Understanding gas transport mechanisms within the coal matrix is crucial for optimizing coalbed methane extraction and preventing gas-related accidents. However, current academic research often ignores the release characteristics and transport behaviors of gas stored within rocks. This study first determined the adsorption constants of coal and rock particles for different gases and conducted isothermal desorption experiments for both carbon dioxide and methane under constant-volume conditions. Based on the free gas density gradient diffusion theory, a mathematical model for gas transport was developed and solved numerically using the finite difference method. Furthermore, a novel method integrating dimensionless analysis criteria with an empirical desorption formula was proposed to determine the micropore diffusion coefficient. The results demonstrate that (1) for both rock and coal particles, and for both carbon dioxide and methane desorption, the simulation curves based on the density gradient diffusion model show fundamental consistency with the experimental data, verifying the model's correctness; (2) within the same coal/rock particle, the micropore diffusion coefficient of carbon dioxide is greater than that of methane. For anthracite under 2 MPa, the methane diffusion coefficient is 6.3 & times; 10(-8) cm(2)/s, while the carbon dioxide diffusion coefficient is 4.9 & times; 10(-7) cm(2)/s. For the same gas, the micropore diffusion coefficient is greater in coal particles than in rock particles; (3) although the total gas content stored in the rock matrix is less compared to coal particles, it is not negligible. Subsequent research should pay greater attention to the storage and transport behaviors of gas within rocks.

Coal, as a porous medium, exhibits a strong adsorption capacity for gas. The laws governing gas adsorption and transport are critical research topics for gas disaster prevention and control, as well as for coalbed methane (CBM) extraction. This study takes coal samples from the Guobei Mine as the research subject. Isothermal adsorption experiments under constant pressure conditions were conducted on coal particles of different sizes to investigate the influence of particle size and initial pressure on gas adsorption capacity and adsorption rate. Based on the density gradient diffusion theory, mathematical models for gas adsorption in both cylindrical and spherical coal particles were established. These models were nondimensionalized, solved using the finite difference method for simulation analysis, and subsequently validated against experimental results. The research indicates that under the same initial pressure, smaller coal particle sizes result in a larger cumulative adsorption capacity and a faster adsorption rate. For particles of the same size, a higher initial pressure leads to a greater saturated adsorption capacity and a shorter time to reach adsorption equilibrium. The cumulative gas adsorption capacity conforms to an empirical model where ″the reciprocal of adsorption capacity shows a linear relationship with 1/t0.65″. The simulation results for cylindrical and spherical particles show a high degree of agreement. Under different initial pressures, the nondimensional pressure for both shapes follows a consistent pattern: "rapid surface response → internal gradient transmission → overall trend toward equilibrium". The equilibrium nondimensional time is approximately 0.08982 at 4.0 MPa, and ranges between 0.3 and 0.45 at 0.5 MPa, with the radial pressure gradient decay rate being consistent. The initial slope, equilibrium time, and saturated adsorption capacity of the nondimensional cumulative adsorption curves are essentially identical. For 50-60 mesh coal samples at 2 MPa, the deviation in the adsorption cycle is less than 0.05 cm3/g, confirming that particle shape has no significant effect on gas adsorption and transport. The established model accurately captures the dynamic characteristics of gas transport. The fit between simulated and experimental values is excellent, with R 2 > 0.99 and an average relative error of only 3.2%. This work breaks through the limitation of the "single spherical particle" assumption, enhances the applicability of the density gradient diffusion theory, and provides reliable theoretical support for the optimization of CBM extraction and gas disaster prevention and control.

Accurately measuring the effective influence zone of coal seam hydraulic flushing remains a key technical challenge in mine safety. This study proposes a novel resistivity-based identification method for blank zones during hydraulic flushing, integrating numerical simulations, laboratory experiments, and field validations. The research results indicate an exponential negative correlation between coal resistivity and moisture content. The spatial extent of multi-physical field alterations induced by hydraulic flushing follows the order: fracture field (R-III) > stress field (R-II) > seepage field (R-I). Post-flushing stress redistribution enhances coal matrix porosity, while the formation of macroscopic fractures obstructs conductive pathways, resulting in localized increases in resistivity. Water infiltration into the fractures significantly reduces apparent resistivity, which subsequently rebounds due to water loss in later stages. Mechanistic findings show that stress redistribution enhances matrix porosity, while macroscopic fractures obstruct conductive channels, leading to localized increases in resistivity. Blank zones-regions not subjected to stress relief or permeability enhancement-are typically located in front of and on both sides of the boreholes, exhibiting irregular, non-uniform patterns shaped by heterogeneous in-situ stress fields. Apparent resistivity mapping effectively captures both low-resistivity flushing-affected zones and embedded high-resistivity blank zones. These research efforts provides a quantitative and engineering-oriented framework for optimizing hydraulic parameters and implementing precise coal and gas outburst prevention measures.

