The Mesozoic volcanic rocks of the Bodong Low Uplift in the Bohai Bay Basin have been studied and explored for years. In 2024, the LK7-A well drilled in this region tested high-yield oil and gas flows from volcanic weathered crust. These volcanic rocks need to be further investigated in terms of distribution patterns, conditions for forming high-quality reservoirs, and main factors controlling hydrocarbon accumulation. Based on the logging, geochemical and mineralogical data from wells newly drilled to the Mesozoic volcanic rocks in the basin, and high-resolution 3D seismic data, a comprehensive study was conducted for this area. The research findings are as follows. First, the volcanic rocks in the LK7-A structure are adakites with a large source area depth, and the deep and large faults have provided channels for the emplacement of intermediate-acidic volcanic rocks. Second, volcanic rock reservoirs are mainly distributed in tectonic breccias and intermediate-acidic lavas, and they are dominantly fractured-porous reservoirs, with high-porosity and low-permeability or medium-porosity and low-permeability. Third, the dominant lithologies/lithofacies is the basic condition for forming large-scale volcanic rock reservoirs. Structural fractures and late-stage strong weathering are crucial mechanisms for the formation scale of reservoirs in the Mesozoic volcanic rocks. Fourth, the Bodong Low Uplift exhibits strong hydrocarbon charging by two sags and overpressure mudstone capping, which are favorable for forming high-abundance oil and gas reservoirs. The Mesozoic volcanic buried hills in the study area reflect good trap geometry, providing favorable conditions for large-scale reservoir formation, and also excellent migration and accumulation conditions. Areas with long-term exposure of intermediate-acidic volcanic rocks, particularly in active structural regions, are the key targets for future exploration.

Based on a large amount of basic research and experimental analysis data from Shengli Oilfield, Bohai Bay Basin, guided by the theory of whole petroleum system, the distribution of sedimentary systems, the distribution and hydrocarbon generation and expulsion process of source rocks, the variation of reservoir properties, and the control of fracture systems on hydrocarbon accumulation in the Paleogene of the Jiyang Depression, Boahai Bay Basin, were systematically analyzed, and the geological characteristics of the whole petroleum system in the rift basin were identified. Taking the Dongying Sag as an example, combined with the distribution of discovered conventional, tight, and shale oil/gas, a hydrocarbon accumulation model of the fault-controlled whole petroleum system in rift basin was proposed, and the distribution patterns of conventional and unconventional oil and gas reservoirs in large geological bodies horizontally and vertically were clarified. The research results show that paleoclimate and tectonic cycles control the orderly distribution of the Paleogene sedimentary system in the Jiyang Depression, the multi-stage source rocks provide sufficient material basis for in-situ shale oil/gas accumulation and other hydrocarbon migration and accumulation, the changes in reservoir properties control the dynamic threshold of hydrocarbon accumulation, and the combination of faults and fractures at different stages controls hydrocarbon migration and accumulation, and in-situ retention and accumulation of shale oil/gas, making the whole petroleum system in the rift basin associated, segmented and abrupt. The above elements are configured to form a composite whole petroleum system controlled by faults in the Paleogene of the Jiyang Depression. Moreover, under the control of hydrocarbon accumulation dynamics, a whole petroleum system can be divided into conventional subsystem and unconventional subsystem, with shale oil, tight oil and conventional oil in an orderly distribution in horizontal and vertical directions. This systematic understanding is referential for analyzing the whole petroleum system in continental rift basins in eastern China.

