After 20 years of shale gas exploration and development, China has become the third country that achieves commercial shale gas production, following the United States and Canada. However, earlier exploration and development of the layer were limited to the Silurian Longmaxi Formation. With improved theoretical understanding of shale gas exploration, China has made exploration breakthroughs in Permian and Cambrian shales in recent years, demonstrating the great potential of shale gas in Sichuan Basin. Based on a review of the exploration history of shale gas in the two major marine phases—Silurian Longmaxi Formation and Cambrian Qiongzhusi Formation, this study summarizes the three phases of shale gas exploration: research and exploration (2000-2011), discovery and production (2011-2022), and multi-layer breakthroughs (2022-present). This study thoroughly analyzes the process of two theoretical innovations and paradigm shifts in the exploration and research of marine shale gas in Sichuan Basin. (1) After comparing the formation conditions and exploration and development characteristics of shale gas between China and the United States, Chinese researchers abandoned the simple replication of North American experience, and highlighted the critical role of preservation conditions based on the evolution characteristics of China’s multi-phase tectonics. This completed the first paradigm shift and achieved major exploration breakthroughs in the Silurian Longmaxi Formation. (2) Research on the characteristics of low-organic matter and inorganic pores was enhanced. Traditional theories of enrichment and reservoir formation were developed and improved, and a “migration+in situ” reservoir formation mode was established. This completed the second paradigm shift and led to exploration breakthroughs in Cambrian Qiongzhusi Formation. Recent research breakthroughs in low-organic shale, inorganic pores, and other aspects have expanded both the scope and depth of shale gas exploration, leading to a multi-layer exploration pattern of marine shale gas. It demonstrates broad exploration prospects and strategic value for national energy security. Based on a review of the exploration history and paradigm shifts from the Silurian to the Cambrian periods, as well as an analysis of the implications from major breakthroughs, this study reveals an exploration path of shale gas with Chinese characteristics, providing important references for future exploration and development of multi-layer and multi-field shale gas.

In line with the strategy of “finding oil layers beneath oil layers”, exploration and development in the Jiangsu Oilfield have progressively extended into deeper formations. Deep, tight, and ultra-low permeability reservoirs in northern Jiangsu have become key targets for reserve enhancement and production expansion. However, due to complex structural settings, sedimentary conditions, and natural fractures, the effective utilization of these reservoirs remains highly challenging. This study conducted research on the effective utilization of deep tight reserves in northern Jiangsu. For “sweet spot” characterization, an integrated geological-seismic approach was developed by synthesizing multidisciplinary data from geology, geophysics, reservoir engineering, engineering, and economics. A multi-parameter comprehensive characterization and evaluation methodology was established for tight sandstone reservoirs, accurate delineation of tight reservoirs and effectively guiding reservoir classification and “sweet spot” selection. For volume fracturing, engineering techniques were implemented such as increasing fracture-controlled volume, using temporary plugging and diversion to enhance fracture complexity, and employing combined proppant injection to increase fracture filling volume. These techniques were further optimized based on the characteristics of specific reservoir blocks, resulting in a preliminary volume fracturing technology tailored to the deep tight reservoirs of Jiangsu. To optimize development strategies, well types, production methods, fracturing parameters, and well pattern designs were systematically refined to ensure stable production. For more efficient and cost-effective drilling, improvements in drilling techniques and well placement schemes were introduced, achieving accelerated drilling speed and cost reductions. The study provided effective guidance for field implementation. A total of 7 conventional wells and 1 horizontal well were drilled in block X17, block F125, and block Y48. The average daily oil production per conventional well exceeded 6 tonnes, while the horizontal well maintained a stable daily output of over 10 tonnes. The results demonstrate the effective utilization of deep tight reserves in northern Jiangsu. The research methodology and field practices can provide technical references for the development of other tight oil resources.

