The Kuqa Depression, a prolific hydrocarbon province in China's Tarim Basin, hosts a dual-sourcepetroleum system with Jurassic coal-bearing and Triassic lacustrine strata. However, the origins and accumulation mechanisms of hydrocarbons in the Dibei Structural Belt remain contentious, particularlyregarding contributions from Jurassic (J(2)kz, J1y) versus Triassic (T(3)h, T(2-3)k) source rocks, compoundedby ambiguities in biomarker interpretations and uncalibrated thermal models. Advanced geochemicalfingerprinting - including sterane distributions, gammacerane indices (GI; ratio of gammacerane to C30hopane), and delta & sup1;& sup3;C isotopes - was integrated with calibrated burial-thermal modeling and structural analysis,which allowed us to clarify source contributions, hydrocarbon charging history, and structural controlson accumulation. Geochemical results demonstrated that Yangxia Formation (Paleogene; a major regionalseal and secondary reservoir unit within the Kuqa Depression) oils exhibit "inverted-L" sterane patterns(C27 < C29) and delta & sup1;& sup3;C values of -26 parts per thousand to -23 parts per thousand, confirming derivation from Jurassic coal measures. Incontrast, Ahe Formation (Jurassic; a major regional sandstone reservoir unit within the Kuqa Depression)hydrocarbons displayed "V-shaped" sterane ratios (C27 > C29), delta & sup1;& sup3;C values of -32 parts per thousand to -30 parts per thousand, and elevatedGI (0.21-0.32), indicative of Triassic lacustrine sources. Notably, the identification of Triassic-sourcedhydrocarbons in deep Ahe reservoirs challenged previous Jurassic-centric models, resolving ambiguitiesthrough multiproxy integration. Burial-thermal modeling, constrained by fluid inclusion homogenizationtemperatures (80 degrees C-160 degrees C), revealed three charging phases: phase I (19-16 Ma, Jidike Fm.), phase II (16-12 Ma, Kangcun Fm.), and phase III (5-1 Ma, Kuqa Fm.), with phase III Himalayan tectonics criticallyreshaping paleo-accumulations into an inverted "gas-below-oil" stratification (phase reversal due to tectonicreorganization). Structural analysis revealed (1) two boundary-fault anticlinal traps (defined by opposednorth- and south-dipping thrust faults) with vertical gas migration in Ahe sandstones and (2) fault-sealed tightgas accumulations controlled by reservoir quality. These findings highlighted the dominant contribution ofTriassic sources to deep gas reservoirs in Dibei and underscored the importance of multiphase tectonicevolution and source-reservoir coupling. This study provided a predictive framework for hydrocarbonexploration in fold-and-thrust belts, advocating prioritized assessment of fault connectivity and Triassicsaline lacustrine source deposits.
Reservoir fluid movement analysis can be enhanced through the integration of 4D seismic attributes and principal component analysis (PCA), showcased through a detailed case study of the C Upper Sand reservoir in the Maui Field, New Zealand. The methodology demonstrates how combining instantaneous, spectral, and geometric attributes can reveal subtle reservoir characteristics that traditional 4D analysis might miss. The case study serves as a vehicle to illustrate the power of this technique, which successfully identifies previously unrecognized fluid barriers, tracks water encroachment patterns, and reveals reservoir compartmentalization affecting production performance. The workflow demonstrates how sweetness and envelope attributes effectively track gas depletion, whereas mean frequency analysis captures water encroachment with remarkable clarity. Spectral bandwidth reveals critical facies variations, including a northeast-southwest trending shoreface deposit acting as a barrier to fluid flow. When integrated through PCA, these attributes provide a comprehensive understanding of the relationship between reservoir heterogeneity and differential fluid movement. This attribute integration technique offers significant advantages over conventional workflows by linking diagenetic cementation patterns to production discrepancies and identifying zones of calcite cementation through the integration of spectral bandwidth and resistivity data. The approach provides a template for improved 4D seismic analysis applicable to similar reservoirs worldwide, with direct implications for optimizing field development planning, well placement, and production strategies.
