A coupled thermal–hydraulic–chemical (THC) model was carried out in this paper to study the influence of rock heterogeneity and the coupling effect of temperature, groundwater, and hydrochemistry on rock damage. Firstly, the hydrochemical and hydraulic erosion equations were established. The equations of the coupled THC model were established by combining the hydrochemical and hydraulic erosion equations, the flow equations, and the heat transfer equations. Weibull distribution was adopted to govern the heterogeneity of initial rock porosity distribution. Secondly, the influence of the hydrochemistry, the temperature and the initial porosity heterogeneity on porosity and fluid velocity change was studied. Then the rock damage rule changed with time at different pH values and temperature was studied. Finally, an actual deep coal mine model was established to apply the THC model to predict water inrush. Results indicate that: (1) The average porosity and average fluid velocity approximately show linear growth and exponential growth with time, respectively, and their growth rates increase with decreasing pH value and increasing temperature in a certain acidity and temperature range. (2) The increase of initial porosity heterogeneity has little influence on porosity change, but it can increase the fluid velocity growth rate. The porosity heterogeneity and fluid velocity heterogeneity approximately show exponential growth with increasing time, and the rock heterogeneity growth contributes to form cracks. The increase of temperature and decrease of pH value have little influence on the porosity heterogeneity, but they can increase the growth rate of the fluid velocity heterogeneity. (3) The rock damage shows linear growth with time, and its growth rate increases with decreasing pH value and increasing temperature in a certain acidity range and temperature range. (4) The increase of rock heterogeneity can increase the possibility of water inrush.

A coupled thermal-nonlinear hydraulic-mechanical (THM) model for fault water inrush was carried out in this paper to study the water-rock-temperature interactions and predict the fault water inrush. First, the governing equations of the coupled THM model were established by coupling the particle transport equation, nonlinear flow equation, mechanical equation, and the heat transfer equation. Second, by setting different boundary conditions, the mechanical model, nonlinear hydraulic-mechanical (HM) coupling model, and the thermal-nonlinear hydraulic-mechanical (THM) coupling model were established, respectively. Finally, a numerical simulation of these models was established by using COMSOL Multiphysics. Results indicate that the nonlinear water flow equation could describe the nonlinear water flow process in the fractured zone of the fault. The mining stress and the water velocity had a great influence on the temperature of the fault zone. The temperature change of the fault zone can reflect the change of the seepage field in the fault and confined aquifer. This coupled THM model can provide a numerical simulation method to describe the coupled process of complex geological systems, which can be used to predict the fault water inrush induced by coal mining activities.

Understanding and predicting floor failure depth is crucial for both mitigating mine water inrush hazards and safeguarding groundwater resources. Mining activities can significantly disturb the geological strata, leading to shifts and damage that may result in floor cracks. These disruptions can extend to confined aquifers, thereby increasing the risk of water inrushes. Such events not only pose a threat to the safety of mining operations but also jeopardize the sustainability of surrounding groundwater systems. Therefore, accurately predicting floor failure depth to take effective coal seam floor management measures is the key to reducing the impact of coal seam mining on water resources. Seventy-eight sets of data on coal seam floor failure depth in China were collected, and the main controlling factors were considered: mining depth (D1), working face inclination length (D2), coal seam inclination (D3), and mining thickness (D4). Firstly, the distance evaluation function based on Euclidean distance was constructed as the clustering effectiveness index, and the optimal cluster number K = 3 was determined. The collected data were clustered into three categories using the K-means clustering algorithm. It was found that the clustering results were positively correlated with the size of D1, indicating that D1 played a dominant role in the clustering. The D1 dividing points of the three types of samples were between 407.7~414.9 m and 750~900 m. On this basis, the grey correlation analysis method was used to analyze the order of the influence weights of the main controlling factors of coal seam floor failure depth. For the first group, the order was D2 > D1 > D3 > D4, while, in the other two, it was D1 > D2 > D3 > D4. D1 emerged as the most influential factor, surpassing D2. Therefore, D1 between 407.7 and 414.9 m could be used as the boundary, the first group could be classified as shallow mining, and the second and third groups could be classified as deep mining. Based on this boundary, CatBoost prediction models for the depth of coal seam floor failure in deep and shallow parts were constructed and the prediction results of the model test set were compared with the calculation results of the empirical formula. These models exhibited superior accuracy with a lower mean squared error (MSE) and mean absolute error (MAE) and a higher R-squared (R²) compared to the empirical formula. This study helps to enhance the understanding of coal seam floor behavior, guide floor management, and protect groundwater resources by defining deep and shallow mining to accurately predict floor failure depth.

This study investigates the permeability evolution in floor fault damage zones under stress–seepage–damage coupling, with a focus on water inrush risks caused by confined water upward conduction during deep mining. A stochastic fracture geometry model of the fault damage zone was developed using the discrete fracture network (DFN) model and the Monte Carlo method. Based on geological data from a mining area in Shandong, a multiphysics-coupled numerical model under mining-induced conditions was established with COMSOL Multiphysics. The simulations visually reveal the dynamic evolution of damage propagation patterns in the floor strata during working face advancement. Results indicate that the damage zone stabilizes after the working face advances to 80 m, with its morphology exhibiting strong spatial correlation to regions of high seepage velocity. Moreover, increasing confined water pressure plays a critical role in driving flow field evolution.