CO2 injection into deep coal seams is an effective approach for large-scale carbon emission reduction and simultaneous coalbed methane recovery. Coal wettability directly governs fluid migration pathways and storage stability. However, the structural origin of wettability evolution induced by supercritical CO2 (ScCO2) remains unclear. This study investigated time-dependent ScCO2-coal interactions under representative deep reservoir conditions (60 degrees C, 19 MPa) over 30 days. By integrating Nuclear Magnetic Resonance, Fourier Transform Infrared Spectroscopy, X-ray Diffraction, and contact-angle measurements, we systematically revealed the mechanism of how chemical structural transformations alter coal wettability induced by ScCO2. The results demonstrate that, at the molecular and mineralogical levels, ScCO2 preferentially cleaves polar oxygencontaining functional groups, promotes the tighter stacking of hydrophobic aromatic layers, and induces the selective dissolution of hydrophilic minerals (such as calcite and ammonium mica). These fundamental chemical and mineralogical removals directly disrupt the existing matrix framework, driving a structural transition of the pore system from a micropore-dominated state to a mesopore- and macropore-dominated state with enhanced surface heterogeneity. Synergistically driven by this chemical depolarization and physical pore expansion, the water contact angle of the coal increased significantly from 63.7 degrees to 85.8 degrees. This progressive reduction in water wettability subsequently lowers the capillary resistance of the deep coal reservoirs. Ultimately, these findings indicate that dynamically adjusting injection parameters (e.g., volume and rate) based on real-time wettability evolution can optimize ScCO2-coal interactions, thereby improving CO2 injectivity, operational safety, and enhanced coalbed methane recovery efficiency.

Understanding the phase behavior of methane within confined nanopore spaces is critical for interpreting its occurrence and transport in coalbed methane reservoirs. Conventional adsorption characterization methods and previous nuclear magnetic resonance (NMR)-based approaches focus on bulk adsorbed methane properties but fail to capture density and volume variations across different micropore and mesopore environments. Building upon the NMR DensTrack framework provided in Part I, we further developed a mathematical model that determines the changes in density and volume of adsorbed methane across different confined spaces, enabling a mechanistic analysis of methane adsorption behavior from the perspective of its phase and physical states. Results showed that both the adsorbed methane density and volume in micropores exhibit a typical Langmuir-type growth trend with increasing pressure. Under strong confinement effects, micropores are gradually filled by methane and eventually become almost completely occupied. In contrast, the adsorbed methane density in mesopores is significantly lower than that in micropores, and only about 30 % of the mesopore volume is occupied by methane. Interestingly, the model analysis revealed that the variation pattern of adsorbed methane volume in mesopores differs from our current understanding. Mesopores can compensate for their low adsorbed methane density by providing a large adsorbed methane volume, thereby making a major contribution to total methane adsorption. This finding suggested that current research on methane adsorption mechanisms may have relied excessively on specific surface area as the main criterion for adsorption contribution, while neglecting the volume dominant role of effective adsorption pore space.

Coal seam water injection technology is widely used as an active and fundamental dust reduction measure. However, the characteristics of low porosity in high ground stress coal seams will make it difficult to inject and store water, which limits the dust reduction effect of coal seam water injection. To improve this situation, an idea of physical modification of coal by liquid CO2-water cold soaking cycle was proposed. The coal matrix strain rate was used as the response value, and the optimal parameters of cycle cold soaking test were determined by numerical simulation and response surface analysis. Multi-detection methods were used to analyze the evolution of pore-fracture structure, surface morphology and mineral composition of the coal before and after cycle. The results indicate that the liquid CO2-water cycle cold soaking has an obvious cracking effect on pore-structure of different scales. After three cycles of cold soaking, the coal pillar samples ultrasonic velocity Vs, VP, the slopes and R2 of the fitted straight lines of VP-VS scatter points decreased by 28.4 %, 27.8 %, 0.088 and 0.104 respectively, the surface of the coal became loose and granular, and the pore edges became more complex. The average porosity of 0.1-30 mu m surface pores increased from 0.01 % to 1.04 %, the variety and quantity of pores significantly increased, and the two-dimensional fractal dimension of the pores increased by 0.60. The volume of 0 to 100 nm pores increased by 52.43 %, and the specific surface area increased by 39.44 %. The effective elimination of minerals by frost heaving and crushing, acidification and corrosion, and water separation is an important reason for the growth of 0-100 nm pores. Liquid CO2 and water exhibit synergistic fracturing effects, and the liquid CO2-water cyclic process achieves more significant fracturing results compared to using liquid CO2 alone. This research offers a novel approach to enhance coal seam water injection for dust prevention capacity.

