The abundant geothermal resources of the Haihu New District of Xining City are significantly constrained in their development and utilization, as the geothermal water is characterized by high salinity. This study aimed to investigate the hydrogeochemical characteristics and genesis of geothermal water in the Haihu New District by analyzing water chemistry data from five geothermal wells using traditional hydrogeochemical methods, statistical analysis, isotope analysis, and geochemical simulations. The findings revealed the chemical characteristics of the geothermal water and identified its recharge sources, elevation, circulation depth, and reservoir temperature. Representative reaction pathways were selected to simulate water–rock interactions along the geothermal water flow path based on the genetic model of geothermal water and the analysis of rock mineral compositions. This study examined the dissolution and precipitation characteristics of rock minerals, elucidating the chemical genesis of geothermal water in the district. The results showed that (1) the analyzed geothermal waters reveal a significant salinity level and a mildly alkaline nature, with Na+ as the dominant cation and SO42− and Cl− as the dominant anions. For this reason, these waters can be classified as Na‐SO₄•Cl waters. (2) The geothermal system in the study area was classified as medium to low temperature. Atmospheric precipitation infiltrates from the Laji and Laoye mountains, with recharge elevations ranging from 2910 to 2980 m. The reservoir temperature is estimated to range from 52.40°C to 70.45°C, with circulation depths between 1000 and 1600 m. (3) The primary sources of Na+ and Cl− in the geothermal water are halite dissolution and cation exchange, while SO42− primarily originates from gypsum dissolution, with additional influence from H2S oxidation and the common ion effect. This study provides a comprehensive understanding of the hydrogeochemical characteristics and genesis mechanisms of the geothermal system in the Haihu New District, offering critical insights for the effective and sustainable development of geothermal resources in the region.

Deep coalbed methane (CBM) is a crucial resource for ensuring energy security. Despite some successful localized deep CBM developments, the unclear understanding of gas content and gas occurrence state remains a key obstacle to the comprehensive development of deep CBM. This study utilizes data from pressure‐preserved coring and wireline coring gas content tests, isothermal adsorption tests, and well test temperature and pressure data to establish a methodological model. This model corrects the gas content obtained from wireline coring and determines the gas occurrence state. The gas content, including adsorbed and free gas content, and gas/water saturation were calculated, and the controlling factors were analyzed. The results reveal that the high values of total gas content and adsorbed gas content are concentrated in the southwestern part of the study area. The adsorption capacity of the coal, influenced by its degree of metamorphism, is identified as the primary factor affecting the total gas content and adsorbed gas content. Furthermore, the high values of free gas content are primarily concentrated at the northwestern edge of the study area. The main factors affecting the porosity difference of free gas are coal metamorphism type and inertinite content. Areas affected by magmatic thermal metamorphism and those with high inertinite content tend to have higher porosity. Additionally, pressure, rather than temperature, is identified as the main factor determining the density of free gas. These findings provide a relatively simple indirect method for obtaining deep CBM content and occurrence state, particularly for studying the free gas content in deep coal seams. This approach is aimed at offering theoretical support for the development of deep CBM in the middle Linxing block.

This research evaluates the performance of artificial neural networks (ANNs) and adaptive neuro‐fuzzy inference systems (ANFIS) in selecting well candidates for hydraulic fracturing (HF) in the Bach Ho oilfield, Vietnam. Traditional well selection often depends on expert judgment and deterministic criteria, which may be limited in uncertain and data‐constrained reservoir environments. To address this limitation, machine learning models are applied to improve decision‐making accuracy. A dataset of 41 wells was analyzed using permeability, porosity, skin factor, reservoir pressure, water cut, and reservoir thickness to predict post‐HF daily production rates. Both models were trained and evaluated using RMSE, MSE, MAE, and R2. The ANFIS model demonstrated superior accuracy, achieving an RMSE of 4.24, R2 of 0.93, and MAE of 4.24 on the training set. On the testing set, ANFIS achieved an RMSE of 40.44, R2 of 0.81, and MAE of 30.33, outperforming the ANN model, which recorded an RMSE of 40.43, R2 of 0.59, and MAE of 31.86. These results suggest that ANFIS is more effective in capturing nonlinear relationships and handling input uncertainties. The study presents a practical, interpretable tool for supporting petroleum engineers in prioritizing HF candidates, ultimately enhancing oil recovery and resource allocation in complex reservoir settings.