Shale gas, a key unconventional energy resource, has become increasingly important in global energyproduction. In the current global context, as energy demands rise and the need for sustainable resourcesintensifies, the exploitation of shale gas presents a significant opportunity. In China, shale gas explorationholds great promise, especially in the Ordos Basin, which is considered a major contributor to the nation'sfuture energy portfolio. The Shanxi Formation in the Ordos Basin is rich in shale gas resources, withrecent exploration breakthroughs positioning it as a strategic replacement field for future reserve expansionand production enhancement. To analyze the geological characteristics of shale gas accumulation and itsmain controlling factors of gas-bearing capacity in the Shanxi Formation, this study systematically analyzedthe mineralogical, geochemical, reservoir properties, and adsorption-desorption characteristics of the shaleusing data from three new wells, including well logging, core samples, and experimental testing in theYan'an area. The findings revealed that the Shanxi Formation shale exhibits large single-layer thickness,excellent lateral continuity, and high organic matter abundance with Type III kerogen. Coupled with coalseams, it forms high-quality gas source rocks characterized by high thermal maturity. The shale demonstratedfavorable fracturability and gas storage capacity due to its high brittle mineral content (brittleness index:44.63%) and a well-developed nanoscale pore-fracture network (specific surface area: 3.84 m2/g; pore volume:0.0103 cm3/g). Field validation showed a desorbed gas content average of 1.137 m3/t, and horizontal welltests achieved an absolute open flow exceeding 5.3 & times; 104 m3/d, confirming its potential for commercialdevelopment. This study highlighted the critical roles of organic matter abundance, thermal maturity, andpore structure in controlling gas content, providing a scientific foundation for efficient shale gas explorationand hydraulic fracturing optimization in the Ordos Basin. These results hold significant implications foradvancing large-scale shale gas reserve expansion in the Yan'an area.
Uncertainty quantification (UQ) in well log prediction remains a significant challenge within geoscientific research because conventional methodologies yield single point estimates without addressing the associated predictive uncertainty The absence of uncertainty assessment may result in suboptimal decisions during exploration phases and reservoir characterization. This study addressed this limitation by applying the conformalized quantile regression (CQR) technique to predict missing AC (P-Sonic) acoustic log curves while simultaneously quantifying the uncertainty of these predictions. The analysis used nine Log ASCII Standard (LAS) files from the Volve Field, with exploratory data analysis revealing substantial missingness, particularly in AC (P-Sonic) logs. Pearson correlation analysis identified strong relationships between AC (P-Sonic), density (DEN), and neutron (NEU) logs. The conformal prediction framework partitions the dataset into training, validation, and test subsets, enabling the derivation of statistically valid prediction intervals. The CQR approach achieved AC (P-Sonic) log predictions with 95% coverage. This work demonstrated the value of UQ in well log prediction by providing accurate predictions accompanied by reliable prediction intervals, thereby supporting robust and informed decision-making in exploration and reservoir characterization. The methodology developed herein offers a comprehensive tool for risk management, enabling geoscientists to proactively identify and mitigate potential adverse outcomes associated with well-log data utilization.
Seismic modeling of carbonate reservoir analogs bridges the gap between outcrop and seismic scales. A forward modeling study based on the Cristal cave karst system (S & atilde;o Francisco Craton, Brazil) is presented. A digital outcrop model (DOM) of the Cristal cave, lithostratigraphic columns, and petrophysical measurements were used to build 2D models of cave systems. The shapes, dimensions, and horizontal spacing of the caves were varied so that 12 different scenarios were composed, which may also include silicified halos. The resulting raw seismic sections were processed following a conventional seismic workflow. Taking into consideration only the resolvability along horizontal and vertical directions, four patterns of cave responses are distinguished: (1) tabular string of bead responses (SBRs) caused by caves with relatively small sizes and horizontal spacings, as in the actual DOM of the Cristal cave, which cannot be resolved either horizontally or vertically; (2) short SBRs caused by caves with relatively small sizes and large horizontal spacing so that they can be resolved horizontally but not vertically; (3) superposed diffraction patterns caused by relatively large caves and small spacing so that they can be resolved vertically but not horizontally; and (4)isolated diffraction patterns caused by relatively large caves and large spacing so that they can be resolved horizontally and vertically. Pull-down effects are observed in most of these patterns. Silicified halos enhance the signals of the small caves but attenuate the signals of large caves. A seismic cube was simulated in the scenario of caves with relatively small sizes, but with large horizontal spacing. A strong correlation between the cave system and the SBRs is evidenced by the seismic cube. The insights gained from this study offer valuable guidance for interpreting cave systems in seismic images.