Quantitative characterisation of multiscale mechanical failure in heterogeneous coal is critical for mitigating subsurface engineering risks, such as borehole instability and hydraulic fracture containment failure during geoenergy extraction. However, accurate predictive modelling is hindered by the intrinsic disconnect between microscopic sedimentary textures and macroscopic engineering responses. To delineate the controls governing multiscale mechanical behaviour, we employed an integrated methodology combining non-destructive geophysical evaluation, advanced experimental mechanics, and grain-based discrete element modelling (GBM-DEM). Specifically, ultrasonic testing and high-fidelity in situ X-ray computed tomography (CT) under varying triaxial confining pressures were used to capture the dynamic evolution of damage and stress-induced anisotropy. This workflow is complemented by a novel deep-learning segmentation approach (MSR-EnlightenGAN-DeepLabV3+) to resolve sub-resolution natural fracture networks, enabling the reconstruction of high-precision digital rock models. By explicitly mapping the micro-mechanical contrast between brittle vitrinite matrices and stiff inertinite inclusions via nanoindentation and a dual-channel neural network (ResNet34-MLP), we revealed a hierarchical control system governing damage evolution. We observed a distinct “mechanical invasion” phenomenon, in which stiff inertinite grains act as stress concentrators, inducing localised shear bands that propagate into the softer vitrinite matrix. Crucially, our quantitative results demonstrate that primary sedimentary fabrics—specifically the vitrinite-to-inertinite ratio—override post-depositional thermal maturity in dictating the fundamental mechanical strength and failure modes. Furthermore, the anisotropy induced by historical stress states and natural fractures significantly dictates the structural damage pathways. This study established a mechanism-based upscaling framework that translates microstructural geological attributes into macroscopic failure criteria and proposes that simple macrolithotypes serve as a robust, cost-effective geological index for rapid stability assessment in underground engineering projects.

Liquid CO₂ (L-CO₂), with its phase-transition expansion and low viscosity, is a promising preconditioning fluid for permeability enhancement and dust reduction by coal seam water injection. However, liquid CO₂ fracturing (LCF) still has challenges, such as high-pressure phase behavior control and a lack of systematic testing system. Moreover, the mechanisms of liquid CO₂ and water cyclic fracturing (LCWCF) remain unclear. To address these gaps, a novel coal testing system for low-temperature fluid cyclic fracturing and wetting enhancement was developed. The functions and working principles of each module were introduced, and key technical issues, such as pulse-free cyclic injection and thermo-hydro-mechanical (THM) multi-field coupling, were resolved. Hydraulic fracturing (HF), LCF, and LCWCF experiments were conducted with synchronous acquisition of pressure and acoustic emission (AE) data. The results show that the system can precisely control stress and temperature to reproduce in situ coal seam conditions at the laboratory scale. Alternating injection of L-CO₂ and water overcame the limitations of a single fluid mode. Compared with HF, both LCF and LCWCF achieved higher fracturing efficiency. LCWCF, combining L-CO₂ phase transformation and water stress transmission, enabled faster fracture initiation, with a first-cycle breakdown pressure of 18.21 MPa, and reduced pressure demand in subsequent cycles. Moreover, LCWCF produced a step-like cumulative AE response, with 31.99

