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Micro-CT-Based Pore Network Characterization and Microscopic Permeability Prediction Modeling for Deep Low-Rank Coal in the Tiefa Basin
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DOI：10.3390/fractalfract10080532.png)
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Abstract
En 中文
Deep low-rank coal from the Daqiang Mine in the Tiefa Basin was investigated using micro-CT imaging with a voxel size of 1 μm. The CT-resolved connected macropore structures of 12 representative elementary volumes (REVs) were reconstructed, and corresponding equivalent pore network models were established. Steady-state, isothermal, single-phase continuum methane flow was simulated under prescribed inlet and outlet pressures with no-flow lateral boundaries, which primarily represent the flow capacity of CT-resolved connected macropores under unstressed conditions. The results showed that: (1) the S1 group exhibited a relatively compact pore structure, smaller throats, stronger spatial heterogeneity, and poorer connectivity, whereas the S2 and S3 groups contained better-developed and more highly connected pore–throat networks; (2) the simulated mean absolute permeabilities of the S1, S2, and S3 groups were 0.781, 0.969, and 0.910 mD, respectively. These values were generally close to, but slightly higher than, the experimental measurements, mainly because the digital models retained only CT-resolved connected pores and did not account for stress-induced compression or the flow-limiting effects of unresolved fine throats; (3) permeability was positively correlated with pore radius, throat radius, and coordination number, but negatively correlated with throat length, pore-to-throat ratio, tortuosity, and fractal dimension. Among these parameters, throat radius showed the strongest correlation with permeability; and (4) an empirical regression model was further established: K = − 4.809 + 0.672 r t + 3.950 τ . The model exhibited a high goodness of fit ( R 2 = 0.952 , p < 0.001 ); however, its applicability is limited to the investigated coal samples from the Daqiang Mine. Overall, effective throat size and pore–throat connectivity provide more direct indicators of gas-transport capacity than total porosity alone, offering a pore-scale basis for identifying favorable CBM flow zones and optimizing reservoir stimulation strategies in the study area.
Keywords:
deep coal
pore structure
seepage simulation
permeability prediction model
micro-CT technology
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