Based on large-field rock thin section scanning, high-resolution field emission-scanning electron microscopy (FE-SEM), fluorescence spectroscopy, and rock pyrolysis experiments of the Mesoproterozoic Jixianian Hongshuizhuang Formation shale samples from the Yanliao Basin in northern China, combined with sedimentary forward modeling, a systematic petrological and organic geochemical study was conducted on the reservoir quality, oil-bearing potential, distribution, and resource potential of the Hongshuizhuang Formation shale in Well Yuanji-2. The results indicate that: (1) The original organic carbon content of the Hongshuizhuang Formation shale averages up to 6.24%, and the original hydrocarbon generation potential is as high as 44.09 mg/g, demonstrating a strong oil generation potential. (2) The rock type is primarily siliceous shale containing low clay mineral content, characterized by the development of shale bedding fractures and organic shrinkage fractures, resulting in good compressibility and reservoir quality. (3) The fifth and fourth members of the Hongshuizhuang Formation serve as shale oil sweet spots, contributing more than 60% of shale oil production with their total thickness as only 40% of the target formation. (4) The Kuancheng-Laozhuanghu area is the most prospective shale oil exploration option in the Yanliao Basin and covers approximately 7 200 km². Its original total hydrocarbon generation potential reaches about 74.11 billion tons, with current estimated retained shale oil resources exceeding 1.148 billion tons (lower limit) - comparable to the geological resources of the Permian Lucaogou Formation shale oil in the Jimsar Sag of the Junggar Basin. These findings demonstrate the robust exploration potential of the Hongshuizhuang Formation shale oil in the Yanliao Basin.

Taking the Wangfu fault depression in the Songliao Basin as an example, on the basis of seismic interpretation and drilling data analysis, the distribution of the basement faults was clarified, the fault activity periods of the coal-bearing formations were determined, and the fault systems were divided. Combined with the coal seam thickness and actual gas indication in logging, the controls of fault systems in the rift basin on the spatial distribution of coal and the occurrence of coal-rock gas were identified. The results show that the Wangfu fault depression is an asymmetrical graben formed under the control of basement reactivated strike-slip T-rupture, and contains coal-bearing formations and five sub-types of fault systems under three types. The horizontal extension strength, vertical activity strength and tectono-sedimentary filling difference of basement faults control vertical stratigraphic sequences, accumulation intensity, and accumulation frequency of coal seam in rift basin. The structural transfer zone formed during the segmented reactivation and growth of the basement faults controls the injection location of steep slope exogenous clasts. The filling effect induced by igneous intrusion accelerates the sediment filling process in the rift lacustrine area. The structural transfer zone and igneous intrusion together determine the preferential accumulation location of coal seams in the plane. The faults reactivated at the basement and newly formed during the rifting phase serve as pathways connecting to the gas source, affecting the enrichment degree of coal-rock gas. The vertical sealing of the faults was evaluated by using shale smear factor (SSF), and the evaluation criterion was established. It is indicated that the SSF is below 1.1 in major coal areas, indicating favorable preservation conditions for coal-rock gas. Based on the influence factors such as fault activity, segmentation and sealing, the coal-rock gas accumulation model of rift basin was established.

For deep prospects in the foreland thrust belt, southern Junggar Basin, NW China, there are uncertainties in factors controlling the structural deformation, distribution of paleo-structures and detachment layers, and distribution of major hydrocarbon source rocks. Based on the latest 3D seismic, gravity-magnetic, and drilling data, together with the results of previous structural physical simulation and discrete element numerical simulation experiments, the spatial distribution of pre-existing paleo-structures and detachment layers in deep strata of southern Junggar Basin were systematically characterized, the structural deformation characteristics and formation mechanisms were analyzed, the distribution patterns of multiple hydrocarbon source rock suites were clarified, and hydrocarbon accumulation features in key zones were reassessed. The exploration targets in deep lower assemblages with possibility of breakthrough were expected. Key results are obtained in three aspects. First, structural deformation is controlled by two-stage paleo-structures and three detachment layers with distinct lateral variations: the Jurassic layer (moderate thickness, wide distribution), the Cretaceous layer (thickest but weak detachment), and the Paleogene layer (thin but long-distance lateral thrusting). Accordingly, a four-layer composite deformation sequence was identified, and the structural genetic model with paleo-bulge controlling zonation by segments laterally and multiple detachment layers controlling sequence vertically. Second, the Permian source rocks show a distribution pattern with narrow trough (west), multiple sags (central), and broad basin (east), which is depicted by combining high-precision gravity-magnetic data and time-frequency electromagnetic data for the first time, and the Jurassic source rocks feature thicker mudstones in the west and rich coals in the east according to the reassessment. Third, two petroleum systems and a four-layer composite hydrocarbon accumulation model are established depending on the structural deformation strength, trap effectiveness and source-trap configuration. The southern Junggar Basin is divided into three segments with ten zones, and a hierarchical exploration strategy is proposed for deep lower assemblages in this region, that is, focusing on five priority zones, expanding to three potential areas, and challenging two high-risk targets.