The remaining coal pillars and roof form an integral coal pillar–roof system (CPRS) that plays an important role in the safety of the room mining goaf. In this research, two different sets of parallel dual coal pillar–roof combinations (PDCRCs) were developed to model the CPRS. One set of PDCRC is formed by two‐component combinations featuring identical mechanical properties, whereas another set is constituted by two‐component combinations exhibiting distinct mechanical properties. Building upon this foundation, a sequence of uniaxial compression tests was carried out on PDCRC. These tests integrated laboratory experimentation and numerical simulation with the particle flow code (PFC). From both macroscopic and microscopic perspectives, the load‐bearing capacities, acoustic emission (AE) features, crack development processes, force chain evolution laws, and deformation features of the PDCRC were recorded. The results indicate that the initial failure of a specific coal can trigger and dominate the instability of its corresponding combination, thereby leading to a chain instability in the other combination and the entire system. For PDCRC composed of two combinations with identical mechanical properties, the two combinations share the external load equally and fail in coordination. Once any component combination loses its ability to withstand the external load, the other component combination and the entire system will immediately and synchronously lose their load‐bearing capacity. For PDCRC composed of two‐component combinations with distinct mechanical properties, the component combination with low strength first fails and loses its load‐bearing capacity, resulting in the synchronous transfer of the originally external load to the high‐strength component combination. Once the high‐strength component combination loses its load‐bearing capacity, the entire system becomes unable to sustain the external load simultaneously. The overall load‐bearing capacity of PDCRC with identical mechanical properties is approximately equal to the sum of the two‐component combinations, while that of PDCRC with distinct mechanical properties is less than the combined total. In summary, the premature instability of certain coal pillars serves as the primary initiating factor for the instability of the CPRS. When conducting stability assessments of room mining goafs, it is essential to adopt a holistic perspective to comprehensively evaluate the load‐bearing capacity of the CPRS as an integrated whole.

The blasting at a site can cause impact disturbances to an open‐pit mine slope. For further study the dynamic mechanical properties of rock masses in open‐pit mine slope, in this paper, the mudstone of an open‐pit slope in Inner Mongolia Autonomous Region of China was taken as research object. Through an indoor split‐Hopkinson impact test and a finite difference method and discrete element method coupling simulation (FDM‐DEM), the macro and micro impact mechanical response of mudstone under different impact velocities was studied. The results showed that under dynamic load, mudstone exhibited significant strain rate effects. The postpeak plasticity varied in exponentially increasing changes. The crack propagation process in mudstone can be divided into undamaged, initiation, propagation, and rupture stages. As the impact velocity increased, the initiation stage exhibited more microcracks, and the cracks opening in the rupture stage became larger. The 3D coupling numerical model can satisfy stress effectiveness during the dynamic impact process. During the impact process, microcracks increased sharply before the peak stress, and there was a strain lag between the maximum point of crack increment and the peak point of stress. A large number of internal microcracks developed during the postpeak stage, and the cumulative crack increment exhibited a reverse “Z” shape.

The Dengying Formation within Pengtan 1 well area in the Sichuan Basin is a vital gas reservoir for exploration and development. The reservoir is situated in a complex fault block structure characterized by multistage fault evolution, leading to a complicated distribution of tectonic fractures crucial for the accumulation and migration of oil and gas. This study establishes a geological model to describe the fault patterns observed in the region and conducts numerical simulations of the paleotectonic stress field. Moreover, we combine rock fracture criteria and strain and surface energy theories to predict tectonic fractures quantitatively. Our findings indicate that the tectonic fractures in the study area predominantly consist of shear fractures, with primary development of low‐angle and oblique fractures and, to a lesser extent, high‐angle fractures. These fractures generally exhibit trends in the north–northwest (NNW), northeast (NE), nearly east–west (EW), and nearly south–north (SN) directions. Most fractures formed during the Yanshanian–Himalayan period are identified as effective fractures. The maximum and minimum principal stress values recorded for the Himalayan period of tectonic activity were 150–180 and 120–150 MPa, respectively. Faults significantly influence the distribution of tectonic stress, and stress concentration usually occurs near the fault. A significant correlation exists between tectonic stress and burial depth, exhibiting lower stress levels at shallower depths. In addition, the linear density of fractures gradually decreases from the fault core to its periphery and further decreases to areas far away from the fault. In these three regions, fractures mainly develop in the order of high angle, oblique, and low angle. This study enhances our understanding of the fracture dynamics within the Dengying Formation, contributing valuable insights into the region’s geomechanical properties and potential hydrocarbon exploitation strategies.

China’s shale gas has undergone nearly 20 years of exploration; unconventional oil and gas geological evaluation theories and research methods have been greatly enriched, but how to quickly, conveniently, and accurately identify the sweet spots of shale gas is still puzzling many researchers. This study focuses on the black shale of the Wufeng–Longmaxi Formation in the southeastern edge of the Sichuan Basin; lithofacies classification, the relationship between lithofacies and depositional environments, and the correlation between lithofacies and shale gas–bearing capacity are discussed. At last, we have established the lithofacies classification criteria; the Wufeng–Longmaxi Formation deposited eight types of lithofacies, which the paleoenvironment during deposition evolved gradually from anaerobic environment to oxygen‐poor and oxygen‐rich environment. The black high‐carbon and high‐silicon shale lithofacies and the black carbon‐rich and silicon‐rich shale lithofacies are rich in organic matter, and they were deposited in high primary productivity, low terrigenous detritus input, and euxinic environment. The black medium‐carbon medium‐silica shale lithofacies and the black medium‐carbon and high‐silica shale lithofacies contain organic matter, which are deposited in medium primary productivity, middle terrigenous detritus input, and oxygen‐poor and low hydrodynamic environment. The gray–black low‐carbon low‐silicon clay‐rich shale lithofacies, the gray low‐carbon and high‐silicon shale lithofacies, and the gray–white low‐carbon and silicon‐rich shale lithofacies are poor in organic matter, which are deposited in a transitional environment of low primary productivity and oxygen poor–oxygen rich. In the analysis of the relationship between organic matter–rich black shale facies and sedimentary environment, it is shown that the enrichment of organic matter is positively correlated with the oxidation–reduction discrimination indicators Ni/Co, U/Th ratio of ancient oceans, and the evaluation indicators Babio and Ba/Al ratios of primary productivity. Only under the favorable sedimentary geochemical conditions and good preservation conditions can deposit lithofacies sections (zones). Based on the optimization of shale gas dessert section and the drilling of horizontal wells, the optimization of favorable black shale lithofacies types and the classification of shale gas dessert section are the key to shale gas exploration. The shale gas–bearing capacity is closely related to lithofacies. Black carbon‐rich silicon‐rich shale lithofacies and black high‐carbon high‐silicon shale lithofacies have the best gas‐bearing capacity and are favorable lithofacies.

