Controls on hydrocarbon accumulation in ultra-deep carbonate reservoirs of the Ordovician Yingshan Formation, Catake Uplift, Tarim Basin.

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Learn more: PMC Disclaimer | PMC Copyright Notice Sci Rep . 2026 Mar 27;16:10932. doi: 10.1038/s41598-026-44873-y Search in PMC Search in PubMed View in NLM Catalog Add to search Controls on hydrocarbon accumulation in ultra-deep carbonate reservoirs of the Ordovician Yingshan Formation, Catake Uplift, Tarim Basin Lingda Wang Lingda Wang 1 College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083 China Find articles by Lingda Wang 1 , Ruizhao Yang Ruizhao Yang 1 College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083 China Find articles by Ruizhao Yang 1, ✉ , Feng Geng Feng Geng 1 College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083 China 2 Petroleum Exploration and Production Research Institute of Northwest Oilfield Company Sinopec, Urumqi, 830011 China Find articles by Feng Geng 1, 2 , Zhongzheng Jiang Zhongzheng Jiang 2 Petroleum Exploration and Production Research Institute of Northwest Oilfield Company Sinopec, Urumqi, 830011 China Find articles by Zhongzheng Jiang 2 , Hao Zhang Hao Zhang 1 College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083 China Find articles by Hao Zhang 1 , Qingquan Zhang Qingquan Zhang 1 College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083 China Find articles by Qingquan Zhang 1 Author information Article notes Copyright and License information 1 College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083 China 2 Petroleum Exploration and Production Research Institute of Northwest Oilfield Company Sinopec, Urumqi, 830011 China ✉ Corresponding author. Received 2025 Dec 8; Accepted 2026 Mar 16; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13039788  PMID: 41896668 Abstract Ultra-deep carbonate hydrocarbon reservoirs represent a key target for hydrocarbon exploration in the Tarim Basin. Characterized by great burial depth and strong reservoir heterogeneity, they pose significant challenges to reservoir prediction and the understanding of hydrocarbon accumulation mechanisms. Taking the Ordovician Yingshan Formation in the Catake depression of the Tarim Basin as a case study, this paper systematically analyzes the main controlling factors and hydrocarbon accumulation models of such reservoirs based on seismic, logging, and core data. The results indicate that the Yingshan Formation reservoirs generally exhibit low porosity and low permeability, and their reservoir effectiveness is mainly controlled by multi-stage tectonic-karstification processes. The reservoir types are dominated by dissolution pores, vugs, and structural fractures. The NE-trending strike-slip faults in the study area serve as critical migration pathways, connecting deep Cambrian source rocks and governing the hydrocarbon accumulation process featuring “multi-stage charging and late-stage accumulation”. Through a systematic comparative analysis of existing drilling data, it is concluded that three core conditions are essential for encountering high-quality hydrocarbon reservoirs: an effective oil-source fault migration system, well-developed high-quality fracture-vug reservoir bodies, and favorable structural conditions, all of which are considered essential. Subsequent drilling results support this interpretation. This study provides useful insights and practical value for the precise exploration of similar ultradeep and complex carbonate hydrocarbon reservoirs. Keywords: ​​ Ultra-deep carbonate reservoir, Strike-slip fault, Reservoir controlling factor, Dry well analysis, Hydrocarbon accumulation model Subject terms: Energy science and technology, Solid Earth sciences Introduction The global oil and gas industry has been undergoing a strategic shift from conventional to unconventional resources and from middle-shallow to ultra-deep formations 1 – 5 . Marine carbonate reservoirs, a core frontier in ultra-deep hydrocarbon exploration, have been widely identified across large basins worldwide, showcasing immense resource potential 6 – 9 . As one of the world’s largest superimposed basins, China’s Tarim Basin has seen ultra-deep carbonate hydrocarbon exploration emerge as a significant contributor to national energy security, underscoring its prominent strategic role 10 , 11 . Billion-ton-class super-large oil and gas fields (e.g., Tahe, Shunbei, Fuman) have been successively discovered in the Ordovician carbonate formations of the Tabei Uplift and Catake Uplift (Tazhong Uplift) within the basin in recent years 12 – 14 . These breakthroughs not only confirmed the region’s exceptional hydrocarbon abundance and reshaped China’s oil and gas resource distribution but also posed significant challenges to traditional petroleum geological theories and exploration techniques—attributed to the reservoirs’ unique traits, including great burial depth, prolonged formation-evolution history, and complex, variable reservoir spaces. Thus, systematically unraveling the formation mechanisms of ultra-deep carbonate reservoirs and hydrocarbon enrichment laws has become an important frontier in international petroleum geology, as well as a critical technical need to drive ultra-deep exploration progress 15 – 17 . The effectiveness of ultra-deep carbonate reservoirs forms the material basis for hydrocarbon accumulation, with core features marked by strong heterogeneity and the dominance of secondary pores 18 , 19 . Unlike traditional primary pore reservoirs, high-quality reservoir spaces in the Tarim Basin’s Ordovician almost entirely depend on secondary dissolution pore-vug-fracture systems formed via multi-stage tectonic-karst processes. This system arose from the superposition of long geological processes: from Caledonian epikarst and Hercynian burial karst 20 , 21 to Himalayan deep burial adjustment, it has undergone multi-stage, multi-type fluid transformation 22 , 23 , coupled with tectonic movements, hydrocarbon charging, hydrothermal activity, and diagenetic evolution. Ultimately, this results in complex hydrocarbon distribution and diverse diagenetic mineral assemblages. This unique geological context makes the Tazhong area an a representative site to integrate structural analysis with petrological and mineralogical data, offering a valuable opportunity to explore strike-slip fault-controlled carbonate reservoir tectono-diagenesis and clarify its impact on structural evolution and hydrocarbon accumulation 24 – 28 . Among geological factors governing hydrocarbon migration, accumulation, and preservation, faults and fault zones play a pivotal role: they act as both preferential hydrocarbon migration pathways and fluid flow barriers. By regulating episodic paleofluid migration, they exert a decisive influence on large-scale hydrocarbon accumulation—an effect particularly pronounced in ultra-deep carbonate reservoirs 29 – 32 . As a key fault type, strike-slip fault systems exert even more prominent control over hydrocarbon accumulation. Recent discoveries of Tarim Basin hydrocarbon reservoirs are closely linked to strike-slip faults 33 – 35 , and these faults’ complex 3D structures directly govern hydrocarbon migration paths and accumulation processes 36 – 38 . Regionally, the Tarim Basin has undergone polycyclic tectonic evolution since the Neoproterozoic, developing a multi-stage, multi-directional strike-slip fault system 39 – 41 . NE-trending and NW-trending conjugate strike-slip faults serve as critical channels for upward migration of hydrocarbons from deep Cambrian source rocks to overlying Ordovician reservoirs. Beyond providing preferential fluid pathways, fractures generated by fault activity significantly enhance