The effectiveness of coal seam water injection is fundamentally governed by fluid transport processes within complex pore-fracture networks. However, existing CT image segmentation methods for coal often exhibit limited capability in resolving blurred boundaries, leading to insufficient characterization of pore topology and an incomplete understanding of the relationship between pore structure and seepage properties. In this study, a coal-rock multiphase adaptive segmentation network (CMAS-Net) based on the Swin Transformer was developed to segment CT images of five coal samples representing different coal ranks. The proposed method enables robust identification of pore-fracture systems, coal matrix, and mineral phases, and allows quantitative extraction of effective porosity (ϕe), fractal dimension (Df), and tortuosity (τ). The network achieved a mean intersection over union (MIoU) of 85.33

Hydraulic fracturing can significantly enhance coalbed methane production, with in-situ stress playing a crucial role in this process. Our study focuses on calculating in-situ stress in the deep 8+9# coal seam in the north-central Zijinshan block. Leveraging data from acoustic logging and hydraulic fracturing tests, we developed a stress prediction model tailored to the area’s geology. We analyzed stress’s impact on fracturing behavior and the origins of mechanical anisotropy in deep coal reservoirs using μ-CT imaging. Our results show that the Anderson-modified model, accounting for transverse isotropy, offers greater accuracy and applicability than traditional models. The study area exhibits a normal faulting stress regime with significant stress contrasts and maximum horizontal principal stress aligned with the east-west geological stress direction. After hydraulic fracturing, fractures form a complex fracture system resembling elongated ellipses in the coal reservoir, primarily extending in the vertical direction. To control fracture height and prevent penetration through the roof and floor, regulatory measures are essential. μ-CT analysis revealed the distribution of primary fractures, pores, and minerals in the coal, contributing to mechanical anisotropy. This research advances CBM development in the Zijinshan block and similar regions by refining stress prediction and fracturing propagation methods.

Coal seam CO2 sequestration is a promising approach for geological carbon storage, where CO2 injection inherently displaces pore water. The migration and retention of CO2 are strongly affected by water evolution within coal, which, in turn, is governed by the CO2 behavior. However, the redistribution of water under different CO2 phases (gaseous, liquid, and supercritical) remains poorly understood. In this study, nuclear magnetic resonance (NMR) was used to monitor water saturation in adsorption and seepage pores during displacement experiments involving three CO2 phases. Results revealed a two-stage displacement process: an initial seepage-dominated stage characterized by free water removal, followed by an adsorption-driven stage involving the desorption of adsorbed water. An adsorption kinetic model was fitted to the data, confirming that the reduction in adsorbed water is primarily attributed to competitive CO2 adsorption. Among the experimental conditions, supercritical CO2 exhibited the highest displacement efficiency in adsorption pores, whereas liquid CO2 achieved stronger displacement in seepage pores. The overall displacement efficiency was governed by the interfacial tension, density difference, viscosity ratio, and related factors. Gaseous CO2, with the highest interfacial tension against water, generated the greatest capillary resistance and thus lower efficiency, while its large density difference with water further impeded displacement. By contrast, liquid CO2, characterized by a smaller viscosity ratio to water, displaced water more effectively and demonstrated higher efficiency in seepage pores. Extrapolation to the reservoir scale indicates that supercritical CO2 offers superior displacement potential for long-term injection. These findings suggest that selecting supercritical CO2 and ensuring an adequate injection duration are essential for maximizing storage efficiency in coal seams.