The deep oil and gas exploration area serves as a crucial position for resource development in Subei Basin. However, challenges including generally poor physical properties of deep reservoirs, insufficient understanding of oil and gas enrichment mechanisms, and ineffective reservoir prediction to meet exploration demands have constrained the expansion of deep oil and gas exploration. To understand the enrichment mechanisms of deep oil and gas, develop key exploration technologies, and indicate future research directions, this paper focuses on the deep layers of Gaoyou and Jinhu Sags, which are rich in oil and gas resources. Firstly, by analyzing the exploration development trends and oil and gas resource potential in oil and gas enrichment Sags such as Gaoyou and Jinhu, along with physical characteristics and main controlling factors of deep reservoirs, it was believed that the deep oil and gas reservoirs in Gaoyou and Jinhu Sags were mainly characterized by low to extra-low porosity and permeability. Secondary pore was the main pore type, while primary pore occurred locally. Overall, as burial depth increased, the proportion of primary pores gradually decreased. Subsequently, based on the relationship between pores and pore throats, deep reservoirs were classified into four types of pore-throat structures: large intergranular pores and wide lamellar throats; small intergranular pores and narrow lamellar throats; intragranular dissolution pores and narrow lamellar throats; and micropores and tubular throats. The physical properties of deep reservoirs were generally poor, with locally developed favorable reservoirs. The factors influencing the physical properties of deep reservoirs were complex. Analysis suggests that sedimentary factors, diagenesis, tectonic activity, oil and gas injection, and abnormal formation pressures all significantly affected the physical properties of deep reservoirs, although the controlling factors and their effects varied across different regions. Secondly, investigations were conducted on the occurrence conditions, main controlling factors, and accumulation models of deep oil and gas. The occurrence conditions of oil and gass suggested that oil and gas migration and accumulation were controlled by the pressure systems and physical properties between source rocks and reservoirs, as well as between different reservoirs. Oil and gas accumulation occurred when migration forces overcame migration resistance. Microscopically, pore-throat structure determined the fluid occurrence state and permeability. Larger throat radii, lower pore-throat radius ratios, and smaller tortuosities led to enhanced pore-throat connectivity and higher reservoir permeability. Macroscopically, pressure increase with oil and gas generation provided the driving force for oil and gas migration and accumulation. The magnitude and direction of source-reservoir pressure difference decided the favorable trends for oil and gas migration and accumulation, controlling their favorable areas. In terms of the main controlling factors for oil and gas enrichment, it was believed that oil and gas accumulation and enrichment in deep reservoirs were jointly controlled by source-reservoir configuration, pressure increase with oil and gas generation, fault-sandstone carrier system, and reservoir physical properties. Three accumulation models for deep oil and gas enrichment were established: stepped accumulation driven by combined abnormal overpressure and buoyancy, accumulation via fault-sandstone carrier system driven by abnormal overpressure, and accumulation of early-stage oil and gas injection followed by later-stage compaction. These models elucidated the enrichment mechanisms of deep oil and gass. Based on the above, to address exploration challenges such as unclear reservoir distribution, undefined enrichment zones, and low identification accuracy of effective reservoirs, three breakthrough technologies were developed: (1) A facies-controlled index method for deep reservoir classification was developed based on “facies-controlled index, porosity-permeability characteristics, pore structures, and diagenetic facies”. Reservoir classification criteria were formulated, categorizing reservoirs into four grades. Effective reservoirs in deep layers were mainly grades Ⅱ and Ⅲ. The distribution of effective reservoirs in the deep layers was evaluated across key stratigraphic intervals, revealing the graded distribution of reservoirs in deep zones of the first and third member of Funing Formation, the third submember in the first member of Dainan Formation in Gaoyou Sag, and the second member of Funing Formation in Jinhu Sag. The favorable areas of effective reservoirs in the deep layers of each stratigraphic system in each Sag were finally determined. (2) Through the analysis of deep oil and gas enrichment mechanisms, and according to the dynamic conditions of oil and gas injection, models for calculating reservoir potential energy, fluid potential, and source-reservoir pressure differences were established. Subsequently, a model for calculating the reservoir injection potential energy index were established based on the above models. Finally, the obtained reservoir injection potential energy index was used to assess the probability of oil and gas accumulation, providing technical support for the selection of favorable oil and gas accumulation zones in deep layers. (3) Subaqueous distributary channels and beach-bar sand bodies were effective reservoirs for deep oil and gass. To address the challenge of effective reservoir prediction in thin sandstone-mudstone interbeds within favorable oil and gas accumulation zones in selected deep layers, an integrated technical suite for effective reservoir prediction was developed. This technique, tailored to different sand body types such as channels and beach bars, integrated pre-stack and post-stack multi-attribute analysis. It leveraged geological, petrophysical, seismic, statistical, and other disciplinary theories to provide a comprehensive approach to reservoir prediction. Based on the distinction between sandstone and mudstone, this suite included six techniques for reservoir prediction: effective reservoir modeling based on petrophysical analysis, post-stack multi-parameter inversion constraint method, pre-stack and post-stack joint inversion method, seismic attribute threshold analysis method, seismic multi-attribute neural network prediction method, and SP curve reconstruction for acoustic curve. These techniques collectively improved the prediction accuracy of effective reservoirs in deep layers. These research findings provide theoretical guidance and technical support for the expansion of deep oil and gas exploration. Significant exploration progress has been made in deep layers such as slope zones, fault zones, and deep sag zones, enabling the expansion of deep oil and gas exploration. In the future, the research directions for addressing challenges in deep oil and gas exploration are clarified, which are continuing to consolidate and expand deep exploration to support the increase in oilfield reserves and production.

With the increasing difficulty in oil and gas development and insufficient replacement of resources, traditional development of oil and gas reservoirs faces multiple challenges, requiring intelligent analysis solutions for enhanced development efficiency. This study focused on the demand and application scenarios for efficient development in conventional oil and gas reservoirs and shale gas reservoirs and proposed an innovative intelligent technology for oil and gas development based on multi-model approaches. It enabled decision-making of production and efficiency allocation, comprehensive abnormal situation awareness, and intelligent balanced injection-production optimization. This effectively promoted the intelligent exploitation of reservoir resources, providing technical support for balanced injection-production and efficient development in multilayered complex waterflood reservoirs. A pressure prediction and capacity factor analysis technology for shale gas reservoirs was developed, along with an abnormality warning mechanism to push alerts about abnormal factors and their root causes. This achieved a transition from post-event analysis to early warning and pre-emptive intervention, thereby supporting the efficient development of gas reservoirs. Breakthroughs were made in establishing a multi-modal self-diagnosis and evaluation technology for oil wells, achieving intelligent diagnosis of pumping well operating conditions, self-diagnosis and intelligent evaluation of electric pumping well conditions, and real-time calculation of dynamic fluid levels in oil wells. These supported measure formulation, enabled refined management of oil wells, and made injection-production adjustments more timely and accurate, effectively improving the production time ratio of oil wells. The integrated technology application supported developing a new operational model featuring “comprehensive awareness, integrated coordination, early warning, and analysis and optimization” for the dynamic management and control of oil and gas reservoirs. These research technologies have been widely promoted among upstream companies of Sinopec, with practical application focusing on multi-model oil and gas development technologies. This study offers new ideas and technical approaches to address key challenges in the efficient development of oil and gas reservoirs, driving the digital and intelligent transformation of the oil and gas sector and facilitating the efficient and high-quality development of oil and gas fields.

The Tarim Basin serves as the major area for deep and ultra-deep oil and gas exploration and development. A significant breakthrough has recently been achieved in the exploration of ancient buried hill-type oil and gas reservoirs within the Cambrian System of the Paleozoic strata in well Tuotan 1, Kuqa Depression, Tarim Basin. Due to the ancient geological age and complex reservoir geology, systematic studies on oil and gas accumulation process and fluid evolution in this area remain insufficient. In this study, methods including biomarker analysis, petrological analysis, in-situ micro-area trace element and strontium isotope analysis, and fluid inclusions were used to determine the fluid origins of vein formation and the timing of multiple-phase of oil and gas charging in the dolomite reservoirs of the Xiaqiulitage Formation. The results revealed that the dolomite reservoirs in Xiaqiulitage Formation, well Tuotan 1 primarily developed two phases of calcite veins that filled fractures and dissolution pores. The first phase of calcite originated from deep, strontium-rich fluids, while the second phase of calcite veins derived from seawater. Two phases of oil-bearing fluid inclusions were predominantly developed within the second-phase calcite veins, comprising secondary blue-white fluorescent oil inclusions and secondary green fluorescent oil inclusions. The integration of fluid inclusion thermometry with single-well burial history reconstruction revealed that the first-phase blue-white fluorescent inclusions recorded oil and gas accumulation during the deposition of the Neogene Jidike Formation (23-20 Ma), while the second-phase green oil inclusions recorded oil and gas accumulation during the deposition of the Neogene Kuqa Formation (5-3 Ma). Oil-source correlation analysis indicated that the two phases of crude oil in the reservoirs of Xiaqiulitage Formation were derived from mixed contributions of lacustrine source rocks in the Triassic Huangsanjie Formation and Jurassic Qakmak Formation. The new findings from well Tuotan 1 in Kuqa Depression demonstrate that ancient strata in the foreland region of the Tarim Basin still retain favorable conditions for large-scale oil and gas accumulation, making buried hill-type oil and gas reservoirs a promising frontier for increasing reserves and production in Kuqa Depression.