Microseismic (MS) disturbances are a critical triggering factor for coal and gas outbursts (CGO) during coal roadway excavation. To address the limitation that existing CGO early-warning methods generally neglect the dynamic effects of MS disturbances, this study investigates the 22# coal seam of the Jinjia Coal Mine. A numerical model is developed to analyze the propagation behavior of MS-induced seismic waves ahead of the excavation face. A coupled model linking seismic-wave velocity, coal-seam stress, gas pressure, and coal-rock damage is established, and an MS-informed energy criterion for CGO prediction and early warning is proposed. The main findings are as follows: (1) Seismic waves in coal and rock masses follow a power-law attenuation pattern. The peak MS disturbance stress and gas pressure are positively correlated with the peak seismic-wave velocity, enabling quantitative characterization of disturbance stress and transient gas-pressure rise using peak vibration velocity. (2) Following an MS event, stress superposition rapidly elevates local stress, while the abrupt increase in gas pressure enhances the internal energy available for outburst. Concurrently, plastic damage to the coal accelerates gas desorption. These coupled effects collectively increase CGO risk; (3) On-site verification shows that after an MS event, the increase in the early-warning indicator Rg value precedes the occurrence of CGO precursors such as abnormal rises in roadway gas concentration. Accordingly, the proposed early-warning criterion enables earlier identification of CGO risk than conventional gas-monitoring methods.

In deep coal mining, gas disasters pose a severe threat as gas extraction efficiency is often hampered by a rapid decline in gas concentration. Existing permeability enhancement techniques for low-permeability coal seams yield suboptimal results. To address this issue, a dynamic breakthrough experimental system was constructed to address this issue. This system simulated the extraction environment in coking coal to investigate the competitive adsorption and migration of CO2-CH4-N2 mixed gas under multi-pressure conditions. The results revealed that the coal adsorption capacity follows the order CO2 > CH4 > N2, while the breakthrough rate follows CH4 > N2 > CO2. The presence of N2 enhances the adsorption depth of both CO2 and CH4. Two distinct methane migration patterns were identified during competitive breakthrough: long-term breakthrough at low flow rate and stable breakthrough at high flow rate. Based on these mechanisms, a novel borehole sealing method termed “two plugs, one extraction, and multiple injections” was proposed. This method utilizes the competitive displacement effect between CO2/N2 and CH4 to proactively maintain and increase gas extraction concentration. This enables borehole operation under low-negative-pressure extraction, normal-pressure desorption, and slight-high-pressure competition, effectively enhancing both gas concentration and extraction rate. The proposed method offers a direct and adaptable technical solution for improving gas control in deep, high-outburst coal mines such as the Pingdingshan mine, with potential applications in enhancing mining safety and efficiency.

This research aims to examine the damage and failure behaviour of red sandstone under multistage-stage amplitude increasing cyclic (MS-AIC) loading, with three different increasing stress amplitudes (ISA). By combining macroscopic mechanical testing and acoustic emission (AE) monitoring techniques, the impacts exerted by three distinct ISA schemes are comprehensively analysed. The investigation focuses on the stress-strain behaviour, energy evolution, AE activity, and damage development in red sandstone. The results demonstrate that (1) Under MS-AIC loading, both the axial strain and damage accumulated progressively with cycle number. According to the irreversible axial strain produced during cyclic loading, a model which can describe the process damage of red sandstone was proposed. (2) The energy evolution analysis showed that under the effect of different ISA, the input energy accumulated, and the dissipated energy exhibited an initial decrease followed by an increase. (3) The cumulative AE counts rose steadily with cycles; AE counts and energy release rate increase sharply when the stress increases. As ISA increased, the tensile cracks ecrease gradually, with the growth in the shear cracks. The final failure mode was a composite tensile-shear fracture. The results support further understanding of the stability of rock mass under MS-AIC loading.