The Qinshui Basin is renowned for its thick, laterally extensive coal seams, high thermal maturity, and significant coalbed methane (CBM) potential. However, reservoir heterogeneity resulting from multi-stage tectonic activity leads to pronounced variability in CBM enrichment, posing challenges for efficient development. This study examines the influence of individual and coupled tectonic, roof-floor lithological, and hydrodynamic factors on CBM accumulation in the southern Qinshui Basin, using seismic data, well logs, and gas content analysis. Four distinct CBM enrichment models are identified from north to south: in shallow seams, atmospheric precipitationdriven groundwater recharge, coupled with anticlinal structures, controls the spatial distribution of gas; with increasing burial depth, reduced groundwater mobility and improved roof-floor sealing shift the dominant control from hydrodynamic to lithological factors; in structural slope zones, gas enrichment is governed by the coupling of nose structure and hydrodynamic sealing; In fault-dominated areas, gas migration along faults and the sealing capacity of fault zones are the primary controls. These findings provide a scientific basis for optimizing CBM exploration and development in geologically complex basins.

Deep coal reservoirs (buried depth > 2000 m) represent a significant yet underexploited resource for coalbed methane (CBM) production. In these reservoirs, CBM primarily exists in adsorbed and free phase, with the pore structure playing a critical role in gas storage and migration. The Jiaxian block in the northeastern Ordos Basin, has emerged as a key area for deep CBM exploration due to its promising resource potential. However, the pore structure characteristics of the No. 8 coal seam in Jiaxian block and their implications for gas storage and production remain poorly understood. A comprehensive characterization of the No. 8 coal seam's pore structure is conducted in the study using multiple methods including high-pressure mercury injection, N2/CO2 adsorption experiments, and integration of measured core gas content data and production history. The study results reveal that the pores can be mainly classified as vesicles and cellular pores, and the fractures are mainly static pressure fractures. Micropores (pore diameter < 10 nm) dominate the pore system (accounting for more than 99 % of the total specific surface area), providing important adsorption sites for gas storage. Although mesopores (pore diameter of 100–1000 nm) and macropores (pore diameter > 1000 nm) account for a small proportion, they feature effective storage spaces and interconnectivity, resulting in a high proportion of free gas. Therefore, the reservoirs shows great development potential after stimulation (such as hydraulic fracturing). These findings emphasize the feasibility of large-scale and long-term development of CBM in the Jiaxian block in terms of reservoir space, gas content and production characteristics. This study serves to lay a scientific basis for its efficient exploitation.

The abnormal thermal effect caused by igneous intrusion has an important influence on the exploration and development of deep coalbed methane. Compared with coals with normal burial depth, coals affected by igneous intrusion or magmatic hydrothermal fluids have obvious changes in reservoir properties of coalbed methane (CBM). The differences between coal reservoirs affected by igneous intrusion thermal effects and undisturbed normal reservoirs need to be investigated. In this work, eight coals from four CBM exploration wells at different distances from igneous intrusion in the Benxi formation were selected from the Zijinshan block of the eastern Ordos Basin. Results indicate that igneous intrusion significantly elevated coal maturity while causing irregular increases in moisture and ash content alongside decreased volatile matter. It further promoted secondary hydrocarbon generation, reduced dolomite content, and enriched hydrothermal minerals/elements. Furthermore, the relationship between the igneous intrusion and the pores in the coals was revealed: <2 nm super micropores contribute the most to the pore volume (PV) and specific surface area (SSA) of the total pore space, and igneous intrusion makes the pore size distribution of the super micropores more complex, which mainly leads to the development of micropores and small pores. Finally, the influence of igneous intrusion on the pore complexity of the coal was analyzed, and it was found that the influence of magmatic heat makes the fractal dimension of medium and large pores decreases with the closer distance to the igneous intrusion, but the fractal dimension of micropores and small pores increases significantly, which increases the surface area of the pores in the coal and leads to the pore surface to be rougher. This study may help understand the multiscale pore structure of deep coalbed methane reservoirs influenced by magmatic thermal effects, providing critical theoretical and technical guidance for optimizing natural gas production in high metamorphic coal regions.

