Fractal Metrics and Pore Architecture as Determinants of Diffusion in High-Rank Coal Reservoirs of the Mengjin Coalfield, Henan Province

Understanding the pore structure of high-rank coals is essential in evaluating gas storage and transport. Here, twelve semianthracite samples from the early Permian Shanxi Formation were investigated by proximate analysis, optical microscopy, low-temperature N2 adsorption, and fractal analysis, coupled with diffusion coefficient modeling. The coals exhibit diverse pore types (plant-cellular, interparticle, and dissolution pores) shaped by coalification and minerals and show Type IV (a) isotherms with H4 hysteresis loops, indicating complex pore networks. Pore-size partitioning reveals that mesopores and macropores dominate total pore volume, whereas mesopores contribute most of the specific surface area. The pore structure exhibits strong fractal characteristics with an average comprehensive fractal dimension (Fc) of 2.628. The calculated gas diffusion coefficient decreases monotonically with increasing pressure from 1 MPa to 5.8 MPa, with a more pronounced decline at low pressure, indicating a clear pressure-dependent attenuation effect. Diffusion capacity is weakly related to average pore diameter but shows positive correlations with total pore volume and, particularly, macropore volume. Multiple linear regression further demonstrates that pore volume structure is the dominant control on diffusion under both low- and high-pressure conditions, with the relative importance ranked as macropores > mesopores > micropores. Macropores provide the main low-resistance transport framework, mesopores serve as transitional pathways linking storage and transport domains, whereas micropores mainly contribute to gas storage and may even suppress apparent diffusion when overly developed. These results reveal a clear functional differentiation of multiscale pore systems and highlight that gas migration in semianthracite is jointly governed by pore size distribution, connectivity, tortuosity, and fractal network topology.