Coal and gas outburst represents one of the most catastrophic dynamic disasters in deep coal mining. Accurate identification of its precursors and precise localization of hazard sources are essential for effective early warning and safe mining operations. In this study, a novel six-dimensional feature fusion framework is proposed, based on a self-developed triaxial electromagnetic radiation (EMR) vector monitoring system. Continuous online EMR monitoring was carried out during excavation at the 2615 working face of Juji Coal Mine. Within successive ten-minute time windows, EMR amplitude peaks were extracted, and the following key parameters were calculated: horizontal deviation, vertical deviation, amplitude deviation, and their corresponding permutation entropies. The resulting feature vectors were classified using the K-nearest neighbor (K-NN) algorithm against six prototypical event vectors to enable rapid identification of outburst-related events. Identified events were categorized as either coal-seam internal fracturing or interface disturbance, and localized via two single-sensor strategies: for internal fracturing, the stress-peak location derived from numerical simulation was used; for interface disturbance, localization was achieved through deviation-vector extrapolation to plane intersection. The average localization errors were approximately 1.34 m (0.073 rad) for internal fracturing and 2.18 m (0.005 rad) for interface disturbance. The proposed "single-sensor + numerical-model" framework is easy to deploy in underground settings and supports rapid spatial localization of high-risk outburst events, offering a practical and efficient technical solution for mine safety monitoring and early warning.

The safety monitoring of high gas coal seam excavation is a critical measure for the prevention and control of coal and gas outburst accidents. In this paper, the geophysical methods such as direct current (DC) method and electromagnetic radiation (EMR) monitoring were used to evaluate the effectiveness of hydraulic flushing in the coal seam and to monitor and warn the safety of the coal seam roadway. The main conclusions are as follows: An outburst risk prediction method for coal roadway excavation process based on resistivity-electromagnetic radiation detection was proposed. The effective range of hydraulic flushing in the coal seam was found to be 8-12 musing the DC method. The reduction in gas content ranged from approximately 0.2 to 3 m3/t per unit, resulting in an overall decrease of around 40 %. EMR is effective in monitoring the dynamic events of the coal seam boring process. The signal was a fluctuation in the EMR signal after excavation began, reaching its maximum value during a coal burst. A method based on processing EMR-AE data to detect precursor signals is proposed. The Unified Precursor Index (UPI) of 0.75 is used as the early-warning threshold for coal burst events, indicating intense state changes in the coal mass. The UPI allows for the coal burst event to be detected 20 min in advance. The research provides a new perspective for the monitoring of coal rock dynamic disasters.

Visual detection of grouting in water-bearing fractured rock mass is a difficult problem in the field of underground engineering. Based on the combination of theoretical analysis, laboratory experiment and field test, this study systematically reveals the temporal and spatial evolution law of slurry diffusion and solidification in fractures, and comprehensively proposes an apparent resistivity evaluation method in grouting effect of waterbearing fractured rock mass. The research results are as follows: Based on the principle of DC (direct current) method, the theoretical relationship model between apparent resistivity and slurry hydration-solidification of water-bearing fractured rock mass is established. Through the self-designed grouting apparent resistivity detection system, it was found that the water-bearing fractures were symmetrically distributed with low apparent resistivity before grouting. After grouting, the apparent resistivity increases gradually and tends to be stable with the continuous solidification of the slurry. And the diffusion radius of the slurry was up to 16 cm, and the grouting effect was up to 78.7%. Apparent resistivity can effectively characterize slurry diffusion range and the degree of solidification in water-bearing fractures. In the rock wall of the underground cavern, it is found that the apparent resistivity around the grouting hole (2) responds significantly before and after grouting. The maximum slurry diffusion radius of the grouting hole (2) is 13 m, and the grouting effect reaches 92%. The test results are verified by field rock wall water seepage. The research provides theoretical support and visual detection method for the evaluation of grouting in water-bearing fractured rock mass.

