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The deep coal seam is the ideal place for CO2 geological storage, and its permeability is the key index to evaluate the geological storage ability. In this study, permeability tests on coal samples under triaxial stress were conducted. Combined with nuclear magnetic resonance and x-ray diffraction tests, the physical modification mechanism of coal sample under the action of water–CO2 and its effect on permeability were discussed. The results indicate that, due to effective stress and adsorption expansion, the internal pores of the coal samples are compressed and closed, resulting in narrower seepage channels. Under varying effective stress conditions, the permeability of coal samples with different moisture contents decreases before CO2 adsorption, after CO2 adsorption, and after CO2 desorption, as moisture content increases. However, due to competitive adsorption between water and CO2, the permeability of coal samples after CO2 injection is lower than that before injection. Under the combined effects of water and CO2, the coal matrix experiences complex interactions leading to mineral dissolution, precipitation accumulation, and changes in the composition and pore structure of the coal samples. After CO2 desorption, the permeability of coal samples exhibits an "M"-shaped change with increasing moisture content. The permeability of samples with 5.6% moisture content was lower than that before CO2 injection, whereas the permeability of other samples increased. The sample with moisture content of 2.8% showed the highest permeability, with the largest proportion of mesopores and macropores providing seepage channels. In contrast, the sample with moisture content of 5.6% had a reduced macropore volume proportion, making macropores the dominant factor in permeability. Based on these findings, a permeability model for coal samples was derived and its accuracy verified. The study reveals the influence mechanism of adsorption expansion, effective stress, and moisture content on the permeability of coal samples. [ABSTRACT FROM AUTHOR]

The complex fracture network in unconventional oil and gas reservoirs is the main channel for the fluid flow, and effective prediction of fracture network permeability is the basis for further accurate assessment of oil and gas productivity. On the basis of the traditional parallel-plate cube law, we introduce the tortuosity fractal dimension DTf to characterize the tortuosity of fractures. Then, combined with fractal theory, a permeability model is derived for a complex tortuous discrete fracture network (DFN). A pixel probability decomposition algorithm is used to generate ten random DFNs that conform to the fractal scale relationship, and the effectiveness of the proposed model is verified by numerical simulation. The fracture geometry parameters are further analyzed and their effect on permeability discussed. The results show that the permeability K of a fracture network increases with an increase in porosity ϕ (0.117–0.292), fractal dimension Df (1.635–1.824), maximum fracture length lmax (3.337–7.472 m), and proportionality coefficient β (0.00108–0.0164), but decreases with the increasing tortuosity fractal dimension DTf (1.0018–1.0196) and fracture dip angle θ (10°–80°). Among these parameters, Df, DTf, and β have the greatest influence on the permeability of the fracture network, followed by θ, lmax, and ϕ. [ABSTRACT FROM AUTHOR]