Abstract:The water-soaked strip coal pillar is subjected to water erosion softening caused by goaf water accumulation during long-term bearing process,which easily leads to varying degrees of damage and deterioration,exacerbating the creep failure of the coal pillar.To further investigate the long-term stability of water-soaked strip coal pillars,this article uses existing constitutive models and OpenGeoSys software to simulate and analyze the creep damage process of water-soaked strip coal pillars under multiple factors.The creep damage mechanism of water-soaked strip coal pillars is analyzed,and a targeted reinforcement method for water-soaked strip coal pillars is proposed.The research results indicate that:(1)the strip coal pillar is in a state of stress concentration for a long time,and under the softening effect of water erosion,the width of the plastic zone of the coal pillar gradually increases,and the degree of damage continues to intensify;(2)the creep damage of coal pillars exhibits a continuous expansion characteristic,with increased inclination angle,burial depth,coal thickness,goaf width,and decreased creep strength all accelerating damage expansion by intensifying stress concentration or expanding the stress concentration range;(3)the proposed concrete grouting and long anchor cable collaborative reinforcement technology can slow down or prevent the creep damage and expansion of coal pillars,and effectively enhance the stability of strip coal pillars.

Abstract:In order to reveal the permeability evolution law of gas-bearing coal under mining-induced stress,the deformation and permeability characteristics of coal under loading and unloading paths with different vertical and horizontal stress rise and fall ratios(4.75∶1,3.50∶1,2.25∶1)are simulated by true triaxial experiments.The research shows that the reduction of the relative unloading rate of horizontal principal stress can enhance the carrying capacity of coal and rock and increase the peak stress,a faster rate of relative unloading will cause significant changes in the horizontal strain of the coal body,leading to instability and failure of the coal body.The evolution of permeability exhibits three characteristic stages:in the initial stage,the increase of vertical stress causes the fracture to close,and the permeability remains stable or decreases;in the stage of fracture expansion,the vertical stress approaches the peak value and the permeability increases slowly;in the fracture coalescence stage,permeability rises sharply due to coal sample failure,with this phenomenon being particularly pronounced in damaged gas-bearing coal.Based on the coupling relationship between gas pressure and coal strain,a permeability prediction model with damage factor D and correction factor C was constructed.The calculation results of this model are in good agreement with the experimental data,effectively characterizing the dynamic response mechanism of permeability with respect to strain and gas pressure.

Abstract:Investigating the rapid initial desorption of gas from crushed coal is essential for accurately assessing the release of expansion energy during coal and gas outbursts.In this study,we developed an equivalent particle size model for gas desorption,based on the fractal particle size distribution of crushed coal.Through impact crushing experiments and gas desorption tests,we analyzed the relationship between the coal's firmness coefficient and equivalent particle size,and examined how particle size influences gas desorption volume.We also constructed an expansion energy model for the initially desorbed gas.The results show that the equivalent particle size for gas desorption increases with the firmness coefficient,reaching a plateau at approximately 0.5.The cumulative gas desorption volume decreases according to a power-law relationship with equivalent particle size across different time intervals,with fitting coefficients between 0 and 1 that approach zero over time.Among various single-pore diffusion models,the time-varying power-law diffusion model provided the best fit and most accurately predicted long-term desorption behavior.Notably,equivalent particle size has the greatest impact on the expansion energy of desorbed gas during outbursts.The expanison energy of desorbed gas increases gradually with the decrease in equivalent particle size,and then rises significantly once the equivalent particle size falls below 0.5 mm.

Abstract:Deep rocks are subjected to true triaxial stress conditions,where their deformation and failure characteristics are determined by the stress state.In order to study the failure modes and energy evolution laws of sandstone under different stress states,this study conducted loading tests on sandstone under different minimum principal stresses and monitored its acoustic emission signals.The stress-strain relationship and energy evolution laws of sandstone were analyzed,and the influence laws of sandstone fracture mechanism on the types of strain energy and its evolution were discussed.The results show that as the minimum principal stress increases,the peak strength and residual strength of sandstone increase,and the total strain energy,elastic energy and dissipated energy before failure also increase,of which the proportion of dissipated energy increases accordingly.By calculating and plotting the relationship curves between the ratio of rise time to amplitude(RA value)and the ratio of count to duration(AF value)in acoustic emission waveforms,and by observing fracture morphology,it was found that sandstone exhibits tensile-shear composite failure under lower minimum principal stress,while the failure mode gradually shifts to shear-dominated with increasing minimum principal stress.Throughout the entire loading and failure process of sandstone,the dissipated energy and plastic shear strain energy curve show a positive correlation.Before failure,the curve transforms from nonlinear to linear with the increase of minimum principal stress,indicating that plastic shear strain energy gradually dominates energy dissipation.After failure,the curve grows linearly,which may be attributed to the fact that energy dissipation is primarily caused by slip friction along macroscopic failure surfaces.The research results reveal the energy evolution mechanism of deep-seated dynamic disasters and provide a theoretical basis for disaster early warning and prevention and control.