The growing burial depth increases the potential risk of ground stress-induced coal and rock dynamic disasters in coal mining. This study attempts to use microseismic and computed tomography (MS-CT) to quantitatively characterize the stress field in coal seam areas. A comprehensive approach encompassing laboratory experiments, numerical simulations, and field investigations was employed to accomplish this objective. The experimental findings suggest a power function relationship between the wave velocity of coal and stress. The model relating wave velocity ratio to stress proves more suitable for research on stress field quantification. This model captures the positive correlation between wave velocity and stress changes and eliminates the influence of sample differences through normalization, rendering the fitting parameter b applicable in the field. This paper takes the No.22 coal seam of Jinjia coal mine as the research object; MS-CT technology was used to generate the cloud map of wave velocity field distribution in the 11224 working face and combined with the experimentally established relational model to relate the wave velocity ratio to the stress and calculate the results of quantitative characterization of the regional stress. At the same time, a detailed three-dimensional numerical model was established and simulated to obtain the stress distribution in the 11224 working face area. Comparison of the simulated stress field results with the quantitative results of MS-CT shows that the general trend is basically the same, and the stress is higher in the area with greater burial depth. The area affected by the overlying goaf has lower stress in the coal seam. The maximum error value of the two is within ± 2 MPa, and the correlation coefficient is 0.79, indicating a strong correlation. Therefore, the MS-CT technique combined with the experimental wave velocity-stress coupling relationship model can determine the stress field distribution and realize the quantitative stress characterization. This provides a crucial foundation for analyzing the mechanical model of coal seam instability and calculating the judgment index of coal-rock dynamic disaster excitation.

The investigation of factors governing the adsorption capacity of various gas molecules in coal matrices is critically important for the efficient utilization of coalbed methane (CBM). In this study, molecular models of four adjacent coal seam samples were constructed to analyze energy distribution characteristics during microporous adsorption, thereby identifying the dominant factors influencing gas adsorption in coal. The results indicate that for a given coal molecular structure, the adsorption capacity consistently follows the order CO2 > CH4 > N-2, with CO2 adsorption being substantially greater than that of CH4 and N-2. The adsorption mechanism of CO2 is weakly chemical by a combination of van der Waals forces and electrostatic forces whereas CH4 and N-2 adsorption is purely physical by van der Waals forces only. The adsorbed amount a based on specific surface area (SSA) and van der Waals forces was proposed to be calculated as a = c(1) center dot A center dot exp(-c(2)center dot F-w). The a varies linearly with the increase of SSA and increases exponentially with the increase of interaction forces on the surface. The Multisite Langmuir (MSL) adsorption model was developed and validated, showing significantly improved fitting accuracy compared to the conventional Langmuir model. This study establishes a comprehensive multiscale framework that correlates molecular-level interactions, structural heterogeneity, and tectonic effects to elucidate gas adsorption behaviors in high-rank coals.

Coal and gas outbursts in deep mining are primarily caused by abnormal stress, yet existing technologies struggle to identify regional stress anomalies quickly and accurately. This study established a wave velocity-stress coupling model that excludes the influence of gas on wave velocity, extracted the stress field of the coal skeleton, proposed a method for characterizing stress anomalies in high-gas outburst coal seams using wave velocity anomaly coefficients (A(n)), and applied it. The results demonstrate that: (1) The effect of gas on coal seam wave velocity depends on adsorption capacity, porosity, and pore structure, leading to an extreme wave velocity value during gas pressure increase. When gas pressure is below 1.2 MPa, wave velocity correlates positively with gas stress, but inversely above this threshold. (2) The proposed A(n) coefficient reveals positive anomalies (A(n) > 0) in stress concentration zones and negative anomalies (A(n) < 0) in fractured or stress-relieved regions. (3) During mining, high-stress and low-stress zones alternate, with stress concentrations (A(n) >= 0.1) often occurring near working faces and faults. (4) Outbursts predominantly occur in high-stress, high-stress-gradient areas, where stress anomalies and microseismic signals exhibit 84.6% spatial overlap. This study provides a novel approach for stress field visualization in high-gas outburst coal seams and a quantitative criterion for regional dynamic prediction of outburst hazards.