surrounding rock permeability, creating favorable conditions for karst fluid circulation and reservoir space expansion 37 , 42 – 44 . Additionally, strike-slip faults exhibit multi-stage and inherited activity: Caledonian-formed faults were reactivated during the Hercynian and Himalayan, with dual effects—facilitating continuous hydrocarbon migration and effective pathway formation, while also adjusting or destroying early reservoirs 36 , 45 – 47 . Quantitatively characterizing fault system geometry, kinematics, and multi-stage activity history is therefore essential to accurately understanding dynamic hydrocarbon accumulation. Current research on ultra-deep Ordovician carbonate reservoir prediction in the Tazhong area has achieved phased progress: scholars have established preliminary correlations between fault activity and fracture-vug development via rock mechanics experiments, fluid inclusion analysis, and 3D seismic attribute interpretation 43 , 48 . However, gaps remain: (1) the dynamic coupling between strike-slip fault activity stages and fracture-vug reservoir evolution is poorly characterized, hindering quantification of fault activation intensity’s control on dissolution; (2) ultra-deep reservoir prediction focuses on single scales (e.g., micro-pores or macro-faults), lacking integrated characterization of “fault-fracture-pore-vug” multi-scale connectivity, which limits accurate assessment of overall reservoir effectiveness 49 , 50 . To address these gaps, this study targets ultra-deep Ordovician carbonate reservoirs in the Catake Uplift, integrating fault development, reservoir characteristics, and production data from 5 oil/gas-producing wells, 4 dry wells, and 5 water wells. It emphasizes analyzing key controls on successful well reservoir development and limiting factors for dry wells. Starting from the coupling of fault systems, karst transformation, and structural settings, this work analyzes the control mechanisms of ultra-deep reservoir efficiency and proposes a conceptual hydrocarbon accumulation model—providing scientific guidance for optimizing subsequent exploration deployment and target selection. Geologic setting The Tarim Basin—the largest intracratonic basin in northwestern China—covers ~ 582,400 km² (Fig. 1 a), bordered by the Tianshan Fold Belt (north), West Kunlun Tectonic Belt (southwest), and East Kunlun Fold Belt (southeast) 42 . It has experienced multiple tectonic phases, developing unconformable faults influenced by Paleozoic-Mesozoic Proto-Tethys/South Tianshan Ocean opening-closing and Cenozoic Eurasian-Indian plate collision 51 – 55 . The Catake Uplift—a hydrocarbon-producing inherited paleo-uplift in the basin’s center (area ~ 230 km²)—had intense early faulting on its north/south sides (weaker in the center). During the Middle-Late Ordovician, Proto-Tethys Ocean subduction-closure 56 triggered intense magmatism and block compression-uplift, forming NW-trending paleo-uplifts in the uplift’s center 57 , plus NW-SE/NE-SW compressive faults and NE-SW strike-slip faults. Fig. 1. Open in a new tab (a) Location of the Tarim Basin in Northwest China (map of China sourced from the Standard Map Service of the Ministry of Natural Resources, China, available at http://bzdt.ch.mnr.gov.cn/browse.html?picId=%224o28b0625501ad13015501ad2bfc0428%22 ). (b) Geographic location of the Tazhong (Central) Uplift within the Tarim Basin. (c) Geographic location map of the study area. (d) Structure map of the Top Yingshan Formation (Ordovician) in the study area. Subfigures (b) and (c) are based on unpublished internal data of the Petroleum Exploration and Production Research Institute of Northwest Oilfield Company Sinopec CN (used with permission; see attached permission letter). Subfigures (b) , (c) , and (d) were created using CorelDRAW Graphics Suite 2021 ( https://www.coreldraw.com/en/ ) and Petrel 2022.1 ( https://www.slb.com/zh-cn/products-and-services/delivering-digital-at-scale/software/petrel-subsurface-software ). The study area lies in the Catake Uplift’s southwest, adjacent to the Tazhong No. 2 Fault Zone (Fig. 1 c and d) and co-controlled by the No. 1 and No. 2 Fault Zones, with dominant NE-trending strike-slip faults. Comprehensive stratigraphy (Fig. 2 ) shows the Ordovician System (bottom-to-top: Penglaiba, Yingshan (O₂y), Yijianfang, Qiaerbake, Lianglitage, Sangtamu Formations)—denudation of the Yijianfang/Qiaerbake Formations creates an unconformity between the Yingshan and overlying Lianglitage Formations. Formed in a carbonate platform setting, the Ordovician is divided into three second-order sequences: Lower Ordovician Penglaiba, Lower-Middle Ordovician Yingshan, and Upper Ordovician Tumuxiuke/Sangtamu Formations. Middle-Late Ordovician uplift denuded most Yijianfang/Tumuxiuke strata 58 . Fig. 2. Open in a new tab Composite Stratigraphic Column of the Study Area. This study focuses on the Middle Ordovician Yingshan Formation—dominated by open platform/platform margin facies micritic limestone, wackestone, packstone, and dolomite 27 . The Lianglitage Formation (micritic limestone, packstone, grainstone, bioclastic limestone, reef limestone) is controlled by open platform/intra-platform tidal flat/lagoon facies; its stable ~ 150 m thickness makes it a high-quality cap rock 59 . The Sangtamu Formation, a regional cap rock, consists mainly of clastic mudstone and sandstone 60 . Debate over Catake Uplift source rocks (Ordovician 61 – 63 vs. Lower Cambrian 64 , 65 has been resolved: more evidence confirms Lower Cambrian origins, with no high-quality Ordovician source rocks found in the uplift or adjacent depressions 66 – 68 . Recent exploration shows carbonate matrix reservoirs (porosity < 5%, permeability < 0.5 mD) lack industrial productivity, while large “beaded” seismic reflection fracture-vug reservoirs have ultra-high productivity 69 , 70 . Seismic profiles reveal multiple strike-slip fault sets (most cutting Cambrian-Ordovician, with intra-Ordovician faults), and fault-associated karst caves show strong “beaded” seismic reflections—this study focuses on these fault-karst cave systems. Data and methods This study utilizes a 3D seismic dataset and drilling data. The seismic data covers an area of approximately 417 km², presenting as a regular 3D seismic volume with a line spacing of 25 m, a sampling interval of 2 ms, an effective bandwidth of 5–60 Hz, and a dominant frequency of about 25 Hz. The drilling data includes conventional logging data, FMI (Formation MicroImager) fracture imaging data, core photos, and cast thin-section identification results from 15 wells in the study area. All data underwent strict quality control before use, with preprocessing including environmental correction and data standardization. Data availability The 3D seismic dataset used in this study was provided by the Research Institute of Exploration and Development of Sinopec Northwest Oilfield Company under a data-sharing agreement for this collaborative project. The drilling data (including well logs and core descriptions) are from the same source. Due to confidentiality agreements, the raw data are not publicly available, but processed data supporting the findings are available from the corresponding author upon reasonable request and with permission of the data owner. The research methods mainly include two parts: fault prediction and karst cave prediction (Fig. 3 a). For fault prediction, a multi-azimuth amplitude contrast fusion ant-tracking technique was adopted 71 – 73 . This method first decomposes the seismic discontinuity attribute volume within the range of 0–180° by azimuth, then selects the appropriate azimuth data volume for fusion. Previous studies on the stress state of the study area have indicated that the main