Abstract:To address the current unreasonable gas extraction conditions in coal mines and achieve intelligent negative pressure control of the underground gas extraction pipe network,a novel negative pressure regulation method based on valve opening optimization is proposed to enhance the gas extraction capacity of the pipe network.Based on the structure of the gas extraction pipe network and the characteristics of gas flow,a network calculation model is established combining optimization algorithms to optimize valve openings.Meanwhile,the pigeon-inspired optimization algorithm is improved by introducing a general learning factor to enhance its overall search capability;it also incorporates individual historical optimal terms and adjusts the center position to strengthen local optimization.Taking the extraction area of the Liuzhuang Coal Mine in Anhui's western section as an example,after optimization,the negative pressure at all gas source ends remains stable within the set range,the air leakage at the pipe network inlet is reduced by 2.323 kg/s,and the gas mass concentration increases to 1.63 times that of the original plan.Through a combination of simulation experiments and practical application,a feasible solution for efficient gas extraction by coal mine pipe networks is provided.

Abstract:This study addresses the challenges of accurately locating trapped personnel during underground mine disasters and reviews recent advances in life detection technologies for mine rescue operations.It highlights the potential of proton transfer reaction mass spectrometry(PTR-MS)as a promising solution for precise search and rescue.By comparing the principles,strengths,and limitations of electronic noses,gas chromatography-mass spectrometry(GC-MS),and selective ion flow tube mass spectrometry(SIFT-MS),the study finds that PTR-MS offers superior real-time monitoring,sensitivity,and compound identification.These advantages make PTR-MS well-suited for detecting trace levels of human-specific volatile organic compounds(VOCs)in mine disaster environments.The study proposes a PTR-MS-based detection technique for mine borehole rescue operations.This approach involves establishing baseline gas characteristics in disaster environments to develop an indicator system for locating trapped individuals.It also recommends the use of ground-based directional drilling combined with a pre-concentration adsorption sampling system to improve the detection of trace VOCs.Additionally,the study examines gas diffusion patterns in confined spaces to construct concentration gradients and develop methods for source tracing.PTR-MS life-signature detection technology enables more accurate localization of trapped personnel,supports innovative search-and-rescue strategies,and contributes to the development of a mine borehole rescue system centered on accurate detection,rapid decision-making,and efficient response.

Abstract:With the increasing mining depth of shallow buried multi-coal seam mines in Northern Shaanxi,strong mine pressure dynamic disaster is prone to occur when the lower working face is mined back overlying coal pillar.This imposes a potential serious threat to the safety production of the mine.In view of the problem that support crushing accident in the coal pillar exit stage of the working face of plate area 302 in Longhua Coal Mine,this study takes the working face 30208 in this plate area as the engineering background.In this study,with the combination of the theoretical analysis and numerical simulation methods,we firstly explored the overlying strata displacement field,fissure field,stress evolution law of key rock strata and the distribution characteristics of the force chain,and then clarified the characteristics of overlying strata migration over the overlying coal pillar in the working face.The control measures were carried out in the mine and the results were verified by mine pressure monitoring.The results show that the upper key layer forms a'Tri-hinge'structure,with the overlying coal pillar acting as a'Transfer load body'to transmit the load downwards.When the working face is out of the overlying coal pillar edge,the hinged structure of the upper key layer is damaged.The overlying caving rock strata rotary subsidence of overlying rock strata,and the internal stress of the overlying coal pillar is shifted.These induce the lower key layer to abnormal periodic breaking,and the energy of the two is instantly released to the quarry,resulting in a strong mine pressure disaster.