Abstract Due to the sensitivity of microorganisms to the environment, microorganisms with strong tolerance in the early stage of coal mining collapse will gradually move to a dominant position, and plants can improve soil quality and provide important carbon sources for microorganisms. The soil characteristics and the response of soil bacteria in the early cracks during 15 ~ 20 days of mining were studied. Compared with non-cracked farmland group (C), soil bulk density in cracked farmland group (F) increased significantly in the early stage of coal mining,while porosity was on the contrary (p < 0.05). The mineral elements (except Ca and Na) in F were significantly lower than those in cracked abandoned land group (A).The abundance of the microbial community might be more closely related to crop planting, while the evenness of the microbial community was more affected by cracks. Coal mining cracks make Proteobacteria enrich significantly, while crop planting is conducive to the enrichment of RB41 and Pir4_lineage. Soil moisture content and AN were significantly negatively correlated with the relative abundance, while pH was significantly positively correlated with it. Planctomycetes and Bacteroidetes, which were significantly enriched in the non-crack area, were significantly positively correlated with AP, while Thaumarchaeot was significantly positively correlated with Eh. The study provided a basis for improving the low ecological environment damage mining technology.

Acid fracturing technology is considered one of the most effective methods to resolve mineral plugging and improve the pore structure of coal reservoirs. To investigate the characteristics of shallow and deep coal nanopore structures under the influence of acidic fracturing fluids, experiments using synchrotron radiation small-angle X-ray scattering (SAXS) were conducted on shallow and deep coal samples soaked in acidic fracturing fluids of different concentrations for varying durations. This quantitatively characterized the different nanoscale pore scattering intensity ratios AI, fractal dimensions, porosity, specific surface area, and average pore diameter. The research indicates that under the influence of acidic fracturing fluids, the shallow coal nanopore structure tends to become more complex, while that of deep coal becomes simpler. The impact of 20% acidic fracturing fluid is greatest on shallow coal nanopore structure, while deep coal nanopore structure is more susceptible to 12% acidic fracturing fluid, with these effects primarily concentrated in the 2–10 nm pores. Acidic fracturing fluids primarily affect the shallow and deep coal nanopore structures by dissolving carbonate minerals, pyrite, clay minerals, etc., resulting in the dynamic evolution of the shallow and deep coal nanopore structures during the soaking process.

The brittleness index is one of the most integral parameters used in assessing rock bursts and catastrophic rock failures resulting from deep underground mining activities. Accurately predicting this parameter is crucial for effectively monitoring rock bursts, which can cause damage to miners and lead to the catastrophic failure of engineering structures. Therefore, developing a new brittleness index capable of effectively predicting rock bursts is essential for the safe and efficient execution of engineering projects. In this research study, a novel mathematical rock brittleness index is developed, utilizing factors such as crack initiation, crack damage, and peak stress for sandstones with varying water contents. Additionally, the brittleness index is compared with previous important brittleness indices (e.g., B1, B2, B3, and B4) predicted using infrared radiation (IR) characteristics, specifically the variance of infrared radiation temperature (VIRT), along with various artificial intelligent (AI) techniques such as k-nearest neighbor (KNN), extreme gradient boost (XGBoost), and random forest (RF), providing comprehensive insights for predicting rock bursts. The experimental and AI results revealed that: (1) crack initiation, elastic modulus, crack damage, and peak stress decrease with an increase in water content; (2) the brittleness indices such as B1, B3, and B4 show a positive linear exponential correlation, having a coefficient of determination of R2 = 0.88, while B2 shows a negative linear exponential correlation (R2 = 0.82) with water content. Furthermore, the proposed brittleness index shows a good linear correlation with B1, B3, and B4, with an R2 > 0.85, while it shows a poor negative linear correlation with B2, with an R2 = 0.61; (3) the RF model, developed for predicting the brittleness index, demonstrates superior performance when compared to other models, as indicated by the following performance parameters: R2 = 0.999, root mean square error (RMSE) = 0.383, mean square error (MSE) = 0.007, and mean absolute error (MAE) = 0.002. Consequently, RF stands as being recommended for accurate rock brittleness prediction. These research findings offer valuable insights and guidelines for effectively developing a brittleness index to assess the rock burst risks associated with rock engineering projects under water conditions.