stress direction is predominantly NE(Fig. 3 f 3 g) 42 , 74 , 75 . Combined with the nature of the current data volume, it is necessary to select the discontinuity data volume within the azimuth range of 70–120° for fusion (Fig. 3 h), based on which ant-tracking is performed. Comparison with traditional ant-tracking results (Fig. 3 e) shows that this method can effectively suppress false faults caused by poor seismic signal quality, and the obtained fault distribution is more regular and consistent with actual geological characteristics. Fig. 3. Open in a new tab (a) Technical workflow of the study; (b) Amplitude gradient calculation results along two directions and the final cave characterization attribute result; (c) Schematic diagram of amplitude gradient calculation; (d) Schematic diagram of statistical variance; (e) Comparison between the ant-tracking results computed by the method in this study and conventional ant-tracking results; (f) - (g) Calculation results of amplitude comparison at azimuth angles of 10° and 100°; (h) Amplitude comparison calculation using the preferred azimuth. For karst cave prediction, a parallelism variance attribute integrating spatial gradient changes of amplitude was employed(Fig. 3 c 3 d). Figure 3 c shows the characteristic vector of coherent amplitude v(x, y) based on a 9-trace analysis window, where and represent the gradient changes of coherent amplitude in the horizontal and vertical directions, respectively. To reduce the impact of acquisition footprints, referring to the method proposed by Marfurt (2006) 76 , instead of directly differentiating along the x and y directions, a smoother differential operator was adopted to construct an average absolute amplitude spatial change rate attribute based on dip scanning, which fuses the weighted energy coherent amplitude gradient. Its mathematical expression is as follows: This attribute is ultimately used to characterize the development law of “beaded” reflections in the study area (Fig. 3 b). The prediction results are in good agreement with drilling and seismic response characteristics, especially in the W7 well area, so it is used to systematically describe the spatial distribution characteristics of karst caves. Results Reservoir characteristics Drilling in the study area reveals that the Yingshan Formation consists of carbonate rocks, divided into upper and lower members (Fig. 4 a). The lithology of the Yingshan Formation is dominated by dolomite, followed by micritic limestone. The dolomite grains are granular euhedral-subhedral crystals with an interlocking granular texture. Pore types include intercrystalline dissolution pores, karst caves, fractures, and microfractures. Thin-section identification confirms the presence of intercrystalline dissolution pores, intragranular dissolution pores, and microfractures (Figs. 4 b ~ e). Imaging logging data indicates that reservoir spaces are dominated by dissolution pores, vugs, and fractures. The dissolution vugs are relatively large with uniform pore diameters within the same interval, distributed in honeycomb, bedded, and scattered patterns. Local vugs develop along fracture edges, leading to fracture dissolution and expansion. Fractures are mainly medium to high-angle fractures (Figs. 4 h, i). Based on the above results, the Yingshan Formation reservoirs in the study area can be classified into two types: fracture-vuggy reservoirs and vuggy reservoirs (Figs. 4 f, g). To further analyze the main controlling factors for the development of high-quality reservoirs in the Yingshan Formation, this study collected porosity and permeability experimental data from 117 core samples of key intervals in Wells W1, W4, W10, and W13 (Table 1 ), and systematically discussed the controlling effects of lithofacies, diagenesis, and fractures on the development of secondary pores by integrating observations from 36 cast thin-sections. Based on the statistical distribution of porosity and permeability data from core samples, this study defines reservoirs with porosity > 3% and permeability > 0.1 × 10⁻³ µm² as high-quality reservoirs. Fig. 4. Open in a new tab Characterization of Fracture-Vuggy Reservoirs in the Yingshan Formation (a) Composite Columnar Chart of Well W10; (b) Well W1, 5523.65 m: Fine-crystalline dolomite with intercrystalline and intercrystalline dissolution pores; (c) Well W3, 5552.51 m: Powder-crystalline dolomite with intercrystalline dissolution pores; (d) Well W6, 5566.34 m: Sparry calcarenite containing dolomitic limestone, with developed microfractures (width 0.01–0.03 mm) and asphalt-filled suture seams; (e) Well W6, 5537.1 m: Fine-crystalline dolomite with intercrystalline pores, intercrystalline dissolution pores, and fractures (width 0.02–0.10 mm); (f) Fracture-Vuggy Reservoir; (g) Vuggy Reservoir; (h) Well W10, 5380 m: Drill core showing significant dissolution vugs; (i) FMI (Formation MicroImager) log of Well W10, showing numerous dissolution vugs and high-angle fractures. Table 1. Porosity and permeability statistics of the Yingshan Formation in the study area based on core sample analysis. Well Number of samples Porosity/% Number of samples Permeability/(10 −3 µm 2 ) Lithofacies Facies Well 1 60 0.3–7.4 46 0.02–13.3 Fine-crystalline dolomite Interior shoal Well 4 21 0.8–6.7 18 0.02–0.65 Micritice Limestone Marginal shoal Well 10 20 2.1–7.4 20 0.02–8.15 Grainstone Marginal shoal Well 13 16 0.2–2.2 10 0.02–9.15 Grainstone Local platform Open in a new tab Lithofacies serve as the fundamental condition for the development of high-quality reservoirs. Thin-section observations show that grain limestone and platform margin shoal facies fine-crystalline dolomite are the most favorable reservoir lithofacies. A large number of intergranular and intragranular dissolution pores are developed in the grain limestone of the upper Yingshan Formation in Well W10 (Fig. 4 b), with porosity generally greater than 5% and a maximum permeability of 13.3 × 10⁻³ µm². In contrast, although the restricted platform facies micritic limestone in Well W13 has undergone multiple stages of dissolution, the development of dissolution pores is limited due to its dense original structure, with porosity mostly below 2%. Diagenesis exerts a decisive influence on reservoir quality. The Yingshan Formation in the study area has experienced multiple stages of diagenetic modification, among which supergene karstification and burial dissolution are the key factors for the formation of high-quality reservoirs. Supergene karstification is mainly associated with the Middle Caledonian and Mid-Caledonian unconformity surfaces. A typical weathered crust karst system is developed at the top of the Yingshan Formation in Well W10, with dense distribution of karst caves and dissolution fractures (Fig. 4 h). The dissolution porosity is 2–3% higher on average than that of the lower intervals. Dissolution preferentially develops along early tectonic fractures, forming a complex fracture-vug system. Burial dissolution plays an important role in the development of deep reservoirs. Acidic fluids generated by the thermal evolution of organic matter migrate along fault systems and selectively dissolve the carbonate rocks of the Yingshan Formation. Fluid inclusion analysis shows a good correlation between hydrocarbon charging and dissolution, which mainly occurred during the Late Hercynian and Himalayan periods. The fracture system not only provides pathways for hydrocarbon migration but also significantly improves reservoir permeability. Statistical data indicate that the permeability of fracture-developed samples is 1–2 orders of magnitude higher than that of unfractured matrix. High-angle tectonic fractures in the Yingshan Formation of Well W10 are interconnected