Shale oil and gas resources are considered one of the most important strategic resources globally today. However, the matrix permeability of oil shale reservoirs is extremely low, it requires modification through hydraulic fracturing technology to realize their economic and effective development. Against this background, we focused on the oil shale in the Xunyi area of the Ordos Basin, employing the ABAQUS platform to simulate and investigate the characteristics of hydraulic fracturing fracture propagation in fracture‐developed oil shale reservoirs and the principal influencing factors. The results of the study show that the larger the angle between the natural fracture and the hydraulic fracture, the easier it is for the hydraulic fracture to pass through the natural fracture; the larger the elastic modulus of the matrix, the stronger the ability of the fracture to penetrate through the stratum, and the fracture morphology tends to be more narrow and long. The direction of fracture propagation tends to be in the direction of the geostress difference, and with the increase of the geostress difference, the degree of convergence of the direction of fracture propagation and penetration is greater. The higher the viscosity of the fracturing fluid, the wider and shorter the fracture tends to be, but it has minimal impact on the direction of fracture propagation. Increasing the fracturing fluid displacement can increase the fracture width and length and enhance the effect of the hydraulic fracturing modification. The research results are significant for the optimized fracturing design in oil shale reservoirs.

It is one of the important disasters faced by coal mine that roof energy accumulation leads to its advance failure and roadway failure. Identifying the position of roof energy accumulation can predict the position of roof advance failure and roadway deformation, so as to take preventive measures. Based on two generalized displacement beams, the accumulation law of the bending moment and energy density of the top coal wall under different loads, different thicknesses, and different cantilever lengths is investigated. The following conclusions are drawn: (1) Under different load conditions, the peak of the bending moment and energy density both appear at 10 m in front of the coal wall and rapidly decrease to 0 after reaching the peak and no longer change. The peak value of the bending moment increases linearly with the increase of the load, and the relation is M = −143.32q − 286.63. The peak value of bending moment changes exponentially with the increase of load, and the relation is Ue = 200.46e0.42q. (2) Under different thicknesses, the bending moment of the thickness to the rock layer has an irregular distribution at the peak value. When the thickness is 12.5 and 15 m, the change tends to be consistent, and when the thickness is 7.5 and 10 m, the bending moment of the roof is small when the thickness is 17.5 m. When the thickness is less than 17.5 m, the smaller the thickness is, the larger the peak value is, and the more advanced the peak value is. The smaller the thickness of the roof, the smaller the range of energy density accumulation. (3) Under different cantilever lengths, with the increase of cantilever length, the peak bending moment presents a linear increase, and the relationship is Me = −158.22 L + 137.4, and the range of bending moment accumulation increases with the increase of the roof cantilever length. With the increase of the cantilever length, the peak energy density of the roof increases exponentially, and the relationship is Ue = 3.5536e1.1067L, and the lead energy accumulation distance of the roof increases. (4) When the thickness of the roof is 10 m, the stress peak occurs more frequently within 5–15 m in front of the working face, which well confirms the correctness of the theoretical analysis.

The Hoek–Brown (H‐B) criterion is widely recognized as a standard in geotechnical engineering for assessing rock mass strength across various rock mass qualities. However, challenges arise in explicitly defining the Mohr failure envelope, particularly when the strength parameter “a” deviates from the conventional value of 0.5. This study investigates the compressive strength of rock masses in the Himalayas, particularly in the context of deep tunneling and slope stability, using the H‐B and Mohr–Coulomb (MC) criteria. Initially, the MC and H‐B criteria were combined while varying the angle of internal friction, revealing an inconsistent trend in friction angles regarding rock mass compressive strength. The relationship between tunnel depth, slope height, and rock mass compressive strength was then examined by combining equations involving RMR, RQD, and modified H‐B criteria. The combination of H‐B and MC resulted in lower rock mass compressive strength values, while noncombined equations yielded higher values. Incorporating the geological strength index (GSI) provided higher and more suitable compressive strength values. For the Himalayas, the suggested H‐B equations with GSI are recommended for both surface and subsurface excavations.