In the current global landscape, Environmental, Social, and Governance (ESG) serves as a vital metric for measuring the sustainable development level of listed companies. With respect to this matter, government departments and company managers have gradually taken notice of the company’s ESG performance. This paper proposed a theoretical model that integrates Scott’s institutional theory and the social embedding theory to evaluate the cognitive characteristics of top managers. Focusing on the period spanning from 2011 to 2020, an examination was conducted on the influence of executive cognitive characteristics on the ESG performance of enterprises under the moderating effect of local fiscal intervention. The empirical analysis results highlighted that executive compensation incentives, educational background, and political association had a promoting effect on the ESG performance of enterprises. Equally crucial, the greater the level of political correlation among executives, the less beneficial it is for the advancement of ESG performance among enterprises. Further research results underlined that local fiscal intervention had a negative moderating effect on the relationship between executive compensation incentives, educational levels, and political association levels on enterprise ESG performance, that is, in areas where there is a significant degree of local fiscal intervention. Ultimately, local fiscal intervention weakens the relationship between executive characteristics and ESG performance.

Early warning of the catastrophic failure of rocks is a challenging rock mechanics problem. This article proposed a failure precursor recognition method based on infrared thermal image texture features for coal and rock. Based on spatiotemporal background noise correction for infrared thermal images, a new thermal image parameter of loading coal and rock, Contrast Texture Feature Values (CTFV), is proposed to extract subtle changes in the thermal image caused by crack evolution based on the Gray Level Co-occurrence Matrix (GLCM). The cumulative Crack Texture Thermal Image (CTTI) is reconstructed using CTFV, which can accurately reflect the spatial evolution process of loading coal and rock cracks. The CTFV remains at 0 in the early stage of loading and gradually increases with stress increase at the unstable crack propagation stage, which can serve as a reference for precursor warning of coal and rock failure. For shale, sandstone, and limestone, the precursor of CTFV at grayscale levels of 7, 8, and 9, can be classified into high failure risk, medium failure risk, and low failure risk, respectively. For coal samples, the CTFV is only applicable for the critical warning of high failure risk when the grayscale level is 7. Then, an adaptive identification method for failure precursors based on the sliding window probability density estimation method is proposed. The research results can enhance the reliability of IR monitoring technology for rock failure and instability early warning and can provide support for the prevention and control of rock engineering and geological disasters.

Accurate quantification of the coexistence of adsorbed and free gas content holds the utmost significance for estimating gas-in-place resources and predicting gas production dynamics. In this study, we conducted real-time isothermal adsorption experiments and NMR fluid monitoring on stress-confining core samples, from the Zhengzhuang Block's No.3 coal seam in the southern Qinshui Basin. Our focus was on assessing multi-phase methane gas contents within coal under various pressure and temperature (P/T) conditions. By integrating experimental findings with adsorption potential theory and the SDR adsorption model, we developed comprehensive models for adsorbed, free, and total gas contents as functions of P/T and water/gas volume saturation. Utilizing these models, we predicted vertical variations in adsorbed and free gas contents within the coal seam. Our results revealed that the interplay between positive reservoir pressure effects and adverse reservoir temperature effects influenced both adsorbed and free methane gases. With increasing burial depth, the influence of pressure on adsorbed gas diminished, while temperature effects became more pronounced. Conversely, free gas content responded noticeably to reservoir pressure, with temperature exerting a marginal influence. Additionally, we performed a numerical simulation to reconstruct the thermal history, burial trajectory, and evolution of reservoir pressure for the No.3 coal seam. The simulation results served as foundational data for understanding the evolution of free and adsorbed gas contents across different geological epochs within the in-situ reservoir. Our findings unveiled a four-stage evolutionary progression in both adsorbed and free gas contents, correlating with the uplift and subsidence of the coal seam. In conclusion, our study provides a conceptual model elucidating the intricate, deep-time evolution process and mechanisms governing the occurrence of multiphase gases across distinct geological epochs. The implications of this research are crucial for accurately evaluating gas-in-place resources and guiding the exploration and development of deep coalbed methane resources.

