026ndash;passive spectral matching, and resonance-based apparent-impedance inversion, yielding images to ~\u0026thinsp;2 km depth. The sections consistently resolve four stratigraphic units and the southwest-dipping Fault F1; pronounced impedance reductions within the fault damage zone indicate intense fracturing and enhanced permeability. Within the Guantao Formation, SFRE reveals two zones of elevated geothermal prospectivity at intersections with F1, implying structural connectivity with underlying Cambrian\u0026ndash;Ordovician carbonates and sustained recharge. On this basis, two borehole locations are proposed\u0026mdash;ZK1 (~\u0026thinsp;1600 m) and ZK2 (~\u0026thinsp;1650 m)\u0026mdash;with expected wellhead temperatures of 55\u0026ndash;65\u0026deg;C. Cross-line agreement between L1 and L2 demonstrates method robustness under strong cultural noise and complex near-surface conditions. Remaining uncertainties primarily reflect sensitivity to shallow heterogeneity and the current two-dimensional acquisition geometry, which motivate denser profiling and multi-method joint inversion. Overall, the results establish SFRE as a fast, source-free, and noise-resilient approach for prioritizing drilling targets and characterizing reservoir\u0026ndash;fault interactions in fault-controlled geothermal systems.\u003c/p\u003e","manuscriptTitle":"Seismic Frequency Resonance for Geothermal Targeting in a Fault-Controlled Reservoir","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 05:35:18","doi":"10.21203/rs.3.rs-7500830/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-11T14:18:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"266024769948056578681666452152970994671","date":"2026-04-13T16:26:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"328839177663318543304355480499672679896","date":"2026-01-12T12:03:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-06T18:20:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-13T21:16:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-17T00:41:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Geomechanics and Geophysics for Geo-Energy and Geo-Resources","date":"2025-08-31T13:18:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"geomechanics-and-geophysics-for-geo-energy-and-geo-resources","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gggg","sideBox":"Learn more about [Geomechanics and Geophysics for Geo-Energy and Geo-Resources](http://link.springer.com/journal/40948)","snPcode":"40948","submissionUrl":"https://submission.nature.com/new-submission/40948/3","title":"Geomechanics and Geophysics for Geo-Energy and Geo-Resources","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"97d7bfe7-12f0-4d03-b669-245fa10dfd4a","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-11T14:18:41+00:00","index":25,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T05:35:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 05:35:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7500830","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7500830","identity":"rs-7500830","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}