with dissolution pores, forming an effective reservoir-seepage system (Fig. 4 i), with an average permeability of 1.151 × 10⁻³ µm², much higher than the regional background value. Fracture development is controlled by the intensity of strike-slip fault activity. The fracture density near the NE-trending strike-slip fault zones increases significantly, providing preferential migration pathways for later dissolution fluids, thereby controlling the zonal distribution characteristics of high-quality reservoirs. Based on the above results, the Yingshan Formation reservoirs in the study area can be divided into two types: fracture-vuggy reservoirs and vuggy reservoirs (Figs. 4 f, g). Statistics on the physical property data of the Yingshan Formation from a total of 4 wells in the study area (Table 1 ) show that the porosity ranges from 0.2% to 7.4%; the permeability ranges from 0.02 × 10 ⁻³ to 13.3 × 10⁻³ µm². This indicates that the Yingshan Formation in this area is characterized by generally low porosity and permeability. However, local intervals exhibit improved reservoir properties, which are typically associated with the development of fractures and dissolution pores/vugs. Reservoir and seal characteristics In the Catake paleo-uplift area, the Yingshan Formation reservoirs exhibit significant vertical zonation characteristics, and their good regional continuity has been confirmed by inter-well correlation (Fig. 5 ). Vertically, the reservoir system can be clearly divided into two main units: the upper unit is a weathered crust fracture-vuggy reservoir, mainly developed below the regional unconformity surface, significantly controlled by Caledonian paleokarstification. This interval is extensively developed with dissolution pores, vugs, and fracture systems, forming reservoir spaces dominated by large karst caves and structural fractures. The middle-lower unit is mainly composed of bedded vuggy dolomite reservoirs, whose development is obviously controlled by high-frequency sea-level cycles. Taking Wells W10 and W3 as examples, bedded vuggy layers mostly appear at the top of upward-shallowing cycles, with lithology dominated by medium-fine crystalline dolomite. Pore types are characterized by intercrystalline pores, intercrystalline dissolution pores, and bedded dissolution vugs (as shown in the photomicrographs, e.g., Figs. 4 b–e), showing typical penecontemporaneous dolomitization genetic characteristics. Fig. 5. Open in a new tab Cross-well correlation profile showing the vertical reservoir zonation and inter-well continuity of the Yingshan Formation (Ordovician) in the study area. The overlying Lianglitage Formation, with its tight carbonate lithology, stable regional distribution, and direct contact with the underlying reservoirs, constitutes an important regional cap rock in the study area. This cap rock has a large single-layer thickness, and logging curves such as GR (Gamma Ray), AC (Acoustic Transit Time), and DEN (Density) show low and stable characteristics, reflecting that it was formed in a stable sedimentary environment with suggesting good sealing capacity, providing superior sealing conditions for hydrocarbon preservation. Fault prediction and hydrocarbon charging Studies indicate hydrocarbon accumulation in this area follows a “multi-stage charging, late-stage adjustment” model, with its evolution closely linked to regional tectonic activity 57 , 77 – 79 . As shown in the homogenization temperature histogram of fluid inclusions from Well W10 (Fig. 6 b), the hydrocarbon-bearing aqueous inclusions exhibit a main peak in the range of 90–110 °C, indicating a major hydrocarbon charging event corresponding to the Late Hercynian Period, as constrained by the burial‑thermal evolution history (Fig. 6 a). The oil inclusions show a broader temperature distribution spanning 70–130 °C, with a subordinate/secondary peak at 120–130 °C, reflecting continuous multi‑stage hydrocarbon charging that includes early crude oil emplacement and later high‑temperature adjustment, corresponding to the Himalayan period in the thermal evolution model.Combined with hydrocarbon generation evolution (Fig. 6 c) and prior studies 57 , 66 , 70 , 80 , reservoirs here underwent initial accumulation (Early Hercynian), adjustment/destruction (Late Hercynian), and finalization (Himalayan)—essentially driven by early large-scale accumulation, middle-term continuous charging, and late tectonic adjustment. Fig. 6. Open in a new tab Hydrocarbon Generation Evolution in the Study Area. (a) Stratigraphic Burial–Thermal Evolution History of Well W10; (b) Homogenization Temperature Distribution Histogram of Fluid Inclusions from Well W10; (c) Ordovician Hydrocarbon Accumulation Evolution Diagram of the Study Area; (d) Inclusions in dissolution pore-filling calcite; (e) ​Hydrocarbon inclusions in dissolution pore-filling calcite. Based on the analysis of fluid inclusion homogenization temperatures, stratigraphic burial-thermal evolution history, and hydrocarbon generation history, and within the chronological framework established by Table 2 (Temporal correlation of tectonic events, hydrocarbon generation peaks, and charging stages in the study area), the hydrocarbon accumulation in the Yingshan Formation of the Catake Uplift is interpreted to have undergone three key stages: The Caledonian period was primarily a reservoir space construction period, where supergene karst processes laid the material foundation for subsequent hydrocarbon accumulation. The Late Hercynian period was mainly a hydrocarbon adjustment period, characterized by early accumulation in lithologic-stratigraphic traps on paleo-uplifts, which may have been subsequently adjusted or destroyed by later tectonic movements. The Himalayan period represents the critical accumulation period, during which the structural framework was finalized, and deep-large faults provided the primary vertical migration pathways for hydrocarbons, culminating in accumulation in late-stage structural traps. Table 2. Timing of Tectonic Events, Hydrocarbon Generation Peaks, and Charging Stages. Geological Period Major Tectonic Events Peak Hydrocarbon Generation Fluid Charging Stage Himalayan​ Intense compression-uplift; intense fault activity Main Hydrocarbon Generation Peak​ Late-Stage Charging Late Hercynian​ Regional compression; large-scale strike-slip fault formation Initial Hydrocarbon Generation Early Charging​ Caledonian​ Regional uplift and erosion; development of unconformity at the top of the Yingshan Fm. Constructive Diagenesis​ Open in a new tab Faults serve as the primary vertical pathways connecting the deep Cambrian source rocks to the Yingshan Formation reservoirs: fault activity creates near-fault fracture zones (preferential fluid channels) and pressure-release “windows” (driving deep-to-shallow fluid flow due to pressure differences). Most local traps in the Catake Uplift align with fault zones (their formation linked to faulting), as faults channel deep oil to overlying traps—making fault prediction critical 81 , 82 . This study used multi-azimuth amplitude contrast fusion ant-tracking for fault prediction (Fig. 7 ). Results include: fault distribution at the Yingshan Formation top (Fig. 7 a), Cambrian salt-penetrating (source-connecting) fault predictions (Fig. 7 b), and fracture trend rose diagrams for the Yingshan Formation in each well (Figs. 7 c–h). Consistency between predictions and drilling-derived rose diagrams confirms the method’s reliability. Fig. 7. Open in a new tab Fault Prediction Results Using Ant-Tracking Technique​; (a) Predicted faults at the top Yingshan Formation interface; (b) Predicted salt-penetrating faults. (source-rock-connecting faults) in the Cambrian System; (c)-(h) Fracture rose diagrams statistically analyzed from FMI logs of individual wells in the Yingshan Formation. Fault predictions reveal dominant NE-trending strike-slip faults. Regionally, the Cambrian salt-penetrating fault system is dense, extensive, and NE/NW-oriented (likely controlled by Early Paleozoic basement fault reactivation); Yingshan Formation top faults are sparser but regular (tied to Caledonian tectonic-karst superposition). Reactivated in the Himalayan Period, this fault system became a key channel for deep Cambrian-sourced hydrocarbons to migrate upward to the overlying Yingshan Formation reservoirs. 