Multiphysics coupling framework for permeability dynamics in coal/shale reservoirs under gas injection: Poroelastic-hydrodynamic synergy

Accurate modeling of rock permeability evolution during gas injection is critical for tight gas recovery. However, this process is complicated by the interaction of poroelastic and fluid dynamic effects. Current permeability models for shale and coal formations either overlook multi-mechanism fluid flow effects or introduce slip-flow corrections to poroelasticity-based formulations. These approaches create theoretical inconsistencies that lead to quantitative mismatches with experimental data. This study critically evaluates existing poroelastic–fluid coupling strategies, revealing critical integration limitations. To resolve this, we present a unified framework that hierarchically couples poroelastic deformation with flow-regime transitions. The model links stress-dependent behaviors to continuous flow regimes and quantifies fluid dynamics using dynamic hydraulic apertures. A differential strain-based poromechanical formulation incorporates volumetric strain constants and adsorption properties to capture non-uniform rock deformation. These coupled mechanisms govern permeability evolution. By clarifying the distinction between initial and intrinsic permeability, our multiphysics-based model resolves normalization discrepancies among conventional coupling methods when validated against experimental datasets. This framework provides a scalable analytical architecture for accurately predicting permeability dynamics across wide pressure ranges, addressing long-standing challenges in permeability modeling. Furthermore, sensitivity analysis of the differential swelling index (f) shows adsorption-driven deformation primarily impacts moderate permeability ranges, not overall trends. In coal, f has narrow variability due to coordinated fracture–matrix interactions, while shale exhibits broad f ranges from dominant matrix swelling with limited fracture deformation. This work bridges experimental-theoretical gaps, improving permeability prediction accuracy and providing a strong foundation for analytical model development.