Core data provide valuable in situ information on the chemical and physical characteristics of subsurface formations. Thin sections, for instance, allow us to define rock types with similar mineral composition, lithologies, and pore types (i.e., petrofacies). Petrofacies logs illustrate the stratigraphic variability within a reservoir and are often used to constrain 3D facies and petrophysical-property models. However, core data are often scarce, prompting the exploration of alternative sources. Well logs, with their different vertical resolution, are commonly used to characterize mineralogy, lithology, and porosity. The challenge lies in reconciling the differences between thin sections and well logs. To address this, a machine learning-based workflow is developed. Our goal was to bridge the resolution gap between these two data types and identify subtle variations in rock properties. Specifically, the focus was on collocated cores that provided thin-section-based petrofacies and X-ray fluorescence (XRF) data. Our approach involved two semi-supervised methods: self-training and labeled clustering. By combining XRF data with dimensionality reduction techniques, a reliable classification of thin-section-based petrofacies is achieved. Remarkably, both approaches achieved accuracies exceeding 90% on Sycamore Formation data. Among the dimensionality reduction techniques tested, Uniform Manifold Approximation and Projection (UMAP) produced the most accurate results. This resulted in petrofacies logs that bridge the resolution gap between core-based thin sections and well-log data. Furthermore, integrating semi-supervised methods into routine core analysis offers substantial cost and time savings. These methods enhance stratigraphic correlation, aid in identifying target zones, design horizontal wells, and constrain subsurface models.
Seismic data can provide an intuitive and accurate reflection of stratigraphic information. However, inareas with low-density seismic line coverage, relying solely on seismic profiles to accurately describe thespatial distribution characteristics of faults in the study area is not convincing. This study used two boundaryidentification methods of gravity and magnetic potential fields: analytical signal amplitude and meannormalized total horizontal derivative, to identify the boundaries of geological bodies in the southeasternGulf of Mexico basin, based on the lateral heterogeneity of geological structures. Combined with theinterpretation results of seismic profiles, the accuracy of the potential field boundary identification wasverified, enhancing the rationality of joint gravity, magnetic, and seismic interpretation results for studyingthe spatial distribution characteristics of faults. The study confirmed that the analytical signal amplitude andthe mean normalized total horizontal derivative methods can be effectively applied to fault characterizationin areas with insufficient seismic coverage. Multiscale faults identified using various approaches controlledthe stratigraphic deposition during the Jurassic and Early Cretaceous periods. This research implemented amethod for enhancing the satellite gravity and magnetic anomalies and provided new insights into studyingthe sedimentary faults and regional tectonic evolution in the southeastern Gulf of Mexico basin
To analyze the deep geological structures of a copper-molybdenum polymetallic ore district located in the Shangri-La region, Yunnan Province, China, the audio-frequency magnetotelluric (AMT) sounding method was carried out. This approach accurately determined the electrical and structural characteristics of the subsurface in the mining area. Ore-prospecting indicators based on AMT data summarized the relationship between resistivity anomalies in AMT profiles and different types of orebodies: vein-like or columnar low-resistivity zones at shallow depths corresponding to intermediate- to low-temperature hydrothermal gold, lead, and zinc polymetallic orebodies; areas exhibiting columnar medium or medium-low resistivity characteristics indicating the presence resence of skarn-type or porphyry-type copper-molybdenum polymetallic orebodies, and intermediate-acid igneous rocks (e.g., diorite porphyrite and porphyry) displaying medium resistivity features. Several potential deep concealed orebodies were delineated, indicating that large-scale porphyry-type copper-molybdenum grebodies may exist at greater depths. The findings suggested that the AMT method is an effective geophytical tool for detecting concealed rock (ore) bodies in the Donglufang copper-molybdenum polymetallic and siruilar deposits. *
Water-rich goaf constitutes a primary hazard factor in coal mines, potentially triggering mine instability and ground subsidence. To detect water-rich goaf efficiently, economically, and non-destructively, the extended spatial autocorrelation (ESPAC) method was applied to perform microtremor surveys in the goaf of the mid-deep sections of the Renjiazhuang coal mine in Ningxia. Microtremor signals were obtained using a linear array, and the 2D distribution of subsurface shear wave velocity was inverted and verified against borehole data. The results showed that in the depth range of -200 to 600 m, the low-velocity zone (500-1500 m/s) is closely related to the fissure development and water-rich area, revealing the spatial distribution of hidden disaster-causing factors in the subsurface. Three low-velocity anomalies within the profile were successfully identified by microtremor probing and combined with borehole drainage validation, confirmed the presence of standing water within these anomalous areas. Enhanced application scope and depth of ESPAC methodology in coal mine water-rich goaf detection have been achieved, establishing comprehensive technical support and theoretical frameworks for subsequent water-rich zone risk assessments and mine safety monitoring systems.