3D geological modeling 3D geological modeling of the study area was conducted using prior stratigraphic structural maps, fault prediction results, and karst cave prediction data (Fig. 8 ). The linear discontinuities represented as ‘fractures’ in this 3D model are primarily derived from the seismic ant-tracking attribute volume. Given the resolution limits of the seismic data, these features more accurately represent seismic-scale minor faults, fault traces, or fault-related fracture zones rather than individual, sub-seismic-scale fractures. They are included to illustrate the distribution and connectivity of the fault-fracture network that controls fluid migration and reservoir heterogeneity. Combined with regional tectonic evolution analysis, Early Caledonian faults—confined to Lower Cambrian strata—form an intra-source rock fault system, while Late Caledonian strike-slip faults penetrate the Cambrian-Ordovician System, creating an interlayer fault system between source rocks and overlying reservoirs. The effective alignment of these two fault types provides key channels for hydrocarbon migration. Fig. 8. Open in a new tab 3D Geological Modeling of the Study Area Integrating Structural, Fault, and Karst Cave Prediction Results. Efficient hydrocarbon migration paths form when Yingshan Formation top faults connect with Cambrian internal faults; in contrast, Cambrian faults that fail to extend to the Yingshan Formation (only cutting its lower member) show significantly reduced migration efficiency. Karst cave predictions further reveal high consistency between cave development areas and strike-slip fault distribution—indicating caves mostly develop along fault zones. Hydrocarbons migrate upward via Cambrian salt-penetrating (source-connecting) faults and accumulate in Yingshan Formation karst cave reservoirs. 3D geological modeling intuitively displays the spatial distribution of the Yingshan Formation’s structure, fractures, and karst caves, while clearly revealing the configuration of the fault-karst cave system—providing a reliable geological model for in-depth analysis of hydrocarbon accumulation laws. Discussion Oil accumulation conditions Drilling and testing in the study area reveal widespread vertical hydrocarbon shows—nearly all wells exhibit oil stains or patches within the Yingshan Formation, indicating regional hydrocarbon fluid distribution. However, after fracturing and oil testing, most wells yield no industrial oil/gas (showing low-yield dry or water-producing layers), with only a few achieving high yields and production 61 , 83 . Efficiently identifying large-scale high-quality reservoirs is thus critical for local hydrocarbon exploration 84 . Analysis of regional structure and hydrocarbon distribution (Fig. 9 a) shows high-yield wells in adjacent northern blocks are clearly fault-controlled, mostly distributed along main faults—confirming fault zones, as preferential migration channels, play a key role in hydrocarbon accumulation 85 – 87 . To further explore fluid properties and charging characteristics, light hydrocarbon samples (cuttings gas, headspace gas) from the study area and adjacent wells were collected, and a light hydrocarbon composition discrimination chart (double logarithmic coordinates, Fig. 9 b) was generated. The horizontal WH index represents the wetness ratio (reflecting the relative abundance of C₂–C₅ hydrocarbons), while the vertical BH index represents the balance ratio (reflecting the proportion between lighter and heavier hydrocarbons) Projections show study area samples and northern high-yield well samples cluster in similar areas, with analogous light hydrocarbon composition and evolution—indicating same-source charging and similar migration/differentiation processes. Fig. 9. Open in a new tab (a) Structural map showing fault distribution and well productivity; (b) Wetness ratio (WH) and balance ratio (BH) discrimination diagram showing fluid type classification.​. It is inferred hydrocarbon charging in the study area mainly occurs via vertical fault migration, showing a “north-strong, south-weak” pattern. The study area lies at the distal end of hydrocarbon migration paths, with underdeveloped faults. Prior karst cave predictions note cave development is tied to strike-slip faults, so weak faulting means poor cave reservoir development. Additionally, the study area has a gentle structure with no obvious local traps, lacking effective accumulation conditions. In summary, despite several main strike-slip faults, the area is disadvantaged in hydrocarbon charging intensity and reservoir-trap conditions—leading to multiple well failures and no large-scale production breakthroughs. Analysis of the causes of the failure of the dry well The four dry wells in the study area can be categorized into two types based on their structural position, fault connectivity, and reservoir-space development. The first type includes Wells W1 and W5 (Fig. 10 c and d) are structurally situated near main fault zones(see their distribution relative to fault zones in Fig. 7 )—locations that are typically within preferential migration pathways, implying potentially favorable conditions for hydrocarbon migration. However, the presence of a fault pathway does not guarantee high productivity, as demonstrated by the outcomes of these wells. During drilling, both wells exhibited obvious gas logging anomalies in target intervals (with significantly increased total hydrocarbon content) and extensive oil-soaked/oil-stained displays in cores, confirming effective hydrocarbon migration. However, neither well achieved industrial productivity post-fracturing stimulation and oil testing, ultimately being classified as dry layers. Comprehensive analysis of drilling, logging, and experimental data points to poor reservoir quality as the primary cause: Well W1’s Yingshan Formation reservoir (Fig. 10 c) has extremely underdeveloped dissolution pores and vugs, alongside a sparse fracture system dominated by closed fractures, resulting in limited and poorly connected reservoir space; Well W5 (Fig. 10 d) consists of light gray dolomitic micritic limestone, with underdeveloped effective dissolution pores and vugs despite a set of high-angle fractures—FMI logs show scattered, discontinuous dissolution pores, and cast thin-section analysis reveals strong cementation with severe calcite and asphalt filling, greatly damaging effective pore space. Despite superior migration conditions, the lack of effective reservoir and seepage space prevented hydrocarbon accumulation. Fig. 10. Open in a new tab Comparative Analysis of Dry Holes and Successful Wells in the Study Area​; (a) Well-logging curves of Well W6 integrated with core description and cast thin-section observations; (b) Well-logging curves of Well W9 integrated with core description and cast thin-section observations; (c) Well-logging curves of Well W1 integrated with core description and FMI (Formation MicroImager) results; (d) Well-logging curves of Well W5 integrated with core description, cast thin-section, and FMI data; s(e) Characterization of the successful Well W10. The second type of dry wells—Wells