Abstract:To address the limitations of traditional resistivity inversion methods in mining scenarios—including initial model dependency,boundary ambiguity,and artifacts present in existing deep learning-base inversion approaches—this study proposes a physics-constrained U-Net inversion method.By integrating electrical sensitivity characteristics and depth focusing mechanisms,the method constructs a weighted cross-entropy loss function based on U-Net's multi-scale feature fusion architecture.Enhanced encoder-decoder skip connections are employed to amplify resistivity contrasts between anomalies and background fields.A parameter space for resistivity distribution was defined based on three types of typical anomalous bodies,and forward modeling was performed on 6 000 models using the finite element method.Dipole-dipole array configurations were applied to acquire apparent resistivity profiles,establishing a geoelectric model-response paired dataset for supervised training.Experimental results demonstrate a Dice coefficient of 0.950±0.018 and a reduction in inversion time from 65.2 s(least-squares method)to 1.0 s per instance,improving computational efficiency by 98.5%.The synergistic optimization of physical priors and deep learning provides an effective solution for precise detection of hidden water-conducting structures in coal mine hazard prevention.

Abstract:Against the dual backdrop of ongoing global climate warming trend and the full implementation of China's"carbon peak and carbon neutrality"strategy,promoting clean and efficient coal utilization of coal has become a critical link in balancing energy security and climate governance.Based on China's energy consumption structure and carbon emission characteristics,this study constructs a technological system for clean coal utilization centered on"source pretreatment—process efficient conversion—end-of-pipe carbon management".It systematically reviews key technologies,such as coal washing,coal gasification,modern coal chemical processes(including coal-to-liquid,coal-to-gas,coal-to-olefins,etc.),clean coal power generation(ultra-supercritical,circulating fluidized bed,integrated gasification combined cycle,and polygeneration),as well as carbon capture,utilization and storage(CCUS).The principles,development status,existing challenges,and future trends of these technologies are analyzed.Research indicates that China has achieved or approached international advanced levels in multiple clean coal utilization technologies,with conditions suitable for engineering demonstration and promotion.Through systematic integration and synergistic optimization of the entire technological chain—encompassing"washing—gasification—power generation and chemical production—capture"—coal utilization efficiency can be significantly enhanced,enabling effective control of pollutant and carbon dioxide emissions.To achieve the carbon neutrality goal,China should continue developing clean energy while positioning clean and efficient coal utilization as a crucial transitional support.By advancing technological iteration,policy coordination,and industrial collaboration,coal can gradually transition from a traditional fuel to a low-carbon raw material and zero-carbon energy carrier,thereby providing a feasible technological pathway for building a clean,low-carbon,safe,and efficient energy system.

Abstract:Geological storage of CO2 in deep coal mine goaf is an important way to alleviate greenhouse gas emissions.In this study,the mechanical behavior and microstructure evolution of saturated broken coal gangue under the interaction of CO2-water-rock were systematically studied.Based on the simulation experiment platform of CO2 storage in goaf,the particle crushing characteristics and compaction characteristics of saturated broken coal gangue under different CO2 reaction pressures(0 MPa,2 MPa,4 MPa,6 MPa,8 MPa)were systematically studied.The microstructure changes of coal gangue after CO2-water-rock interaction were analyzed by X-ray fluorescence and scanning electron microscopy,and the microscopic mechanism of coal gangue particle crushing was discussed.The results showed that with the increase of CO2 reaction pressure,the relative crushing rate of broken coal gangue increased from 36.07%to 45.49%,with an increase of 9.42%.The fractal dimension increased from 2.677 7 to 2.736 3,with an increase of 14.01%.Under the stress of 25 MPa,the strain of the sample increased from 0.309 at 0 MPa to 0.354 at 8 MPa,with an increase of 14.56%.X-ray fluorescence analysis showed that the content of Ca decreased from 65.455%to 15.531%,with a decrease of 76.27%,indicating that the Ca-containing minerals underwent strong dissolution during the reaction.The results of scanning electron microscopy showed that as the CO2 reaction pressure increased from 0 MPa to 8 MPa,the proportion of pore cracks on the surface of coal gangue increased from 1.446%to 2.641%,and the fractal dimension of surface pores increased from 0.993 2 to 1.143 1.Based on the experimental results,an improved empirical model considering the reaction pressure of CO2 is proposed,which can accurately describe the mechanical behavior of saturated broken coal gangue under high CO2 pressure.The research results provide a theoretical basis for evaluating the stability and safety of CO2 sequestration in coal mine goaf.