The Sichuan Basin has rich resources of tight sandstone gas. Currently, research on the pore evolution of ultra-deep, ultra-tight sandstone reservoirs in the eastern slope of the western Sichuan Depression is relatively scarce. Using core observation, cast thin section identification, scanning electron microscopy, carbon-oxygen isotope analysis, and homogenization temperature of fluid inclusion, combined with burial history and thermal history, the coupling characteristics of pore evolution and oil and gas charge in the ultra-deep, ultra-tight sandstone reservoirs in the second member of Xujiahe Formation (hereinafter referred to as Xu 2 member) on the eastern slope of the western Sichuan Depression were clarified. The Xu 2 member reservoir is mainly composed of lithic sandstone and lithic quartz sandstone, with authigenic quartz and carbonates as the primary cementing materials. The storage space is dominated by intragranular pores. The densification period of the reservoir varies among different submembers. The upper submember is less resistant to compaction due to the presence of higher plastic materials like mudstone clasts, and it became compacted during the Middle to Late Jurassic. Subsequently, under continuous deep burial and the dual destructive effects of pressure dissolution and quartz, the middle and lower submembers became compacted during the Late Jurassic. At the end of the Cretaceous, tectonic uplift led to the formation of fractures that promoted the dissolution of the middle and lower submembers, increasing the reservoir porosity to around 5%, with a more significant increase in permeability. There were two main periods of oil and gas charge. The upper submember had a poorer coupling relationship, with early densification that was unfavorable for oil and gas charge and natural gas accumulation. In contrast, the main oil and gas charge period for the middle and lower submembers occurred prior to the densification of the reservoir, which was favorable for natural gas accumulation and reservoir formation. The Xu 2 member on the eastern slope of the western Sichuan Depression exhibits three “sweet spot” reservoir development modes: ancient trap+source fracture superposition, ancient trap+internal source rock+late fracture superposition, and ancient trap+source fracture+late fracture superposition. The study provides examples and theoretical guidance for understanding the evolution-oil and gas charge coupling characteristics of deeply buried ultra-tight sandstone reservoirs.

The southeastern Sichuan region is characterized by complex tectonic structures. The shale gas reservoir from the first member of the upper Ordovician Wufeng Formation to the Lower Silurian Longmaxi Formation is buried at considerable depths, which significantly affects the rock mechanical properties. However, systematic studies remain limited. This study focuses on the deep shale gas reservoir in the Lintanchang area of southeastern Sichuan. A series of mechanical experiments, including triaxial compressive tests, acoustic wave velocity measurements, tensile strength tests, and fracture toughness tests, were carried out. Based on the results of these multi-mechanical experiments, the rock mechanical properties of shale samples were analyzed, and a vertical mechanical property profile for a single well was established. With increasing temperature and pressure, the residual stress after fracture, Young’s modulus, and Poisson’s ratio of the deep shale samples showed an upward trend. The post-peak stress-strain curves exhibited more pronounced fluctuations. Acoustic wave velocities at the plunging end of the Lintanchang anticline were lower than those at the flanks. Young’s modulus and Poisson’s ratio values, corrected using a dynamic-static linear transformation, exhibited improved accuracy. The maximum load borne by the deep shale samples was less than 10 kN. Type Ⅰ and Type Ⅱ fractures displayed notable differences in propagation characteristics, and the degree of fracture penetration was greatly affected by sampling direction. The vertical mechanical profile of well T4 revealed that the bottom section of the first member of the Wufeng-Longmaxi Formation has higher Young’s modulus, lower Poisson’s ratio, and stronger brittleness, while the compressive and tensile strengths, as well as the fracture toughness index, remain relatively low. These mechanical properties show a weak compressive-tensile state, providing favorable conditions for reservoir stimulation. Thus, this interval represents an optimal target for future exploration and development.

The deep Permian Maokou Formation in the Penglai area, central Sichuan, is located in the Sichuan Basin. It is a sedimentary formation primarily composed of carbonate rocks, with dolomite being the main lithology. With good reservoir properties, it represents an important oil and gas reservoir in the Sichuan Basin. However, due to characteristics such as deep burial, thin reservoirs, strong heterogeneity, minimal impedance contrast with surrounding rocks, and weak reflection signals, seismic prediction becomes challenging. Conventional frequency enhancement processing either fails to identify thin reservoirs or results in a large area of coherent seismic events, making seismic prediction of thin reservoirs in this region difficult. Therefore, the application of “high-fidelity and high-resolution” processing technology for identifying thin reservoirs in the Maokou Formation was investigated. In response to the adverse factors such as deep burial, weak signals, thin reservoirs, and small impedance contrast with surrounding rocks in the Maokou Formation, research on weak-signal processing techniques for deep carbonate formations was conducted. In addition, the “high-fidelity and high-resolution” processing technology involving the concept of “protecting low frequencies and enhancing high frequencies” throughout the processing workflow was proposed. Methods such as pre-stack fidelity denoising, high-frequency residual static correction, multiple-wave suppression, pre-stack time migration in the Offset Vector Tile (OVT) domain, anisotropic correction, and frequency enhancement based on compressed sensing were studied to highlight the weak reflection signals of the Permian dolomite reservoirs. The research results effectively identified favorable reservoirs in the Maokou Formation as discontinuous, medium-to-strong amplitude reflections, with a well-seismic calibration match rate of 100%, thereby achieving effective identification and precise characterization of heterogeneity of thin dolomite reservoirs in the Maokou Formation. Based on the new findings, the drilled well PY001-H1 successfully reached high-quality reservoirs. Therefore, the results demonstrate that the studied “high-fidelity and high-resolution” processing technology is beneficial for deep reservoir prediction by improving seismic data resolution, amplitude preservation, heterogeneity analysis, and weak signal recovery.