Coal and gas outburst represents one of the most severe dynamic disasters in underground coal mining. Conventional point-based prediction methods have difficulty dynamically capturing the evolution of outburst risk under mining-induced disturbances. Taking a typical outburst-prone coal seam as the engineering background, this study proposes a dynamic prediction approach for coal seam outburst based on microseismic (MS) monitoring with seismic velocity tomography (SVT) identified risk zones. First, by analyzing the spatiotemporal evolution of MS events, the correlations between microseismicity and geological structures, stress concentration zones, and abnormal gas emissions were revealed. Second, seismic velocity tomography was employed to delineate stress anomaly zones, and the results were validated against areas with excessive gas parameters. On this basis, six sensitive MS precursors (b-value, A (b)-value, seismic activity degree S, seismic moment deficit M, algorithmic complexity AC, and seismic activity scale ΔF) were integrated using the entropy weight method and fuzzy comprehensive evaluation to construct a multi-dimensional early warning model. The results indicate that: (1) The spatiotemporal distribution of MS events correlates well with geological structures and advance stress concentration zones, with clear precursory patterns (energy accumulation-release cycles and “M-shaped” frequency variations) preceding high-energy events; (2) High-velocity anomalies identified by seismic velocity tomography show strong spatial consistency with areas of high gas content and locations with excessive gas parameters, confirming stress concentration as a key factor inducing outbursts; (3) The proposed multi-dimensional early warning model identifies the level of high-energy microseismic events associated with outburst risk, achieving a prediction accuracy of over 80% in field applications and outperforming single-indicator methods. This study provides an effective geophysical approach for dynamic coal and gas outburst early warning.

With the increasing mining depth, the dynamic disaster of outburst coal seam presents the characteristics of low gas outburst and strong dynamic load disturbance outburst, which makes the disaster prevention face serious challenges. The tectonic coal development is a significant geological feature of dynamic disasters. Therefore, this paper studies the stress and deformation evolution laws of tectonic coal stratified workface under the coupling action of dynamic and static loads. Based on the safety barrier model, the mechanical model of disaster initiation and the basis for disaster initiation discrimination were established. The evolution process of compound dynamic disasters induced by the failure of the safety barrier was revealed. It is found that the instability of the safety barrier under the action of disturbance stress and static load stress are the main reasons for the initiation of disasters. The monitoring method for the stress field of deep outburst coal seams was proposed. The static load stress of the workface was monitored by using the vibration wave CT inversion technology, and the disturbance stress of the workface was monitored by using the microseismic system. The high stress and high disturbance areas monitored have experienced dynamic disaster manifestation events. Based on the mechanical model of disaster initiation, the dynamic disaster manifestation events were analyzed and calculated, validated the accuracy of the model. The research results provide a theoretical basis for the monitoring and prevention of compound dynamic disasters in deep mines.

To address the frequent occurrence of rock burst in deep mining at Yuejin Coal Mine and the inaccuracy of traditional single-index early warning, this study integrates electromagnetic radiation (EMR), microseismic (MS) monitoring, and on-site observations to systematically analyze the precursors and mechanisms of rock burst in the 25,110 working face. The results show that EMR signals exhibit three temporal patterns: rise-then-fall (71.4% of events), continuous fall, and continuous rise. Spatially, EMR intensity in the damage zone increases significantly 1-2 days before a rock burst, and bursts mainly occur in areas 0-50 m or beyond 200 m from the working face. MS signals follow a consistent rise-then-fall pattern: energy and frequency increase 4-9 days before the burst, peak 1-5 days later, then decline, with the burst occurring 2-3 days after the decline begins. Based on the energy response and perturbation effect of EMR signals, three precursory mechanisms are identified: "rising (falling)", "∧" shaped, and "N" shaped, corresponding to different failure stages of coal-rock under loading. These findings provide theoretical support for precise, multi-parameter early warning of rock burst in coal mines.

Electrical resistivity imaging technology provides an effective solution for geotransparency of underground roadways. In this paper, we use finite-element method simulations to obtain coupled equations for the resistivity of the representative elementary volume (REV) and propose a method for inversion of apparent porosity. The main conclusions are as follows: the resistivity of the REV is affected by the combined effect of resistivity and porosity. The porosity-resistivity change path is the basic path that characterizes the resistivity of the REV. A coupled equation for REV resistivity is established based on the differential effective medium approximation (DEMA), and the calculation equation of the apparent porosity of a coal rock body is derived. An inversion method of apparent porosity based on apparent resistivity data is proposed. The field results show that the apparent porosity varies significantly in the disturbed area and less in the undisturbed area. This study helps to improve the quantitative analysis for geotransparency of a deep coal rock state.