During drilling operations, the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit. This study investigates high-resolution seismic data processing technologies and methods tailored for drilling scenarios. The high-resolution processing of seismic data is divided into three stages: pre-drilling processing, post-drilling correction, and while-drilling updating. By integrating seismic data from different stages, spatial ranges, and frequencies, together with information from drilled wells and while-drilling data, and applying artificial intelligence modeling techniques, a progressive high-resolution processing technology of seismic data based on multi-source information fusion is developed, which performs simple and efficient seismic information updates during drilling. Case studies show that, with the gradual integration of multi-source information, the resolution and accuracy of seismic data are significantly improved, and thin-bed weak reflections are more clearly imaged. The updated seismic information while-drilling demonstrates high value in predicting geological bodies ahead of the drill bit. Validation using logging, mud logging, and drilling engineering data ensures the fidelity of the processing results of high-resolution seismic data. This provides clearer and more accurate stratigraphic information for drilling operations, enhancing both drilling safety and efficiency.

Conventional borehole image log interpretation of linear fractures on volcanic rocks, represented as sinusoids on unwrapped cylinder projections, is relatively straight-forward, however, interpreting non-linear rock structures and complex facies geometries can be more challenging. To characterize diverse volcanic paleoenvironments related to the formation of the South American continent, this study presents a new methodology based on image logs, petrography, seismic data, and outcrop analogues. The presented methodology used pseudo-boreholes images generated from outcrop photographs with typical igneous rock features worldwide simulating 2D unwrapped cylinder projections of a 31 cm (12.25 in) diameter well. These synthetic images and standard outcrop photographs were used to define morphological patterns of igneous structures and facies for comparison with wireline borehole image logs from subsurface volcanic and subvolcanic units, providing a “visual scale” for geological evaluation of volcanic facies, significantly enhancing the identification efficiency and reliability of complex geological structures. Our analysis focused on various scales of columnar jointing and pillow lava lobes with additional examples including pahoehoe lava, ignimbrite, hyaloclastite, and various intrusive features in Campos, Santos, and Parnaíba basins in Brazil. This approach increases confidence in the interpretation of subvolcanic, subaerial, and subaqueous deposits. The image log interpretation combined with regional geological knowledge has enabled paleoenvironmental insights into the rift magmatism system related to the breakup of Gondwana with associated implications for hydrocarbon exploration.

The presence of clay coatings on the surfaces of quartz grains can play a pivotal role in determining the porosity and permeability of sandstone reservoirs, thus directly impacting their reservoir quality. This study employs a multiphase-field model of syntaxial quartz cementation to explore the effects of clay coatings on quartz cement volumes, porosity, permeability, and their interrelations in sandstone formations. To generate various patterns of clay coatings on quartz grains within three-dimensional (3D) digital sandstone grain packs, a pre-processing toolchain is developed. Through numerical simulation experiments involving syntaxial overgrowth cementation on both single crystals and multigrain packs, the main coating parameters controlling quartz cement volume are elucidated. Such parameters include the growth of exposed pyramidal faces, lateral encasement, coating coverage, and coating pattern, etc. The coating pattern has a remarkable impact on cementation, with the layered coatings corresponding to fast cement growth rates. The coating coverage is positively correlated with the porosity and permeability of sandstone. The cement growth rate of quartz crystals is the lowest in the vertical orientation, and in the middle to late stages of evolution, it is faster in the diagonal orientation than in the horizontal orientation. Through comparing the simulated results of dynamic evolution process with the actual features, it is found that the simulated coating patterns after 20 d and 40 d show clear similarities with natural samples, proving the validity of the proposed three-dimensional numerical modeling of coatings. The methodology and findings presented contribute to improved reservoir characterization and predictive modeling of sandstone formations.

