Adsorption Characteristics and Micromechanical Properties of CH₄‑Containing Coal under the Coupling Effect of...

Deep coalbed methane resources exhibit substantial potential and hold significant strategic importance. This study employs Grand Canonical Monte Carlo (GCMC) simulations and molecular dynamics (MD) methods to investigate the adsorption characteristics and mechanical properties of coal slit-pore models under coupled temperature-pressure conditions. Slit-pore models containing adsorbed methane are constructed with different initial pressures (0, 5, 10, 20 MPa) and temperatures (303.15, 338.15, 363.15, 393.15 K), with external stress applied to the models. Based on stress-strain curves in the elastic phase, the deformation characteristics and mechanical parameters (Young's modulus, Poisson's ratio, and bulk modulus) of slit-pore models under coupled temperature-pressure conditions are analyzed. The results indicate that the adsorption capacity of slit-pore models for methane increases with rising gas pressure, following the Langmuir model, while decreasing with increasing temperature. The change in the models with external stress can be divided into three stages. Under the same temperature and external stress conditions, the resistance to deformation progressively weakens with increasing gas content. Under the same gas content and external stress conditions, the resistance to deformation gradually enhances with rising temperature. Young's modulus, Poisson's ratio, and bulk modulus all increase with higher gas content and temperature, but there are differences in their response mechanisms. Poisson's ratio and bulk modulus demonstrate a nonlinear response to increasing external stress: rapid initial decline, followed by gradual reduction, and eventual slow recovery. This work reveals the evolution mechanisms of adsorption characteristics and mechanical behavior in deep coal seams under coupled temperature-pressure-stress controls. The results provide a theoretical basis for evaluating deep coalbed methane reservoirs and identifying optimal "sweet spots."