W6 and W9 (Fig. 10 a and b)—differ distinctly from the first. These wells did not directly intersect source-connecting faults(see their distribution relative to fault zones in Fig. 7 ), featuring relatively poor structural locations, weak hydrocarbon migration conditions, and no typical “beaded” seismic reflections (indicating overall mediocre reservoir development). In terms of reservoir characteristics, Well W6 (Fig. 10 a) has gray dolomitic limestone at the Yingshan Formation top, with relatively developed and unfilled dissolution pores/vugs, microfractures, and intercrystalline pores (cast thin-sections confirm a decent pore structure with certain reservoir capacity), but its low structural position (5530 m depth for the Yingshan Formation reservoir) undermines hydrocarbon accumulation. Well W9 (Fig. 10 b) has local fractures and dissolution pores/vugs in the Yingshan Formation, though severely filled—minor crude oil seepage during core retrieval confirms past hydrocarbon entry. Cast thin-section observations reveal that the majority of pores are filled by argillaceous material and asphalt, resulting in low visual porosity and significantly reducing reservoir effectiveness. This poor reservoir quality is in stark contrast to the well-developed pore systems documented in successful wells like W10 (see Sect. 4.1 ). Despite a relatively high structural position, the lack of effective hydrocarbon migration channels prevented hydrocarbon delivery to traps, leading to failure. For comparative analysis, Well W10 (Fig. 10 e)—a successful, stable-production well in the study area—serves as a typical example. Structurally, it lies in the main fault zone, with well-developed fault systems providing efficient hydrocarbon migration channels(see their distribution relative to fault zones in Fig. 7 ); it also occupies a high structural position, favoring hydrocarbon accumulation. More critically, its Yingshan Formation reservoir is exceptionally well-developed: core observations reveal dense, unfilled dissolution pores and vugs, cast thin-sections confirm well-developed intercrystalline dissolution pores. Combined with core analysis data that shows high porosity (up to 7.4%, Table 1 ),​ and FMI logs which show high-angle fractures coexisting with dissolution pores/vugs, they collectively form a robust reservoir-seepage system. Comparative analysis of the four dry wells and one successful well reveals that ultra-deep carbonate hydrocarbon accumulation is governed by a “triple coupling” mechanism: an effective migration system (relying on source-connected faults) is the prerequisite, high-quality reservoir space is the foundation, and a favorable structural position is the guarantee. As the key hydrocarbon migration pathway, the fault system must connect effectively with source rocks; reservoir development determines hydrocarbon storage capacity, while structural height controls accumulation. The absence or improper configuration of any of these three elements results in drilling failure, a principle that provides important guidance for hydrocarbon exploration in geologically similar areas. Analysis of the causes of the failure of the water well Five water-producing wells have also been identified in the study area, with drilling flowback water samples showing similar water properties (Table 3 ). These wells are divided into two types based on structural location, fault development, and reservoir characteristics. Table 3. Analysis Results of Returned Water Samples from Well Logging in the Study Area. Well Test layers Water analysis PH Completion method Conclusion CI − (mg/l) TDC(mg/l) Water type W13 5713.6–5730 93,198 152,510 CaCl 2 5.9 completion water layer 5605.4–5621.8.4.8 100,348 166,394 CaCl 2 5.8 completion water layer W8 5542–5559 91024.3 149,386 CaCl 2 6.0 completion water layer 5510.0–5522.0 91224.7 154,947 CaCl 2 5.7 completion water layer W9 5455–5481 102802.16 165673.09 CaCl 2 6 acid fracturing water layer W3 5478–5600 91367.94 148470.87 CaCl 2 5.9 acid fracturing water layer 91998.07 149975.44 CaCl 2 6.2 acid fracturing water layer 97284.73 158659.74 CaCl 2 6.0 acid fracturing water layer 94968.42 154619.66 CaCl 2 6.0 acid fracturing water layer 97705.87 159164.98 CaCl 2 6.1 acid fracturing water layer Open in a new tab The first type includes Wells W7, W8, and W14 (Figs. 11 a–c), all distributed around the high-yield Well W10 but at significantly lower structural positions. Well W8 (Fig. 11 a) has gray oil stains in cores and developed fractures (FMI data), while seismic profiles show the Yingshan Formation’s top burial depth is 5470 m–120 m deeper than Well W10’s 5350 m. Notably, Well W10 has a gas-water zone at 5500 m, indicating Well W8’s position is near or below the oil-water interface; coupled with underdeveloped source-connecting faults (Cambrian intra-source fault superimposed map, Fig. 11 f) and weak hydrocarbon charging, it drilled into a water layer. Well W7 has favorable reservoir conditions (typical seismic “beaded” reflections, well-developed core dissolution pores/vugs, and good fractures via FMI) but lies 76 m deeper than Well W10 (Yingshan Formation top at 5426 m); though a NW-trending fault with limited migration capacity exists, no large-scale structural trap formed, leading to water production. Well W14 (Fig. 11 c) has core dissolution pores/vugs, yet its Yingshan Formation top is 5621 m (195 m deeper than Well W10), and testing confirms the entire interval is a water layer. Fig. 11. Open in a new tab Comprehensive analysis of water-bearing holes (W3, W7, W8, W14, W15) in the study area, integrating well log, core, thin-section, FMI, and seismic data. (a) W8; (b) W7; (c) W14; (d) W3; (e) W15. The second type comprises Wells W3 and W15 (Figs. 11 d–e). Well W3 (Fig. 11 d) has relatively well-developed reservoirs compared to the dry wells—dense core dissolution pores/vugs, unfilled intercrystalline dissolution pores (cast thin-sections), and symbiotic high-angle fractures (FMI)—with physical properties comparable to Well W10. However, underdeveloped Cambrian source-connecting faults in the well area lack effective migration channels, leaving the trap uncharged with hydrocarbons. Well W15 (Fig. 11 e) has seismic “beaded” responses and is adjacent to a southward fault-developed anticlinal belt (with migration potential), but a large water layer was encountered in the Lianglitage Formation, and intermediate testing confirmed the entire well interval is water-bearing. This failure is attributed to its proximity to the structural belt: ineffective lateral sealing may be associated with the migration of hydrocarbons to higher structural positions along faults, rendering the trap invalid. Analysis of these water-producing wells is consistent with the proposed triple coupling mechanism for carbonate hydrocarbon accumulation, with structural height as the critical factor for accumulation and preservation. Low structural positions, even with good reservoirs and local faults, fail to accumulate hydrocarbons (due to being below the oil-water interface or serving as lateral migration zones); high positions also cannot form industrial accumulations without effective migration or quality reservoirs. Exploration must therefore strictly screen sweet spots where “high structural position, developed source-connecting faults, and high-quality reservoirs” synergize, avoiding risks from poor element configuration—an insight that provides a useful reference for similar deep carbonate exploration settings. Recent drilling analysis Based on the success-failure analysis of drilling wells and the planar distribution of unsuccessful wells in the study area (Fig. 12 a), this study establishes a risk prediction model for failed wells based on the coupling of geological elements, dividing the study area into two risk zones: (1) High-risk zones, which mainly include areas near strike-slip fault zones where high-quality reservoirs are underdeveloped, and local structural highs distant from effective oil-source faults. Although these areas possess migration or accumulation potential, the risk of encountering dry intervals or low-productivity hydrocarbon flows is extremely high due to the lack of effective reservoir space or hydrocarbon supply.