The core sampling experiments were conducted after hydraulic fracturing in the three-dimensional development zone of Fuling shale gas. Six coring wells of different well types were systematically designed. Based on the integrated engineering technology of post-fracturing drilling, coring and monitoring of shale and the analysis of fracture source tracing, the evaluation of the fracture network after fracturing in the three-dimensional development of shale gas was conducted. The data of core fractures after fracturing indicate that three major types of fractures are formed after fracturing: natural fractures, hydraulic fractures, and fractures induced by external mechanical force, which are further classified into six subcategories: natural structural fractures, natural bedding fractures, hydraulic fractures, hydraulically activated fractures, drilling induced fractures, and fractures induced by core transportation. The forms of the artificial fracture network after fracturing are complex. Hydraulic fractures and hydraulically activated fractures interweave with each other, presenting eight forms of artificial fracture networks, among which the “一”-shaped fracture is the most common, accounting for approximately 70% of the total fractures. When the distance to the fractured wellbore is less than 35 m, the density of the artificial fracture network is relatively high; when it is 35-100 m, the density is lower; and when it is beyond 100 m, the density gradually increases. The results of the fracture tracing in the core sampling area confirm that the current fracturing technology can essentially achieve the differential transformation of the reservoir in the main area of Jiaoshiba block in Fuling. The three-layer three-dimensional development model can efficiently utilize shale gas reserves, although there is still room for improvement in the complexity and propagation uniformity of fractures. It is necessary to further optimize technologies such as close-cutting combined with temporary blocking and deflection within fractures or at fracture mouths, as well as limited flow perforation techniques, to promote the balanced initiation and extension of fractures.

Currently, unconventional reservoirs are characterized by low single well-controlled reserves, high initial production but fast production decline. This paper sorts out the problems of energy dispersion and limited length and height of main hydraulic fractures induced in staged multi-cluster fracturing, and proposes an innovative concept of “energy-focused fracturing development”. The technical connotation, theoretical model, and core techniques of energy-focused fracturing development are systematically examined, and the implementation path of this technology is determined. The energy-focused fracturing development technology incorporates the techniques such as geology-engineering integrated design, perforation optimization design, fracturing process design, and drainage engineering control. It transforms the numerous, short and dense hydraulic fractures to limited, long and sparse fractures. It focuses on fracturing energy, and aims to improve the fracture length, height and lateral width, and the proppant long-distance transportation capacity, thus enhancing the single well-controlled reserves and development effect. The energy-focused fracturing development technology has been successfully applied in the carbonate reservoirs in buried hill, shallow coalbed methane reservoirs, and coal-rock gas reservoirs in China, demonstrating the technology’s promising application. It is concluded that the energy-focused fracturing development technology can significantly increase the single well production and estimated ultimate recovery (EUR), and will be helpful for efficiently developing low-permeability, unconventional and low-grade resources in China.

The production optimization in the closed-loop reservoir management is generally empirical, and challenged by the issues such as low precision, low efficiency, and difficulty in solving constrained optimization problems. This paper outlines the main principles, advantages and disadvantages of commonly used production optimization methods/models, and then proposes an intelligent integrated production optimization method for waterflooding reservoirs that considers efficiency and precision, real-time and long-term effects, and the interaction and synergy between a variety of optimization models. This method integrates multiple optimization methods/models, such as reservoir performance analysis, reduced-physics models, and reservoir numerical models, with these model results and insights organically coupled to facilitate model construction and matching. This proposed method is elucidated and verified by field examples. The findings indicate that the optimal production optimization model varies depending on the specific application scenario. Reduced-physics models are conducive to short-term real-time optimization, whereas the simulator-based surrogate optimization and streamline-based simulation optimization methods are more suitable for long-term optimization strategy formulation, both of which need to be implemented under reasonable constraints from the perspective of reservoir engineering in order to be of practical value.