Key Technical Descriptions

1. Pre-stack Fidelity Denoising Technology

Fidelity processing aims to preserve both amplitude and phase integrity. The current approach primarily employs the “six-step method” for denoising in the F-X, F-K, and Tau-P domains, which involves classification and segmentation by time, frequency, domain, step, and region. The principle of fidelity ensures that the chosen modules protect effective signals while maintaining relative amplitude relationships, particularly preserving low-frequency signals and improving the signal-to-noise ratio of weak high-frequency signals.

The data in this area is primarily affected by impulsive noise, surface waves, and linear noise. While methods for suppressing impulsive and surface waves are well-established, this study used frequency-domain suppression and localized surface wave suppression to maintain the original data’s frequency range. Due to wide-azimuth acquisition, residual surface waves and linear noise often remain at non-vertical offsets. In these cases, cross-spread domain suppression was applied post-static correction. This method considers interference wave frequency, apparent velocity, and non-vertical offsets for effective suppression.

2. Multiple-Wave Suppression Technology

A combination of Radon transforms and curvelet transform achieved effective suppression of interlayer multiples. Specifically, high-precision Radon transform was used to obtain multiple models, enhancing signal identification during curvelet transform. The curvelet transform better differentiates energy by frequency, dip, and position. By controlling the strength of simulated multiples through thresholds and applying adaptive subtraction, this approach improves multiple-wave suppression and enhances data quality for low signal-to-noise ratio datasets.

3. Compressed Sensing Frequency-Expansion Technology

Compressed sensing is a novel signal sampling theory. The method used here employs a robust compressed sensing spectral inversion algorithm. It determines initial reflection coefficients using a thin-layer matching pursuit algorithm and then performs post-stack sparse inversion based on the L0-norm compressed sensing theory. The final reflection coefficient model is obtained by applying regularization. Subsequently, wavelet decomposition and high-frequency wavelet replacement are conducted to expand the high-frequency spectrum while maintaining amplitude and fidelity, significantly improving seismic data resolution.

Application Results

The test area spans 200 km², using an observation system with 24 lines, 7 sources, 270 receivers, and 180-fold coverage. The bin size is 20 × 20 meters, with a maximum offset of 6 332.46 meters and an aspect ratio of 0.62, representing typical high-density and wide-azimuth acquisition. The raw data exhibits high noise levels, low dominant frequencies in deep layers, and narrow frequency bandwidths. Interferences include surface waves, impulsive noise, interlayer multiples, and anisotropy effects. After applying “Double-High Processing,” multiple-wave interferences were eliminated, and the quality of gathers significantly improved. Well-to-seismic profiles achieved good alignment, yielding favorable results.

For example, well PY1, with a burial depth of 6 040 meters and a reservoir thickness of 7 meters, showed a weak reflective base on synthetic seismograms and seismic profiles, with consistent matching between synthetic records and seismic waveforms. Clear reservoir characteristics were identified. Following these advancements, a new development well was drilled to a depth of 6 103 meters. In the second member of the Maokou Formation, a dolomite reservoir was encountered with a slanted thickness of 23.1 meters, a vertical thickness of 8.5 meters, and an average porosity of 3.8%. This high-quality dolomite reservoir achieved excellent drilling results.

In recent years, basement gas reservoirs in Qaidam Basin have demonstrated significant potential for exploration and development. The Kun 2 block in Kunteyi gasfield, as an ultra-deep basement gas reservoir, poses significant challenges for reservoir prediction and favorable area selection due to its complex internal geology, strong heterogeneity, and dual-porosity characteristics of fractures and dissolution pores. By integrating geological, logging, seismic, and production data, this study developed an innovative integrated method combining “well-seismic integration, static-dynamic fusion, and multi-attribute synergy” to systematically characterize reservoir characteristics and predict natural gas accumulation zones, aiming to reveal the spatial distribution of ultra-deep basement reservoirs and provide guidance for the optimization of well placement. The results showed that: (1) The basement reservoirs in the Kun 2 block primarily consisted of granitic gneiss, with storage spaces characterized by a dual-porosity system of fractures and dissolution pores. The fractures exhibited a network-like development and were distributed in NE-SW trending bands in the plane view. Lateral heterogeneity was significant. The fracture densities ranged from 3 to 10 m^-1, the average fracture porosity was about 0.015%, and the matrix porosity ranged from 1.8% to 6.8%. Overall, this demonstrated tight and low-permeability characteristics. (2) The development of dissolution pores was fault-controlled, primarily distributed along Kun 1, North Kun 2, and North Kun 101 faults. These faults formed fracture-pore coupled reservoirs. The interval 100-300 m below the top of the basement was a concentrated development zone, with the maximum reservoir thickness reaching up to 200 m. (3) The innovative integration of maximum likelihood attributes and structure tensor-acoustic impedance inversion technologies achieved high-precision characterization of the spatial distribution of fractures and dissolution pores. The prediction of maximum likelihood attributes revealed that high-angle fractures were mainly located on the upthrown side of faults, exhibiting an 85% consistency rate with imaging logging results. Additionally, the structure tensor-acoustic impedance inversion revealed that zones of dissolution pore development aligned closely with fault orientations, thereby validating the controlling mechanism of fault activity on dissolution process. (4) Based on reservoir classification and evaluation criteria, along with seismic prediction and dynamic production data, this study proposed a reservoir development model of “fault-controlled fractures, fracture-controlled pores” for the first time, indicating structurally high positions on upthrown side as the core zones of natural gas accumulation. Five favorable areas for natural gas accumulation were selected, including four on the upthrown side and one on the downthrown side. Among them, the NE-SW strip zones on both sides of the North Kun 2 Fault were identified as the optimal target areas.