(2) Low-risk zones, which are areas with a favorable spatial configuration of fault zones, high-quality reservoirs, and late-stage structural traps​ (e.g., the Well W10 area). These zones are favorable targets where hydrocarbon charging is prioritized and the probability of accumulation is significantly higher. Fig. 12. Open in a new tab (a) Planar map of the study area showing the distribution of failed wells and the delineated exploration risk zones superimposed with predictions for source-rock-connecting faults and karst caves; (b) Seismic profile crossing wells W12, W11, and W7, with superimposed fault and fracture zone interpretation and karst cave predictions. The mechanism underlying this risk differentiation essentially reflects the strict dependence of hydrocarbon accumulation on the tripartite coupling of reservoir, migration pathway, and trap. Against the background of generally weak regional hydrocarbon charging intensity, the formation of high-quality hydrocarbon reservoirs must satisfy three key conditions: favorable lithofacies​ provide the material foundation for reservoir development, multi-stage dissolution​ creates effective storage space, and the fracture system​ ensures permeability and provides migration pathways. All three are indispensable; they jointly control the distribution of high-quality reservoirs and the locations of hydrocarbon enrichment. During the accumulation process, the strike-slip fault system acts as the primary vertical migration pathway, transporting hydrocarbons generated from the deep Cambrian source rocks to the Yingshan Formation reservoirs. Industrial hydrocarbon accumulations can only form where the fault system is effectively spatially matched with high-quality reservoirs. The success of Well W10 is precisely attributed to this “fault + high-quality reservoir + high structural position” tripartite coupling. In contrast, although Well W1 is located near a fault zone, it ultimately became a dry layer due to underdeveloped dissolution pores and a predominantly closed fracture system in the reservoir, which conversely confirms the decisive role of reservoir quality. Based on this understanding, the project team deployed and drilled Well W11 in an area satisfying these tripartite coupling conditions (Figs. 12 a, b), successfully discovering a high-yield gas reservoir at the top of the Yingshan Formation. This result not only supports the reliability of the tripartite coupling accumulation model​ but also further s consistent with the effectiveness of the risk prediction model established in this study, providing clear guidance for the next steps in exploration deployment within the study area. Based on the successful experience of Well W11, the project team further deployed Well W12 and drew a cross-well reservoir model diagram of the area (Fig. 13 ). The model diagram believes that Well W12 also has similar favorable conditions to Well W11, and theoretically Well W12 will also be successful. However, in fact, the well failed. Through analysis of logging curves and returned core observations, it is known that the main reason for the failure of this well is the reservoir destruction caused by magmatic intrusion (Fig. 14 a). The strong amplitude “beaded” seismic reflection characteristics at the Yingshan Formation of Well W12 are caused by the intrusion of diabase, not karst caves. Well W7 also encountered magmatic intrusive rocks during drilling, and there are currently two pieces of evidence supporting this understanding: (1) well-log responses characteristic of igneous intrusions (e.g., high resistivity, low velocity), and (2) published petrographic confirmation. Specifically, the work of Yang et al. (2015) 88 , 89 , cited in our study, provides detailed petrographic analysis and conclusively documents that Well W7 drilled through Permian magmatic intrusive rocks. This prior study, combined with our seismic and log interpretations, robustly supports the interpretation of magmatic intrusion at this location, confirming that magmatic intrusion was the cause of reservoir destruction and well failure. Fig. 13. Open in a new tab Theoretical reservoir formation model diagram of wells W11, W12, and W7 in the study area. Fig. 14. Open in a new tab (a) Well logging curves and core/thin-section observations from W12, revealing multiple intervals of magmatic intrusive rocks; (b) Well logging curves of W7, showing magmatic intrusive rocks in the middle-lower part of the Yingshan Formation. The recent drilling practice of two wells further adds support to the broader applicability of the “triple coupling” reservoir control law in this area, that is, the synergistic configuration of effective migration, high-quality reservoirs, and high structural positions is the key to hydrocarbon accumulation. Future exploration should continue to strengthen the comprehensive evaluation of the three elements, and prioritize favorable zones with higher structural positions, reservoirs not damaged by later stages, and more developed source-connecting faults to improve exploration efficiency. Hydrocarbon accumulation model Based on the above well analysis, a hydrocarbon accumulation model of the study area was developed (Fig. 15 a). Combined with comparative studies of failed and successful wells, four typical hydrocarbon migration-accumulation models were further summarized (Figs. 15 b–e), reflecting how the configuration of accumulation elements controls the accumulation process under different geological conditions. Fig. 15. Open in a new tab Models of Hydrocarbon Accumulation and Well Performance​; (a) Hydrocarbon accumulation model for the study area; (b) Dry hole failure model, exemplified by Well W5; (c) Successful well model, exemplified by Well W10; (d) Water-bearing well failure model Type I, exemplified by Well W12; (e) Water-bearing well failure model Type II, exemplified by Well W14. The first is the fault transport-reservoir failure type (Fig. 15 b), represented by Well W5. Its core constraint is the lack of high-quality reservoirs: despite well-developed faults (ensuring good hydrocarbon migration), poor reservoir physical properties and underdeveloped pore-fracture systems prevent effective hydrocarbon accumulation. The second is the triple coupling-successful accumulation type (Fig. 15 c). Its key lies in the synergistic configuration of effective migration, high-quality reservoirs, and high structural positions: the fault-karst cave system forms an efficient migration-storage network, the high structural position favors accumulation, and unconformity surfaces (as lateral migration channels) further enhance hydrocarbon enrichment. The third is the magmatic intrusion-reservoir destruction type (Fig. 15 d), exemplified by Well W12. Later intrusive rock destruction is the main cause—even with favorable migration and structural conditions, reservoir damage from magmatic activity thwarts hydrocarbon accumulation. The fourth is the source-sink mismatch-insufficient charging type (Fig. 15 e), typified by Well W14. It is constrained by two factors: underdeveloped source-connecting faults (leading to weak hydrocarbon charging due to no effective oil-source channels) and low structural positions (prone to being below the oil-water