Abstract:During the mining process of small coal pillars and gob-side entry retaining,cracks are prone to occur,causing air leakage in the goaf.Spraying sealing materials is the key to preventing air leakage,but existing spraying materials have problems such as poor toughness and proneness to cracking.To solve this problem,an organic-inorganic hybrid flexible sprayed sealing material was developed.The preparation principles and methods were elaborated;flowability testing,water-bleeding rate testing,toughness testing,and microstructural analysis were conducted to determine the optimal mix ratio of the new material;a leakage-sealing performance test platform capable of simulating mine pressure was constructed,and the roadway sealing effectiveness of the flexible sprayed material was validated under conditions where support wall deformation occurred due to varying pressures.The experimental results show that after organic hybridization,the inorganic cement-based materials reduce the water separation rate of the materials,and increase the fluidity and toughness of the materials.When the addition of organic lotion reaches 20%,the elongation at break increases to 8%,which is primarily attributed to the formation of a three-dimensional interpenetrating network structure within the material,thereby significantly enhancing its toughness.The optimal formulation of the new material is as follows:water-cement ratio of 0.6∶1,sodium silicate content of 2%,polyvinyl alcohol content of 3%,and VAE emulsion content of 20%.Compared with traditional cement-based materials,the internal organic network structure of flexible sprayed materials can undergo certain deformation,which enhances the leak-proofing performance by over 30%,and is less affected by mine pressure.It has a better sealing effect on air leaks such as small coal pillars and gob-side entry retaining that are prone to cracks caused by mine pressure,reducing the probability of coal spontaneous combustion.

Abstract:Accurately collecting various signals and extracting features is the key to achieving automatic control of mining equipment.The vibration signal of motor bearings is one of the important signals for automatic identification of coal and rock in mining equipment.It is severely affected by environmental noise and component friction under complex working conditions,resulting in blurry signal characteristics and affecting the signal characteristics of mining equipment.This study proposes a joint wavelet denoising method based on Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(ICEEMDAN)and Multiscale Permutation Entropy(MPE)optimized by a genetic algorithm,and evaluates its effectiveness through signal-to-noise ratio,mean square error,and denoising error ratio.The research results show that compared to traditional methods such as EEMD-MPE,CEEMDAN-MPE,and ICEEMDAN-MPE,the proposed joint wavelet denoising method has the highest signal-to-noise ratio,minimum mean square error,and maximum denoising error ratio in simulated signals and mechanical equipment bearing vibration datasets.This method not only exhibits excellent noise suppression capabilities,but also effectively preserves the feature information that characterizes the mechanical state.By studying the motor bearing signals of coal mining equipment,it can provide preliminary research for studying the signal characteristics of the entire mining equipment,and lay a certain foundation for the subsequent automatic recognition of coal and rock and the automation and intelligence of working condition equipment.

Abstract:To address the challenge of limited prediction accuracy for underground gas concentration,we propose a spatio-temporal graph neural network(DASTNN)model incorporating a dual attention mechanism.This model aims to enhance the prediction of gas concentration in coal mine drainage pipe networks.By integrating a graph convolutional network(GCN)with a gated recurrent unit(GRU),and applying both spatial and temporal attention mechanisms,the model improves the extraction of features related to network topology and time series patterns.We evaluated the model on the gasnet-data1 and gasnet-data2 datasets.The results demonstrate that our approach outperforms traditional methods such as HA,SVM,GCN,and GRU.On the gasnet-data1 dataset,the model achieved a mean absolute error(eMA)of 0.310,a root mean square error(eRMS)of 1.069,and a coefficient of determination(R2)of 0.975.On gasnet-data2,the eMA was 0.181,the eRMS was 0.745,and the R2 was 0.990.These findings indicate that the dual attention mechanism effectively captures the spatiotemporal dependencies of gas concentration,and significantly improves prediction accuracy.