Accurate interpretation of well logging data is crucial for the evaluation of reservoir fluid properties in oil and gas exploration. Conventional well logging methods rely on petrophysical models that correlate parameters such as porosity, permeability, and oil and gas saturation with reservoir fluid properties to achieve reservoir classification. However, complex geological conditions often lead to issues such as anomalies, multi-factor coupling, and ambiguous fluid boundaries in well logging data. These challenges limit the adaptability of conventional methods and bring uncertainties in interpretation results. To improve the accuracy of reservoir fluid evaluation, this study incorporated cloud model theory into conventional well logging evaluation and proposed an evaluation method for reservoir fluid based on a 2D cloud model. The method selected porosity and gas saturation as key logging parameters and utilized cloud models to process the fuzziness and randomness in well logging data, thereby establishing a mathematical model for reservoir fluid classification. First, a 2D cloud model for well logging evaluation was derived based on cloud model theory, with clarified geophysical significance assigned to its mathematical parameters (expectation, entropy, and hyper-entropy). 2D cloud diagrams of the reservoir were generated using a cloud generator. Subsequently, similarity analysis was applied to quantitatively classify reservoir types, enhancing interpretation accuracy. To validate the effectiveness of this method, well logging data from the Kuqa Depression in the Tarim Basin were used for application analysis, with results compared with those obtained from conventional methods, cloud model evaluation, and well testing. The results showed that the proposed method accurately characterized reservoir fluid properties in complex reservoirs. Compared with conventional methods, the 2D cloud model not only provided qualitative classification of reservoir types but also quantified uncertainties in fluid properties, thus improving the stability and reliability of evaluation results. The findings indicate that the reservoir fluid evaluation method based on 2D cloud model effectively reflects reservoir fluid characteristics and exhibits strong adaptability in complex reservoir environments. The final evaluation results demonstrate strong consistency with well testing results, verifying the method’s feasibility and effectiveness. As a valuable supplement to conventional well logging interpretation, this method provides a new approach for improving the accuracy of well logging data interpretation and optimizing fluid property identification in complex reservoirs.

The Upper Triassic Xujiahe Formation in the western Sichuan Depression, Sichuan Basin is an important area for the increase in reserves and production of tight sandstone gas (hereinafter referred to as “tight gas”) in the Sichuan Basin. In practical production, high-yield and stable production wells are highly correlated with the dense development of fractures. Fractures provide pathways and spaces for gas migration and storage, and whether fractures develop is a key factor restricting the formation of high-quality reservoirs. To evaluate the “sweet spot” enrichment area of the Xujiahe Formation gas reservoir, fracture development characteristics are identified and an effective fracture recognition method is established based on core observation, logging data, and intelligent algorithms. The research suggests that structural fractures, diagenetic fractures, and overpressure fractures all develop in the study area. The structural fractures are mainly divided into three phases: Phase 1 (NW-SE orientation) predominantly develops low-angle fractures, with occasional high-angle fractures; Phase 2 (NNE-SSW orientation) mainly develops high-angle fractures; Phase 3 (E-W orientation) predominantly develops high-angle fractures. The fracture segments in the tight gas reservoir display characteristics of low density, high neutron density, high sonic time difference, and positive amplitude differences in deep and shallow lateral resistivity. The conventional logging data with fracture and non-fracture labels were normalized, and machine learning algorithms were applied for fracture intelligent prediction. The F1 scores for the K-nearest neighbors (KNN), support vector machine (SVM), extreme gradient boosting (XGBoost), and random forest algorithms were 0.65, 0.83, 0.88, and 0.91, respectively. It was found that the random forest algorithm demonstrated strong robustness and anti-interference capabilities, with higher prediction accuracy and efficiency compared to the other three algorithms. Additionally, to balance computational efficiency and accuracy, the genetic algorithm was selected as the optimization algorithm for hyperparameter tuning, outperforming grid search, Bayesian optimization, and particle swarm optimization algorithms. Shapley Additive Explanations (SHAP) were used to calculate the contribution of different influencing factors to the predictions. It was found that the sonic time difference, neutron density, and compensated density were the main logging curves influencing prediction accuracy. The fracture density exhibited a clear spatial distribution pattern, decreasing from the southwestern part to the northwestern part of the Sichuan Basin. The research results can provide a practical and feasible intelligent prediction model for the fracture “sweet spot” zone in tight gas reservoirs in the western Sichuan Basin, laying the foundation for increasing reserves and production of tight gas.

The third submember of the first member of Dainan Formation in the deep layers of Gaoyou Sag, Subei Basin, which overlies high-quality source rocks of the fourth member of Funing Formation, serves as a potential replacement for oil and gas resources. However, due to its deep burial depth, numerous failed wells, and limited structural reservoir traps, it has long been perceived as “difficult for accumulation, unpromising, and unprofitable”. To clarify the key factors for oil and gas accumulation and the exploration potential of the third submember of the first member of Dainan Formation, using drilling, well logging, mud logging, experimental data, and seismic data, fundamental studies were conducted on multiple aspects, including sequence stratigraphy, sedimentary systems, reservoir-seal combination, trap types, and main controlling factors of oil and gas accumulation. The results showed that the third submember of the first member of Dainan Formation was the first sedimentary strata at the early stage of the transition from fault sag to fault subsidence in Gaoyou Sag. Its unique stratigraphic development position endowed it with oil and gas accumulation characteristics of “near-source sealing, northern delta and southern fan, dual pore-fracture reservoirs, and dual control on reservoirs”. Specifically, it was manifested in six aspects: (1) The top of the third submember of the first member of Dainan Formation was characterized by stable transgressive lacustrine mudstone, serving as an independent oil and gas accumulation unit. (2) Underlying the third submember of the first member of Dainan Formation, the fourth member of Funing Formation was located within the mature source rock zone, making it the most oil and gas-rich submember in Dainan Formation. (3) A large delta developed in the northern gentle slope and various types of fan bodies in the southern steep slope. The sand body development showed an east-high-west-low distribution pattern. (4) In addition to structural traps, four types of subtle traps developed abundantly in large scale. (5) Two types of reservoir spaces—porosity and fractures—developed. (6) Lateral sealing and effective reservoirs were the main controlling factors for reservoir formation. The findings from the research brought two major shifts in exploration strategies for this stratigraphic sequence, identified exploration directions, and led to successful drilling of multiple exploration wells. This promotes the third submember of the first member of Dainan Formation in Gaoyou Sag to become an important resource replacement area in Subei Basin.