interface), making accumulation difficult. These four models reveal the dynamic configuration of “source-transport-reservoir-accumulation-preservation” elements during accumulation: successful accumulation relies on triple coupling, while failure stems from the lack or improper configuration of key elements (e.g., reservoir properties, structural position, oil-source channels). This insight is crucial for deepening research on ultra-deep carbonate hydrocarbon accumulation laws and optimizing exploration targets. Conclusions This study analyzed 3D seismic volumes and drilling test data of the block, and constructed a 3D geological model using geophysically derived fault and cave prediction results. Key conclusions are as follows: (1) The Yingshan Formation reservoirs in the study area are low-porosity and low-permeability, with effectiveness relying primarily on late-formed secondary storage spaces. They exhibit distinct vertical zonation: the upper section is weathered crust fracture-cavity reservoirs controlled by Middle Caledonian karstification, while the middle-lower section is layered porous dolostone reservoirs influenced by high-frequency sea-level cycles. Storage spaces—dominated by dissolution pores, vugs, and tectonic fractures—often combine into complex fracture-cavity systems. (2) The fault system, especially NE-trending strike-slip faults and their intersections with NW-trending faults, acts as the primary migration pathway connecting deep Cambrian source rocks to overlying Ordovician Yingshan Formation reservoirs. Hydrocarbon accumulation features “multi-phase charging and late-stage finalization”: Himalayan tectonic activity reactivated early faults, turning them into important migration channels for upward adjustment and redistribution of deep hydrocarbons. Effective migration pathways require faults to extend downward into source rocks (“source-contacting faults”) and upward into Yingshan Formation reservoirs, forming efficient efficient migration pathways for hydrocarbon delivery to suitable traps. (3) Analysis of dry and water-bearing wells identifies “triple-element coupling” as the core condition for high-quality hydrocarbon reservoirs: superior transport (effective source-contacting faults linking Cambrian source rocks); high-quality storage space (unfilled dissolution pores, vugs, and effective fracture networks forming a good storage-seepage system); favorable structural position (traps at relatively high structural levels, avoiding locations below the oil-water contact or lateral hydrocarbon migration escape zones). This model is supported by recent drilling—Well W11 successfully discovered a productive gas reservoir. Future exploration should target “sweet spots” where source-contacting fault development, high-quality fracture-cavity reservoirs, and relatively high structural positions are effectively coupled, while avoiding adverse impacts from late-stage tectonic destruction and special geological bodies. Acknowledgements We thank Sinopec Northwest Oilfield Company for the favorable data. We would like to express our sincere gratitude to Schlumberger for providing the Petrel software, which was an essential tool in this research work. Author contributions **HKS**; Conceptualization, Investigation, Methodology, Project administration, Resources, Validation, Formal analysis, Writing – original draft, review & editing**MB**; Data curation, Investigation, Methodology, review & editing**AGD**; Conceptualization, Methodology, Validation, review & editing**HG**; Data curation, Investigation, review & editing. Funding This work was supported by the Collaborative Project Funding of Research Institute of Exploration and Development of Sinopec Northwest Oilfield Company [Grant Number KY2024-027]. Data availability All data generated or analyzed during this study are included in this published article and its supplementary information files. 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The drilling data (including well logs and core descriptions) are from the same source. Due to confidentiality agreements, the raw data are not publicly available, but processed data supporting the findings are available from the corresponding author upon reasonable request and with permission of the data owner. The research methods mainly include two parts: fault prediction and karst cave prediction (Fig. 3 a). For fault prediction, a multi-azimuth amplitude contrast fusion ant-tracking technique was adopted 71 – 73 . This method first decomposes the seismic discontinuity attribute volume within the range of 0–180° by azimuth, then selects the appropriate azimuth data volume for fusion. Previous studies on the stress state of the study area have indicated that the main stress direction is predominantly NE(Fig. 3 f 3 g) 42 , 74 , 75 . Combined with the nature of the current data volume, it is necessary to select the discontinuity data volume within the azimuth range of 70–120° for fusion (Fig. 3 h), based on which ant-tracking is performed. Comparison with traditional ant-tracking results (Fig. 3 e) shows that this method can effectively suppress false faults caused by poor seismic signal quality, and the obtained fault distribution is more regular and consistent with actual geological characteristics. Fig. 3. Open in a new tab (a) Technical workflow of the study; (b) Amplitude gradient calculation results along two directions and the final cave characterization attribute result; (c) Schematic diagram of amplitude gradient calculation; (d) Schematic diagram of statistical variance; (e) Comparison between the ant-tracking results computed by the method in this study and conventional ant-tracking results; (f) - (g) Calculation results of amplitude comparison at azimuth angles of 10° and 100°; (h) Amplitude comparison calculation using the preferred azimuth. For karst cave prediction, a parallelism variance attribute integrating spatial gradient changes of amplitude was employed(Fig. 3 c 3 d). Figure 3 c shows the characteristic vector of coherent amplitude v(x, y) based on a 9-trace analysis window, where and represent the gradient changes of coherent amplitude in the horizontal and vertical directions, respectively. To reduce the impact of acquisition footprints, referring to the method proposed by Marfurt (2006) 76 , instead of directly differentiating along the x and y directions, a smoother differential operator was adopted to construct an average absolute amplitude spatial change rate attribute based on dip scanning, which fuses the weighted energy coherent amplitude gradient. Its mathematical expression is as follows: This attribute is ultimately used to characterize the development law of “beaded” reflections in the study area (Fig. 3 b). The prediction results are in good agreement with drilling and seismic response characteristics, especially in the W7 well area, so it is used to systematically describe the spatial distribution characteristics of karst caves. All data generated or analyzed during this study are included in this published article and its supplementary information files. The datasets analyzed during the current study available from the corresponding author on reasonable request. Articles from Scientific Reports are provided here courtesy of Nature Publishing Group ACTIONS View on publisher site PDF (4.9 MB) Cite Collections Permalink PERMALINK Copy RESOURCES Similar articles Cited by other articles Links to NCBI Databases Cite Copy Download .nbib .nbib Format: AMA APA MLA NLM Add to Collections Create a new collection Add to an existing collection Name your collection * Choose a collection Unable to load your collection due to an error Please try again Add Cancel Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top