The impact mechanism of long-term creep in gas-containing coal on coal and gas outbursts has not been fully elucidated and remains insufficiently understood for the purpose of disaster engineering control. This investigation conducted triaxial creep experiments on raw coal specimens under controlled confining pressures, axial stresses, and gas pressures. Through systematic analysis of coal’s physical responses across different loading conditions, we developed and validated a novel creep damage constitutive model for gas-saturated coal through laboratory data calibration. The key findings reveal three characteristic creep regimes: (1) a decelerating phase dominates under low stress conditions, (2) progressive transitions to combined decelerating–steady-state creep with increasing stress, and (3) triphasic decelerating–steady–accelerating behavior at critical stress levels. Comparative analysis shows that gas-free specimens exhibit lower cumulative strain than the 0.5 MPa gas-saturated counterparts, with gas presence accelerating creep progression and reducing the time to failure. Measured creep rates demonstrate stress-dependent behavior: primary creep progresses at 0.002–0.011%/min, decaying exponentially to secondary creep rates below 0.001%/min. Steady-state creep rates follow a power law relationship when subject to deviatoric stress (R2 = 0.96). Through the integration of Burgers viscoelastic model with the effective stress principle for porous media, we propose an enhanced constitutive model, incorporating gas adsorption-induced dilatational stresses. This advancement provides a theoretical foundation for predicting time-dependent deformation in deep coal reservoirs and informs monitoring strategies concerning gas-bearing strata stability. This study contributes to the theoretical understanding and engineering monitoring of creep behavior in deep coal rocks.

For the actual combination of experimental results and engineering applications, it is of great significance to explore the influence of size on tensile failure behavior. Brazilian tests are carried out on granite and sandstone with different diameters to investigate size-dependent behavior of tensile failure and the affected acoustic and electromagnetic law. Only when the specimen reaches the peak load and the stress drops sharply after the final failure, there is an extremely significant acoustic and electromagnetic response. The tensile strength and Brazilian split modulus decrease in larger specimens, and the dispersion of repeated tests is also reduced. As the size of the rock disc increases, the acoustic emission activity generated from the final splitting failure gradually decreases, while the fractal dimension values of acoustic emission activity also show an increasing trend. It is indicated that relatively less activity occurred around the peak load in larger rocks and greater amounts of acoustic emission activity are generated before the final splitting failure. According to the failure type characterized by the parameter (RA-AF), the ratio of tensile fracture decreases with the increase of diameter. In the case of a larger size, the electromagnetic signal generated by the splitting failure is dominated by the lower frequency band. The size-dependent failure behavior can be attributed to the volume and microstructure differences in rock specimens. This further leads to varying degrees of charge and elastic energy accumulation at the microscale, ultimately affecting acoustic and electromagnetic signals.

The role of bedding angle on the mechanic properties and failure modes of shale under cyclic loading and unloading conditions is unclear. This study conducted uniaxial cyclic loading and unloading tests on shales from the Longmaxi Formation with different bedding angles (B = 0 degrees, 22.5 degrees, 45 degrees, 67.5 degrees and 90 degrees), and characterized their damage evolution through both AE and charge signals. Results show that the compressive strengths are higher, and the loading cycles are more in specimens with B = 0 degrees and 90 degrees than those with B = 22.5 degrees, 45 degrees and 67.5 degrees during cyclic loading tests, resulting in a silent period of signaling presented in former but not in latter B. Both AE and charge signals can well reflect the major damages in time-domain analysis, while only charge signals can characterize the minor damages at the silent stages by continuous wavelet transforming into time-frequency plots, leading to their advantages in characterizing the damage evolution in specimens with B = 0 degrees and 90 degrees, but not with B = 22.5 degrees, 45 degrees and 67.5 degrees. These differences can be attributed to their different signal acquirement mechanisms. These findings highlight the effectiveness of charge signals in characterizing the shale damage evolution under loading and unloading conditions.