Helium is a rare inert gas with indispensable applications in defense, aerospace, and medicine. However, helium resources available for use in China are extremely limited. To date, no independently accumulated helium resources have been found. Helium is primarily found in two forms: natural gas-associated and geothermal water-dissolved. This study focused on two typical basins—the Hangjinqi area in the northern Ordos Basin and the Weihe Basin—to investigate the genesis of helium. Helium isotope mass spectrometry analysis, rock radioactive element analysis and other methods were conducted to test the assgciated gas, core samples and potential helium source rock in the surrounding areas of the study area. The results show that helium in the Hangjinqi area in the northern Ordos Basin is typically crust-derived. While in Weihe Basin, high volume fractions of mantle-derived helium (up to 6.959%) were detected near deep-seated faults penetrating the basement, such as the Baoji-Xianyang fault and the Piedmont Fault of the Qinling Mountains. Both basins are located on the southwestern margin of the North China Plate and share a basement composed mainly of Archean-Proterozoic metamorphic-granite complexes, which serve as the main source rocks of helium formation. In addition, the main source rocks for helium gas in the Weihe Basin also include the uranium-rich granites of the Yanshanian period around the periphery and the concealed granitic bodies of the same period in the deep part of the basin. Due to the low mass fractions of U and Th elements or the low helium gas content of the desorbed gas in the basement sedimentary rock complexes, they cannot be regarded as the main source rocks for helium gas. The formation, migration and accumulation of helium gas in both areas are controlled by the source rocks and faults, and are closely related to the distribution of deep-seated fault zones. These findings provide a scientific basis for the further exploration and development of helium resources in the Weihe and northern Ordos basins.

Under the influence of the ultra-deep, ultra-high temperature, and ultra-high pressure reservoir formation and control mechanism, stratum fluid in the Shunbei ultra-deep fault-controlled condensate gas reservoir exhibits complex phase characteristics of supercritical condensate gas. The impact of the complex phase evolution behavior on the development dynamics is an urgent issue to be addressed in the development process of the Shunbei ultra-deep fault-controlled condensate gas reservoir. Using the supercritical condensate gas with high condensate oil content from the Shunbei No. 4 fault zone as the subject of study, high-temperature and high-pressure visual experimental observation methods were first used to study the near-critical condensate oil and gas fluid’s critical opalescence, non-equilibrium phase transition, mist retrograde condensation sedimentation, critical slow-down phenomenon, and special phase evolution behavior such as fluid stratification in the retrograde condensation process. Subsequently, the non-equilibrium phase evolution characteristics of near-critical condensate gas fluid under high-temperature and ultra-high pressure conditions were analyzed, revealing the impact of non-equilibrium phase transition and seepage on early-stage mist retrograde condensation, sedimentation and relaxation slow-down phenomenon during gas well depletion, ultimately affecting the recovery degree of condensate oil. The relaxation time for mist condensate oil gravitational settling from the dew point pressure to the maximum retrograde condensation pressure in the PVT (pressure-volume-temperature) apparatus could reach 1 193 s, which when scaled to the deep fracture-cavity flow space of the Shunbei condensate gas reservoir, could correspond to 7 026 s. By reasonably controlling the production rate, the recovery degree of mist retrograde condensate oil could be increased by 4.99%. Based on long-core non-equilibrium seepage experiments, it was found that reasonably controlling the production rate could increase the recovery degree of retrograde condensate oil by 7.14%. Combining the the production curve patterns of typical gas wells in the Shunbei No. 4 zone, the influence of non-equilibrium phase transition and mist retrograde condensation sedimentation relaxation effect on condensate oil recovery degree during the retrograde condensation stage was explored. Actual production data showed that the current condensate oil recovery degree was more than 5% higher than that of natural gas. The developed high-temperature and high-pressure in-situ phase observation system has been successfully applied to ultra-deep gas reservoirs in Tarim Basin and Sichuan Basin, and can provide a reference for the analysis of the development dynamics and the adjustment of development strategies for the Shunbei ultra-deep condensate gas reservoir.

During the development of middle and deep gas reservoirs in South Sichuan, conventional reservoir engineering methods—such as fracture propagation, stress-induced analysis, and numerical simulation—render productivity prediction of infilling wells laborious and ineffective in addressing variations in production capacity across different production stages, with stringent application conditions. In order to quickly and accurately predict the production capacity of infilling wells, this study classifies the “three-stage” declining trend observed in the production pressure curves of existing wells into: (1) A drastic decline period, regarded as the initial water production stage; (2) a rapid decline period; and (3) a slow decline period, both considered part of the later gas production stage. The Grey Wolf Optimizer(GWO) algorithm, a fast optimization algorithm with adaptive capabilities and an information feedback mechanism, is applied for hyperparameter optimization of the Long Short-term Memory (LSTM) neural network. Two stage-specific models were constructed, with the number of hidden layer neurons, dropout rate, and batch size determined by the optimal solutions obtained via GWO. The number of iterations was selected based on the loss curve and performance metric curve, while a linear warm-up strategy was used to dynamically adjust the learning rate, facilitating high-speed training and the formation of a staged productivity prediction model. Example studies show that the GWO-optimised LSTM neural network model achieves rapid convergence with a preset learning rate of 0.002 and 450 iterations, ultimately reaching a performance index of 0.923. Compared to the conventional LSTM neural network model, the average absolute errors during the early and later stages are reduced by 1.290 m³/d and 0.213 × 10⁴ m³/d, respectively. Compared with numerical simulation fitting results, the average absolute error in gas production prediction is reduced by 0.24 × 10⁴ m³/d. Therefore, the improved LSTM neural network model demonstrates excellent performance in capacity prediction across different production stages, and the stage-specific productivity variations in infilling wells within middle and deep shale gas reservoirs in South Sichuan. This provides a theoretical foundation for productivity prediction methods of infilling wells.