This study systematically reviews the development history and key technological breakthroughs of large gas fields in the Ordos Basin, and summarizes the development models of three gas reservoir types, low-permeability carbonate, low-permeability sandstone and tight sandstone, as well as the progress in deep coal-rock gas development. The current challenges and future development directions are also discussed. Mature development models have been formed for the three representative types of gas reservoirs in the Ordos Basin: (1) Low-permeability carbonate reservoir development model featuring groove fine-scale characterization and three-dimensional vertical succession between Upper and Lower Paleozoic formations. (2) Low-permeability sandstone reservoir development model emphasizing horizontal well pressure-depletion production and vertical well pressure-controlled production. (3) Tight sandstone gas reservoir development model focusing on single-well productivity enhancement and well placement optimization. In deep coal-rock gas development, significant progress has been achieved in reservoir evaluation, sweet spot prediction, and geosteering of horizontal wells. The three types of reservoirs have entered the mid-to-late stages of the development, when the main challenge lies in accurately characterizing residual gas, evaluating secondary gas-bearing layers, and developing precise potential-tapping strategies. In contrast, for the early-stage development of deep coal-rock gas, continuous technological upgrades and cost reduction are essential to achieving economically viable large-scale development. Four key directions of future research and technological breakthroughs are proposed: (1) Utilizing dual-porosity (fracture-matrix) modeling techniques in low-permeability carbonate reservoirs to delineate the volume and distribution of remaining gas in secondary pay zones, supporting well pattern optimization and production enhancement of existing wells. (2) Integrating well-log and seismic data to characterize reservoir spatial distribution of successive strata, enhancing drilling success rates in low-permeability sandstone reservoirs. (3) Utilizing the advantages of horizontal wells to penetrate effective reservoirs laterally, achieving meter-scale quantification of small-scale single sand bodies in tight gas reservoirs, and applying high-resolution 3D geological models to clarify the distribution of remaining gas and guide well placement optimization. (4) Further strengthening the evaluation of deep coal-rock gas in terms of resource potential, well type and pattern, reservoir stimulation, single-well performance, and economic viability.

This study takes shale samples from the Jiaoshiba block in the Fuling shale gas field of the Sichuan Basin, and uses the true triaxial testing system to conduct a series of mechanical experiments under deep shale reservoir conditions after shale hydration. Stress-strain data and mechanical parameters of shale after hydration under high temperature and high pressure were obtained to investigate the effects of reservoir temperature, hydration time and horizontal stress difference on the mechanical strength of shale after hydration. By using nonlinear regression and interpolation methods, a prediction model for the mechanical strength of shale after hydration was constructed, and the mechanical strength chart of deep shale under high stress difference was plotted. First, higher hydration temperature, longer hydration reaction time, and greater horizontal stress difference cause shale to enter the yield stage earlier during the compression process after hydration and to exhibit more prominent plastic characteristics, lower peak strength, peak strain, residual strength and elastic modulus, and higher Poisson’s ratio. Second, the longer the hydration time, the smaller the impact of hydration temperature on the mechanical strength of deep shale is. As the horizontal stress difference increases, the peak strength and residual strength weaken intensely, and the peak strain, elastic modulus and Poisson’s ratio deteriorate slowly. Third, the mechanical strength of shale decreases significantly in the first 5 days of hydration, but gradually stabilizes as the hydration time increases. Fourth, the visual mechanical strength chart helps to understand the post-fracturing dynamics in deep shale gas reservoir fracturing site and adjust the drainage and production plan in time.