Detecting and delineating thin channels and conduits within flow zones in a carbonate aquifer at field scale is a complex processt To achieve this task, an algorithm is applied that inverts sonic logs to determine the secondary porosity and pore aspect ratios of the carbonate structure. This information helps to characterize flow zones at the pore and borehole scales integrated with Formation microimager(FMI), permeability, and micro-resistivity logs. The inversion of the velocity logs for wells MF37 and EXPM1 from the South Florida Water Management District's Port Mayaca Aquifer site shows similar results. Data from both wells are combined to characterize the structure in the inter-well region of 1200 ft. Because the structure information at the well EXPMI defines detailed flow zone characteristics, the analysis is initiated at this well. In the inter-well region, the flow zones are defined by micro-resistivity anomalies and by relating the aspect ratio logs to the pore space observed in the FMI logs. The well logs are displayed and analyzed together to evaluate the connectivity of the flow zones in the inter-well region, where we identified and delineated three flow zones associated with water production zones. The FMI logs are used to describe the pore structure and the fractures intercepted by the wells. The Elemental Log Analysis porosity image delineates the flow zone structure, confirming the presence of the heterogeneous porous limestone formation at the field scale. This interpretation suggests a methodology for monitoring fluid transmission in flow zones by measuring changes in pore structure using seismic reflection.
The Permian Basin has experienced >9900 local magnitude (ML) 2.0+ earthquakes since 2017 due to thereinjection of produced water from approximately 35,000 horizontal wells into strata above (shallow-saltwater disposal [SWD]) and below (deep-SWD) shale production intervals. Curtailment of deep-SWD withinregulated seismic response areas (SRAs) has resulted in declined monthly rates since 2021; however, in theNorthern Culberson Reeves SRA (NCR SRA), seismicity rates have remained high despite curtailment ofdeep-SWD, and this has caused ongoing concern. In the NCR SRA, there are three distinct levels of faultingidentified within an approximately 1500 km2 3D seismic reflection data set: (1) intrabasement (IB), (2)basement-rooted (BR), and (3) shallow, strata-bound (SSB). IB faults are low-to-moderate-angle (similar to 20 degrees-45 degrees)Proterozoic thrust faults, which are truncated by the Great Unconformity. BR faults are moderate-to-high-angle reverse and subvertical strike-slip faults (similar to 50 degrees-90 degrees), which offset the Great Unconformity and overlyingPaleozoic strata including deep-SWD injection strata. SSB faults are steeply dipping (similar to 60 degrees-80 degrees), elongate,narrow graben, which deform upper-Permian age units, including shallow-SWD injection strata. A regionalstress model, which reflects a normal-faulting regime, was applied, and fault-slip sensitivity was assessedusing the Coulomb shear failure model. Under these conditions, most SSB faults are optimally oriented forslip, BR faults range from stable to critical, and IB faults are stable, requiring a significant pore-pressureincrease to reach criticality. In the NCR SRA, significant earthquakes (M-L 4.0+) are located exclusively withinthe basement. These events are spatially linked to BR fault segments, which sole into IB imbricate faults andextend into deep-SWD injection strata, providing direct hydraulic communication between faults and SWDinjection intervals.
The LH-Y oilfield in the South China Sea is a large reef limestone reservoir characterized by complex. pore systems that vary laterally with sedimentary facies. This pore-scale heterogeneity contributes to rapid increases in water cut in development wells and a low recovery factor. To investigate the impact of pore structure on development performance, we analyzed core samples using scanning electron microscopy, thin sections, and geological vision resistivity logging. Three primary pore types were identified: intergranular pores, intragranular dissolved pores, and dissolution caves, along with three throat types: pore shrinkage, necking, and tortuous throats. Based on integrated core, imaging, and logging data, the reservoirs were classified into four structure types: relatively dense, dense fractured, pore fractured, and porous. Production data from more than 30 horizontal wells show a strong correspondence between the pore structure type and production dynamics. Reservoirs with high fracture density and large connected pores are prone to early water breakthrough and unstable performance. To address this, inflow control devices and continuous packers were deployed to isolate high-permeability channels and delay water coning. Field application of this strategy reduced water put by approximately 10% and increased cumulative oil production by more than 50,000 m & sup2;. These results demonstrate that pore structure characterization is critical for guiding well completion and production optimization in fractured reef limestone reservoirs.