Shale gas production has exhibited high initial yields followed by a rapid decline. This rapid decline suggests that early-stage production rates were likely excessive, accelerating the depletion of reservoir productivity and adversely affecting the Estimated Ultimate Recovery (EUR) of shale gas wells. Therefore, accurate and reasonable productivity evaluation plays a key role in ensuring stable reservoir development. To identify the challenges of current shale gas productivity evaluation approaches and explore feasible solutions, this study analyzed the unique connotation of shale gas productivity and reviewed recent progress in three approaches: (1) Analytical solution methods of flow equations; (2) numerical simulation methods of flow equations; and (3) artificial intelligence (AI)-based methods. The results revealed that shale gas productivity was highly stage-dependent, with substantial variations in dominant controlling factors, flow mechanisms, and flow regimes across different production stages. Early and late production stages exhibit distinct controlling factors, leading to differentiated perspectives across the various evaluation methods. The analytical solution method relied heavily on a deep understanding of flow mechanisms. Numerical simulation methods require extensive, high-quality datasets and strong reservoir engineering expertise for validation. AI-based methods faced challenges such as high opacity, limited interpretability, and poor generalization. Based on these findings, future research should focus on integrating shale gas flow mechanisms at both micro and macro scales. Emphasis should be placed on the multidimensional integration of geological modeling, stress-petrophysical evolution, fracture propagation, multiphase flow numerical simulation, and decline analysis, enabling more comprehensive productivity characterization. In addition, further work is needed to incorporate mechanism-informed constraints into machine learning algorithms, enhance model transparency through causal inference, and improve interpretability. These advancements aim to avoid the limitations in existing productivity evolution methods and support the development of robust and rational shale gas productivity evaluation models and methods, providing theoretical guidance for accurate well productivity prediction, production stabilization, and efficient resource development.

CO₂ flooding is an important method to enhance oil recovery in low-permeability reservoirs. However, due to the heterogeneity of the reservoir, long-term CO₂ injection can easily lead to CO₂ gas channeling, leaving a large amount of residual oil in the reservoir, which severely impacts the effectiveness of CO₂ flooding. CO₂-water-alternating-gas flooding (CO₂ WAG) is an effective technique to suppress CO₂ gas channeling in low-permeability oilfields. During the implementation of CO₂ WAG, numerous injection parameters such as injection rate, slug size, and gas-water ratio are involved. Unreasonable injection parameters make it difficult to achieve improved oil recovery. Traditional reservoir numerical simulation methods for determining optimal injection parameters are time-consuming, labor-intensive, and costly, and may be unfeasible in large oilfields with complex multi-well injection parameter combinations. The hunger game search algorithm was introduced to optimize the injection parameters for CO₂ WAG, with the addition of chaotic mapping functions to enhance the randomness and diversity of initial injection parameter values. This new approach formed an improved hunger game search algorithm based on chaotic mapping functions, allowing for collaborative intelligent optimization between the algorithm and reservoir simulation software. This method enhanced the accuracy and efficiency of CO₂ WAG injection parameter optimization for typical oilfields. Compared to the Logistic, Gaussian, and Singer chaotic mapping functions, the Tent chaotic mapping function resulted in more evenly distributed chaotic values and frequency distributions, making it a better choice for improving the hunger game search algorithm. The hunger game search algorithm improved by the Tent chaotic mapping function is an effective method for optimizing CO₂ WAG injection parameters. The optimal CO₂ WAG injection parameters derived from this approach lead to a cumulative oil production of 34.974×10⁴ m³, a 0.213×10⁴ m³ increase over the results from the Hunger Game Search algorithm, and 5.820×10⁴ m³ more than the current CO₂ WAG injection parameter scheme. This approach provides an effective technical solution for the efficient implementation of CO₂ WAG in the field.

As a critical component of Carbon Capture, Utilization, and Storage (CCUS) technologies, CO₂-enhanced oil recovery (CO₂-EOR) has been widely used both domestically and internationally. This technology not only improves oil recovery but also enables large-scale CO₂ sequestration. However, potential CO₂ leakage risks exist throughout the processes of CO₂ injection, displacement, sequestration, and production. Existing monitoring practices in domestic and international projects primarily focus on reservoirs and caprocks, with limited attention paid to systematic ecological environmental monitoring. CO₂-EOR development commenced in the Zhangjiaduo oilfield in 2014. As of now, a cumulative total of 195,300 tonnes of CO₂ has been injected, resulting in an incremental oil production of 51,600 tonnes. The oil recovery rate was improved by 15.22%, and the phase oil replacement ratio reached 3.78, indicating remarkable stimulation effectiveness. Based on the Zhangjiaduo CO₂-EOR and sequestration project, a comprehensive 3D monitoring system was developed, integrating multiple indicators across groundwater, soil, and atmosphere to enable real-time monitoring and early warning of CO₂ leakage. After over one year of continuous monitoring, the results showed that the CO2 mass concentration in Zhangjiaduo groundwater remained stable at about 5,712 mg/m³, with a near-neutral pH and stable electrical conductivity ranging from 1.343 to 1.347 μS/cm. The CO₂ mass concentration, pH, and conductivity in the soil also remained relatively stable. Atmospheric CO₂ concentrations at three different altitudes exhibited periodic fluctuations consistent with soil data, averaging between 730 and 780 mg/m³, which aligns with typical atmospheric CO₂ levels in low-latitude regions. These multi-parameter monitoring results indicate that no CO₂ leakage has occurred in the Zhangjiaduo oilfield to date. The successful application of this monitoring system has provided robust scientific support for the sustained development of the field. Moreover, it offers practical insights and references for environmental monitoring in similar projects, contributing to the safe and sustainable advancement of CO₂-EOR technologies.

With technological advancements, fibers now serve roles beyond proppant backflow prevention, including proppant transport, plugging, fracture morphology optimization, and other aspects, namely, fiber-network proppant fracturing technology. The fiber-based proppant transport and fiber temporary plugging technologies can effectively address issues currently faced by deep shale gas, such as proppant near-wellbore accumulation and insufficient temporary plugging effectiveness, thereby improving the effectiveness of volumetric fracturing stimulation. To this end, the study was conducted in a deep shale gas block in the southern Sichuan Basin, investigating fiber-based proppant transport and fiber temporary plugging mechanisms, as well as laboratory physical simulations to optimize and evaluate the performance of fiber materials. Based on the regional geological and engineering characteristics of the study area, fracturing software simulations were carried out to determine the hydraulic fracture width for deep shale gas. A field test plan was then developed, and the fracturing construction, flowback, plugging, and fracturing effectiveness of the test wells were monitored and evaluated. The research results indicated that fibers had strong proppant transport assistance and flexible bridging capabilities. By modifying the molecular structure of fiber materials and adding a certain amount of structural stabilizers, discontinuous cluster-like support structures can be formed, significantly enhancing the placement effect and conductivity of proppants. Based on fracture width simulation calculations, the hydraulic fracture width for deep shale gas is between 2 to 5 mm. By optimizing fiber types based on fracture width, proppant grain size, and concentration, full support of fractures can be achieved. Compared to conventional fracturing wells, the test wells with modified fiber + structural stabilizer for sand-carrying fracturing exhibited better production increase and proppant flowback prevention. Fibers can be used for temporary in-fracture plugging. During the construction process, the pressure response is evident, which may lead to excessively high pressure during subsequent operations, making proppant addition difficult. Optimizing the timing of fiber injection is beneficial for the subsequent overall sand addition process. Additionally, fibers can also be used to address the inter-well gas migration issue in deep shale gas wells by strengthening the temporary plugging of fracture openings and sealing natural fractures, thereby preventing further communication between hydraulic fractures and distant natural fractures. The study, based on the characteristics of deep shale reservoirs in the southern Sichuan Basin, has developed a set of performance indicators for fiber materials suitable for deep shale gas, including fiber length, stability, compatibility, and degradation rate. It also proposes a four-in-one fiber injection process and design method, focusing on “entry, distance, height, and prevention”. It provides strong support for the future economic development, technology optimization, and fracturing process adjustments of shale gas.

