Permeability is a key parameter affecting the transport process of fluid through a porous media. In this paper, the random generation method was used to generate some 2D geometric models of pore structure with different structural characteristics. A mathematical flow model based on the Lattice Boltzmann Method (LBM) was established to study the transport of fluid process through these pore structure models. Before simulation, this model was tested by the Poiseuille flow, and a good agreement was achieved by compared with analytical solutions. The detailed distribution of velocity in complex pore space was obtained and presented visually. Furthermore, the Darcy's law was used to calculate the permeability of these porous media models based on the results of LBM simulation. Then, we investigated the effects of porosity, pore shape (skeleton shape), skeleton particle size and pore randomness on permeability. Results show that the increase in the porosity or the pore size will lead to an increase in the permeability, in addition, pore randomness and pore shape also have an effect on permeability. The numerical method established in this work provides a promising approach to study pore-scale flow in porous media.

1. INTRODUCTION

The fluid flow and transport in porous media is a hot research topic, which widely exists in many engineering fields, such as petroleum engineering, soil science, groundwater engineering, carbon dioxide sequestration and so on (Dai et al., 2014; Doyon and Molson, 2012; Kang et al., 2010; Telmadarreie et al., 2016). Permeability, which is a macroscopic characteristic parameter of porous media, has a great influence on fluid transport in pore, so the study for permeability of porous media is helpful to understand the process of fluid flow process in porous media. Previous studies have shown that permeability has nothing to do with the fluid properties in the pores, but the pore structure characteristic parameters of porous media have great influence on permeability, such as porosity, pore shape, skeleton particle size, skeleton particle distribution characteristics, etc (Carman, 1939; Jeong, 2010; Pape et al., 2000; Rumpf and Gupte, 1971).

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