Abstract:This study analyzes patterns of gas over-limit accidents in Chinese coal mines from 2023 to 2024,considering factors such as mine type,accident location,timing,enterprise type,and accident categories.The analysis reveals that over-limit accidents are most prevalent in outburst mines and high-gas mines,representing 54%and 28%of incidents,respectively.The regions with the highest numbers of these accidents are Southwest China,North China,and Northwest China.Areas with severe gas hazards are more susceptible to over-limit events.From March to May and August to December,gas over-limit accidents occur most frequently,which is primarily influenced by the production organization of coal enterprises.Non-state-owned enterprises accoant for 67.90%of gas over-limit accidents.Poor mining and excavation management is the main cause of such accldents,and climate-driven"breathing"phenomena in mines contribute to such accident in Northwest China.To reduce the occurrence of gas over-limit accidents,greater emphasis must be placed on both technical improvements and management practices.This includes risk prediction and graded control,advanced large-scale gas control measures,stable operation of ventilation and extraction systems,high-reliability monitoring system,and precise prevention and control strategies,based on atmospheric pressure fluctuation monitoring.These integrated efforts are essential to ensure safe and efficient mine production.

Abstract:As the depth of coal mine mining advances year by year,the danger and harm of coal and gas outbursts are becoming more and more serious.In order to study the evolution law of coal and gas outburst energy with increasing burial depth,Pingmei No.12 Coal Mine was taken as the engineering background and typical outburst accident cases were selected that occurred during shallow(407 m),middle(731 m)and deep(1 108 m)mining process.By constructing an outburst energy calculation model,the evolution and release law of coal and gas outburst under different burial depths were explored.The research results showed that during the process of coal and gas outburst,the elastic energy of coal and rock and the gas expansion energy both increased with the burial depth.At the same burial depth,the gas expansion energy was 1 to 3 orders of magnitude higher than the elastic energy of coal and rock,which was the main energy source for the outburst.The outburst energy was mainly used for the crushing and transportation of the ejected coal.As the burial depth increased,the work required for coal fragmentation and transportation showed a logarithmic increase and exponential increase trend respectively.In addition,the effective desorption ratio was introduced to quantitatively characterize the proportion of gas expansion energy actually involved in expansion work to the total gas expansion energy in the outburst coal seam.It was found that the effective desorption ratio showed a linear growth trend with the increase of burial depth,indicating that deeper burial leads to a higher proportion of effective gas expansion energy and a greater risk of outbursts.

Abstract:In order to prevent the occurrence of coal mine gas explosion accidents,it is necessary to identify hazard sources,analyze the root causes of such incidents,and implement control measures for their causal factors.This study investigates the advantages and implementation process of RCA(Root Cause Analysis)in analyzing coal mine gas explosion accidents.It introduces the AHP-RCA analysis method and applies tools such as brain storming and fishbone diagrams in combination with actual cases,analyzing the patterns and common issues in coal mine gas explosions to identify their underlying causes.Building on this foundation,the AHP(Analytic Hierarchy Process)is employed to construct a hierarchical model of the causative factors in coal mine gas explosion accidents.A quantitative analysis of these causative factors is then conducted by establishing judgment matrices,calculating their eigenvectors and weights,ultimately identifying the primary causes leading to gas explosion accidents.The results show that the AHP-RCA analysis method breaks through the limitations of traditional accident tree analysis,and realizes the priority of causal factors through weighting,in which human factors and management factors are the main disaster factors,so the rectification measures and suggestions are put forward for the safety management of on-the-job personnel to better carry out accident prevention.

Abstract:During the long-term operation of rail conveyors,the rail surfaces are prone to wear and foreign object accumulation.If not addressed promptly,these issues can lead to unstable trolley movement or even derailment.To address the problems of delayed response and low detection accuracy in manual inspections,a track 3D profile registration deviation detection method based on the Principal Components Analysis-Normal Iterative Closest Point(PCA-NICP)algorithm is proposed,aiming to achieve high-efficiency and high-precision detection of surface anomalies in rail conveyor tracks.The method begins with data validity verification and outlier removal.Subsequently,Principal Component Analysis(PCA)and the Normal Iterative Closest Point(NICP)algorithm are employed to achieve coarse and fine registration of the profiles,respectively.Finally,the track profile is visualized,and the surface anomaly status is output.Experimental data validation shows that the detection error for track wear and foreign material thickness is less than 0.3 mm,effectively improving both detection efficiency and accuracy.