Marine carbonate oil and gas resources in the western Sichuan region of the Sichuan Basin are buried at depths exceeding 7 000 meters. Vertically, multiple hydrocarbon reservoirs exist, resulting in complex pressure systems where the coexistence of influx and loss may occur within the same open hole-section. When downhole complications arise, well control becomes challenging. In such cases, a contingency casing string must be run, which increases the number of casing intervals, prolongs the drilling cycle, and raises overall costs. To address this challenge, a targeted optimization of the wellbore structure was performed after setting the contingency casing. However, technical challenges persisted due to the coexistence of high- and low-pressure systems within a single open-hole section, and the presence of a narrow safe mud weight window. Based on a managed pressure and gas-venting density reduction process, and integrating formation gas seepage theory with wellbore flow dynamics, the migration patterns of natural gas in both the formation and annular space were analyzed. The research results showed that during the early stage of gas-venting density reduction under managed pressure, the gas influx rate declined rapidly, then gradually slowed and stabilized. This technique effectively released formation energy and reduced formation pressure, thereby helping to expand the safe mud weight window. The gas influx rate was identified as the main factor affecting well control safety. To ensure safe operations, the gas influx rate must not exceed the critical safe threshold. Based on both theoretical analysis and cost evaluation, the optimal duration for gas-venting density reduction was determined to be 10 days. Field applications were conducted in two wells targeting high-pressure formations in the Maokou Formation within the Shuangyushi Structure. Managed pressure and gas-venting operations successfully reduced the lower limit of the safe mud weight window by 0.16 g/cm³ and 0.40 g/cm³ respectively. These wells were drilled in combination with low-pressure reservoirs in the Qixia Formation. As a result, the casing program was simplified from six intervals to five, significantly reducing the drilling cycle and costs. This led to the development of a safe drilling technology for ultra-deep gas wells with complex pressure systems through managed pressure and gas-venting density reduction. The proposed method provides a valuable technical reference for wellbore structure optimization and safe drilling operations in similar ultra-deep, complex pressure environments.

Shale gas, an unconventional natural gas resource, has become an important supplement to global conventional oil and gas resources. With the increasing development of shale gas resources, deep shale gas reservoirs have emerged as key targets for exploration and production. These reservoirs are characterized by complex geological structures, high rock plasticity, and significant vertical and horizontal stress differences. Such conditions hinder the formation of complex fracture networks during hydraulic fracturing, often resulting in simple, narrow, and long fractures. The narrow width of these fractures significantly affects the settlement and migration of proppants, which in turn influences fracture conductivity and determines the effectiveness of reservoir stimulation. Therefore, investigating the settlement and migration behaviors of proppants in long narrow fractures is essential for the safe and efficient production of deep shale gas wells. Current experimental studies on proppant migration commonly use parallel-plate simulation devices made of organic glass. Research indicates that proppant settlement and migration are substantially influenced by viscous fluid drag, with the drag coefficient depending on factors such as particle shape, concentration, and flow rate. Additionally, proppant type, density, and concentration further affect proppant distribution. However, most existing studies are based on the fracture geometries of medium and shallow shale reservoirs, which differ from those of deep shale formations in both fracture width and suitable proppant size. To address this gap, this study employed a large-scale visualized simulation device to examine the settlement and migration of proppants in long narrow fractures in deep shales. The objective is to clarify the effects of different proppant properties and fracturing parameters on proppant distribution, thereby providing theoretical support for fracturing stimulation in deep shale reservoirs. The experimental setup included a fracture simulation device, a mixing unit, and a circulation system. The fracture simulation device was composed of interconnected organic glass plates, with adjustable fracture widths between 2-3 mm to replicate the fractures in deep shale. Slickwater fracturing fluids were prepared with three viscosities: 3 mPa·s, 6 mPa·s, and 9 mPa·s. Selected proppants included 40/70 mesh, 70/140 mesh, and 100/200 mesh quartz sand, along with 70/140 mesh coated ceramic proppants, representing micro-sized particles. A total of 11 experimental groups were designed to investigate the effects of fracturing fluid viscosity, injection rate, proppant concentration, proppant particle size, proppant type, and fracture width variation. Experimental results indicated that, compared with the wider fractures of medium and shallow shales, under the same conditions, long narrow fractures in deep shale promote the agglomeration of proppant particles, causing a rapid settlement near the inlet. This led to a reduced leading-edge slope of the sand bank and a smaller height difference between the front and rear of the sand bank compared to wider fractures. The overall proppant distribution tends to be more uniform and smoother. In long narrow fractures of deep shale, the proportion of terminal sand bank area to the total sand bank area increases with higher fracturing fluid viscosity and injection rate, while the effect of proppant concentration is relatively limited. Micro-sized proppants are more prone to settling at the far end of the narrow fracture and contribute to a more uniform overall distribution. Moreover, the contraction of fracture width has no significant effect on sand bank placement before contraction, but it hinders the flow and placement of proppant particles after contraction, resulting in decreased proppant settlement. Due to the high closure pressure in deep shale reservoirs, fractures are prone to closure, and the reduction in proppant settlement after fracture contraction further increases the difficulty of effective fracture support. This experimental study reveals the settlement and migration patterns of proppants in long narrow fractures in deep shale, providing a theoretical foundation for optimizing fracturing simulation strategies. The findings have practical significance for selecting proppant types and optimizing fracturing parameters to enhance the production efficiency of deep shale gas wells.