Accurately predicting geologically rock loading phases under varying water levels is crucial to prevent rock engineering operations from severe geological hazards. Acoustic emission (AE) traditionally determines these phases, but machinery in rock projects can disrupt AE sensors, leading to imprecise data and potential accidents. To address this, our study tested a novel approaches using AE, Average Infrared Radiation Temperature (AIRT), Critical Slow Down Theory (CSDT), and Convolutional Neural Networks (CNNs) to predict rock loading phases accurately under different water conditions. The research findings are: (1) AE analysis divides the stress-strain curve into four phases: crack closure, elastic deformation, and stable and unstable crack propagations. Each phase exhibits distinct characteristics in terms of AE signal behavior. (2) AIRT analysis reveals specific patterns during different loading phases. The AIRT and cumulative AIRT have distinct trends in different phases. (3) The AIRT sequence's fractal dimension shows distinct trends during loading phases: it initially rises during the elastic phase and then declines. Fractal dimensions for crack closure, elastic deformation, and stable crack propagation increase, while that for unstable crack propagation decreases with water content. (4) The stress-strain curve phases were successfully predicted by using AIRT and CSDT, demonstrating a strong correlation with actual stress levels. Notably, this marks the first-time prediction of phases through non-destructive tests (IR and CSDT), where CSDT fluctuations at each stage can serve as early indicators of rock failure. (5) The proposed CNNR model achieves high accuracy (98%) in predicting different phases of the stress curve using AIRT. It particularly performs well in the elastic deformation and stable crack propagation phases, with only a few instances of false negative predictions. The model shows promising potential for effective and safe geological projects, especially under varying water conditions. The findings contribute to the understanding of rock behavior and offer insights for the design of safer and more efficient rock engineering projects.

In view of the low porosity and permeability of the coal seams that are difficult to inject water, and the difficulty of effectively wetting the coal body with the traditional water injection dust reduction technology, a new idea of improving the water injection effect of the coal seams by injecting liquid CO2 into the coal seams is proposed. In order to clarify the multi-field coupling evolution law of the liquid CO2 filling process in the coal seam with difficulty in water injection, this paper selects the Ji-15 coal seam of Minmetals in Pingmei Group as the research object. A multi-field coupling cooperation model of the liquid CO2 filling in the coal seam with difficulty in water injection was established by combining the Comsol finite element software and the Matlab data processing software. In view of the complex hole-fracture structure of the coal body, the heterogeneous distribution parameters are introduced, and the coal seam is divided into 10 000 areas through the Comsol with Matlab interface, and the Weibull distribution function is called to assign values to the material properties of all areas of the coal seam, so as to achieve the heterogeneous representation of the coal body material. Through the simulation of filling pressure, filling time and other parameter control variables, the multi-field coupling evolution of liquid CO2 filling process in coal seams with difficulty in water injection is analyzed. The results show that the expansion rate of the seepage channel, the extension range of the cooling zone, the ratio of tensile damage and compressive damage are positively correlated with the filling time and pressure of liquid CO2, and the evolution rate of seepage, cooling and damage area is more significantly affected by the filling pressure than the filling time; Compared with the filling pressure of 10 MPa, at 20 MPa, the number of branch flow channels with lower flow velocity in the outer region is significantly increased, and the ability to open the coal seam seepage channel is stronger; In the process of loading the filling pressure from 0 MPa to 30 MPa, the proportion of tensile damage and compressive damage of the coal seam finally reached 47.86% and 4.23%, respectively. The main damage of the coal seam is tensile damage, which is consistent with the constitutive relationship that the tensile capacity of the coal body is far lower than the compressive capacity. The research work can provide a theoretical basis for the research and development of coal seam liquid CO2 fracturing, moisture enhancement and disaster prevention technology.