Abstract:The existing gas disaster warning systems suffer from issues such as poor data transmission stability,high latency,and delayed warning responses.To address these problems,a gas emission anomaly warning device with multi-parameter sensing,multi-mode communication,and independent operation capabilities has been developed to enable real-time on-site monitoring and accurate warning of gas disasters.The device integrates an environmental parameter sensing module,a power module,a multi-mode communication module,an analysis and warning module,and an accident alarm module.It can simultaneously collect seven environmental parameters,including methane and wind speed,and supports five modes of data transmission.It is adaptable to a wide voltage range of 127 V to 660 V underground and can operate independently without relying on safety monitoring systems,achieving real-time on-site monitoring and warning of gas disasters.The research also established gas over-limit warning technology based on Long Short-Term Memory(LSTM)artificial neural networks,gas emission anomaly warning technology based on gas monitoring statistical data,and a warning indicator system for coal and gas outbursts,enabling accurate monitoring and warning of hazards such as abnormal gas emissions,gas over-limit,and coal and gas outbursts.The warning device has completed its industrial trials at the Xiangshan Mine of Shaanxi Coal and Chemical Industry Group Hancheng Mining Co.,Ltd.The test results show that the warning device can predict the methane concentration 5 minutes ahead with an average absolute percentage error of 0.98%.The coal and gas outburst indicator A can effectively reflect the change trend of the gas desorption indicator K1 in drill cuttings,and it has demonstrated good warning effects for both gas exceedance warnings and coal and gas outburst warnings.

Abstract:In view of the problems existing in intelligent excavation face of coal mine,such as the slow tunneling rate of full-section roadway,the difficulty of preparing roadway for one-time roadway formation,and the relatively low level of intelligence in full-section tunneling,a method of full-section rapid roadway in the intelligent excavation face of coal mine is proposed.The cutting track is optimized and modified according to local conditions to reduce the wear of the roadheader and the waste of resources at both ends of the excavation face roof.The system of full-section rapid roadway in the intelligent excavation face in coal mine is developed.According to the data obtained by the information acquisition device of roadheader,the cutting speed is automatically adjusted and the corresponding cutting mode is selected.The autonomous cutting is carried out by pre-set optimized tunneling scheme and inertial navigation,and remote intervention can also be carried out.This method and system have been applied in 14010 working face of Zhaogu No.2 Coal Mine.It has gone through three stages of learning and exploration,preliminary application and formal application.It has realized the memory cutting of intelligent roadheader,autonomous bolting with a monorail-mounted six-boom bolter,and the intelligent control of rapid repair equipment of coal roadway.The working face achieves an additional daily advance of 2 m while reducing manpower by 8 workers per shift.This substantiates the realization of manpower reduction and efficiency enhancement in intelligent excavation operations,providing both technical support and a theoretical reference for achieving full-section rapid roadway in intelligent excavation face of coal mine.

Abstract:Controlled by geological conditions,coalbed gas occurrence exhibits heterogeneity.Revealing its occurrence patterns and geological control mechanisms serves as a critical basis for implementing the"one mine,one policy;one mining face,one policy"gas control strategies in coal mines.Based on gas geological theories and methods,utilizing measured gas content data and relevant geological data,this study investigates the gas occurrence patterns and geological control mechanism in the area bounded by the F17-1 and F18 Faults within the No.2-1 Coal Seam of Zhaogu No.2 Mine.The results show that:affected by geological factors such as the thickness of the overlying bedrock,burial depth,faults,and synclines,the gas occurrence of the No.2-1 Coal Seam in different ranges of the study area presents significant heterogeneity and differences in controlling factors.For the area with a burial depth of less than 790 m,the thin bedrock combined with shallow faults such as the F30 Fault,its branch faults,and the FS3 Fault is conducive to gas escape,which is the main reason for the overall low gas content in this region.Meanwhile,affected by burial depth,the gas content shows a trend of slow increase with the increase of burial depth.For the area with a burial depth greater than 790 m,the bedrock thickness is the dominant controlling factor for the overall distribution of gas occurrence.The bedrock thickness first increases and then decreases with the increase of burial depth,which is the main reason for the coal seam gas content first increasing rapidly and then decreasing as the burial depth increases.The pinch-out zone of the F17-1 Fault and the S4 Syncline area are local gas-enriched zones under the overall control of bedrock thickness.The gradual increase in coal seam gas content at the same depth level—progressing from the F18 fault toward the F17-1 fault—is primarily attributed to the gas dissipation effect of the F18 fault.