Structural Characterization and High-Pressure Methane Adsorption Mechanism Across Different Coal Ranks: Insights from Molecular Modeling

To elucidate coalbed methane (CBM) adsorption mechanisms in deep coal reservoirs, the macromolecular structures of coal samples with different coal ranks were characterized using FTIR, XPS, and C NMR, followed by the construction of corresponding molecular models. Grand Canonical Monte Carlo (GCMC) simulations were employed to investigate methane adsorption behavior within the coal matrix at 313.15 K and pressures up to 20 MPa. The results showed that as coal rank increased (Ro,max = 1.63% to 3.18%), the coal macromolecular structure transformed from a side-chain-rich configuration to a highly aromatized and directionally stacked structure. This structural maturation leads to a more compact coal matrix, evidenced by a reduction in free volume from 5108.39 Å3 to 3999.87 Å3 and a decline in accessible free volume from 8.23% to 6.26%, thereby restricting the effective space for methane storage. At 20 MPa, although the pore walls of high-rank coal exhibit stronger localized adsorption capacity, the bulk adsorption capacity follows the order: DZ > ZC > SH. This suggests that under deep, high-pressure conditions, the pore-volume compression effect associated with increasing coal rank governs the upper limit of adsorption per unit mass of coal. As pressure increases into the deep reservoir regime, the state of methane in coal micropores gradually shifts from surface adsorption to a high-density, quasi-liquid filling behavior. Consequently, the influence of specific surface area diminishes, while effective free volume emerges as the primary determinant of high-pressure adsorption capacity. The impact of coal rank on deep methane adsorption reflects a competition between enhanced adsorption potential and restricted storage space. The densification-induced compression of effective free volume is identified as the dominant factor limiting the adsorption capacity of deep CBM. This study provides a molecular-scale understanding of deep CBM occurrence mechanisms and establishes a theoretical framework for resource evaluation.