To optimize the bit selection for large-diameter wellbore in the upper section of an ultra-deep well S-1, a full-well dynamic model integrating drill string vibration and bit rock-breaking was established and then verified using measured vibration data of drilling tools and actual rate of penetration (ROP) from Well HT-1 in northern Sichuan Basin. This model was employed to calculate and analyze drill string dynamic characteristics during large-diameter wellbore drilling in the Jurassic Penglaizhen Formation of Well S-1, followed by bit optimization. Research results show that during the drilling in Penglaizhen Formation of Well S-1, considering both the ROP of six candidate bits and the lateral/axial/torsional vibration characteristics of downhole tools, the six-blade dual-row cutter bit with the fastest ROP (average 7.12 m/h) was optimally selected. When using this bit, the downhole tool vibration levels remained at medium-low values. Field data showed over 90% consistency between actual ROP data and dynamic model calculation results after bit placement, demonstrating that the model can be used for bit program screening.

The method for optimizing the hydraulic fracturing parameters of the cube development infill well pad was proposed, aiming at the well pattern characteristic of “multi-layer and multi-period” of the infill wells in Sichuan Basin. The fracture propagation and inter-well interference model were established based on the evolution of 4D in-situ stress, and the evolution characteristics of stress and the mechanism of interference between wells were analyzed. The research shows that the increase in horizontal stress difference and the existence of natural fractures/faults are the main reasons for inter-well interference. Inter-well interference is likely to occur near the fracture zones and between the infill wells and parent wells that have been in production for a long time. When communication channels are formed between the infill wells and parent wells, it can increase the productivity of parent wells in the short term. However, it will have a delayed negative impact on the long-term sustained production of both infill wells and parent wells. The change trend of in-situ stress caused by parent well production is basically consistent with the decline trend of pore pressure. The lateral disturbance range of in-situ stress is initially the same as the fracture length and reaches 1.5 to 1.6 times that length after 2.5 years. The key to avoiding inter-well interference is to optimize the fracturing parameters. By adopting the M-shaped well pattern, the optimal well spacing for the infill wells is 300 m, the cluster spacing is 10 m, and the liquid volume per stage is 1 800 m³.

For shale oil reservoirs in the Jimsar Sag of Junggar Basin, the fracturing treatments are challenged by poor prediction accuracy and difficulty in parameter optimization. This paper presents a fracturing parameter intelligent optimization technique for shale oil reservoirs and verifies it by field application. A self-governing database capable of automatic capture, storage, calls and analysis is established. With this database, 22 geological and engineering variables are selected for correlation analysis. A separated fracturing effect prediction model is proposed, with the fracturing learning curve decomposed into two parts: (1) overall trend, which is predicted by the algorithm combining the convolutional neural network with the characteristics of local connection and parameter sharing and the gated recurrent unit that can solve the gradient disappearance; and (2) local fluctuation, which is predicted by integrating the adaptive boosting algorithm to dynamically adjust the random forest weight. A policy gradient-genetic-particle swarm algorithm is designed, which can adaptively adjust the inertia weights and learning factors in the iterative process, significantly improving the optimization ability of the optimization strategy. The fracturing effect prediction and optimization strategy are combined to realize the intelligent optimization of fracturing parameters. The field application verifies that the proposed technique significantly improves the fracturing effects of oil wells, and it has good practicability.

To improve the accuracy and generalization of well logging curve reconstruction, this paper proposes an artificial intelligence large language model “Gaia” and conducts model evaluation experiments. By fine-tuning the pre-trained large language model, the Gaia significantly improved its ability in extracting sequential patterns and spatial features from well-log curves. Leveraging the adapter method for fine-tuning, this model required training only about 1/70 of its original parameters, greatly improving training efficiency. Comparative experiments, ablation experiments, and generalization experiments were designed and conducted using well-log data from 250 wells. In the comparative experiment, the Gaia model was benchmarked against cutting-edge small deep learning models and conventional large language models, demonstrating that the Gaia model reduced the mean absolute error (MAE) by at least 20%. In the ablation experiments, the synergistic effect of the Gaia model's multiple components was validated, with its MAE being at least 30% lower than that of single-component models. In the generalization experiments, the superior performance of the Gaia model in blind-well predictions was further confirmed. Compared to traditional models, the Gaia model is significantly superior in accuracy and generalization for logging curve reconstruction, fully showcasing the potential of large language models in the field of well-logging. This provides a new approach for future intelligent logging data processing.