Permeability prediction of organic shale with generalized lattice Boltzmann model considering surface diffusion effect
Junjian Wang, Li Chen, Qinjun Kang, Sheik S Rahman

TL;DR
This study develops a generalized lattice Boltzmann model to predict gas permeability in organic shale, considering surface diffusion and multiple transport mechanisms, providing insights into how organic content and pore size influence permeability.
Contribution
The paper introduces a comprehensive modeling approach combining GLBM, EM algorithm, DGM, and GMS to accurately predict shale permeability considering surface diffusion effects.
Findings
Surface diffusion significantly affects apparent permeability.
Total organic content influences gas transport.
Pore size distribution has minimal impact on permeability.
Abstract
Gas flow in shale is associated with both organic matter (OM) and inorganic matter (IOM) which contain nanopores ranging in size from a few to hundreds of nanometers. In addition to the noncontinuum effect which leads to an apparent permeability of gas higher than the intrinsic permeability, the surface diffusion of adsorbed gas in organic pores also can influence the apparent permeability through its own transport mechanism. In this study, a generalized lattice Boltzmann model (GLBM) is employed for gas flow through the reconstructed shale matrix consisting of OM and IOM. The Expectation-Maximization (EM) algorithm is used to assign the pore size distribution to each component, and the dusty gas model (DGM) and generalized Maxwell-Stefan model (GMS) are adopted to calculate the apparent permeability accounting for multiple transport mechanisms including viscous flow, Knudsen diffusion…
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