Under the background of deep coal mining and low-carbon energy transformation, it is significant to study the gas adsorption mechanism and pore size regulation of coal to ensure the safe and efficient development of coalbed methane and promote the goal of Carbon Neutrality. Based on the GCMC method, a full pore size model of 0.4–200 nm is systematically constructed, and the adsorption behavior of CH4 in coal under different pressure conditions is simulated and analyzed, revealing the influence mechanism of pore size on adsorption characteristics. The results show that the micropore region (0.4–1.8 nm) is dominated by the coupling of potential fields on both sides of the pore wall, and the adsorption phase density is close to that of liquid methane, which conforms to D-A model. The mesoporous region (3–30 nm) shows multi-layer adsorption under the action of a single pore wall, and Langmuir model has the best fitting effect. The adsorption behavior of the macroporous region (50–200 nm) is close to that of free gas, which is more in line with BET multi-layer adsorption theory. By establishing the quantitative function relationship between the adsorption parameters such as V0(d), VL(d) and Vm(d) and the pore size, a comprehensive adsorption model suitable for the full pore size range was constructed. It was found that the adsorption phase density decreased in three stages as the pore size increased (micropores decreased by 40%, mesopores decreased by 63%). The model can accurately characterize the adsorption behavior of CH4 with full pore size, and the error is less than 6%. This error verifies the reliability of the constructed comprehensive adsorption model in predicting CH4 adsorption behavior in cross-scale pores, indicating that the model can effectively integrate the multi-adsorption mechanism dominated by micropore filling, mesoporous surface adsorption and macroporous multi-layer adsorption, which provides an important theoretical basis and prediction tool for accurate evaluation of coalbed methane reserves and optimization of development schemes.
Bai et al. (Wed,) studied this question.