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Current Minireview | Open Access

Pore-scale fluid flow simulation coupling lattice Boltzmann method and pore network model

College of Petroleum Engineering, China University of Petroleum, Beijing 102249, P. R. China
College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang 464000, P. R. China
Institute of Extreme Mechanics and School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, P. R. China
Department of Mechanical and Process Engineering, ETH Zürich, Zürich 8092, Switzerland
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Abstract

The lattice Boltzmann method and pore network model are two types of the most popular pore-scale fluid flow simulation methods. As a direct numerical simulation method, lattice Boltzmann method simulates fluid flow directly in the realistic porous structures, characterized by high computational accuracy but low efficiency. On the contrary, pore network model simulates fluid flow in simplified regular pore networks of the real porous media, which is more computationally efficient, but fails to capture the detailed pore structures and flow processes. In past few years, significant efforts have been devoted to couple lattice Boltzmann method and pore network model to simulate fluid flow in porous media, aiming to combine the accuracy of lattice Boltzmann method and efficiency of pore network model. In this mini-review, the recent advances in pore-scale fluid flow simulation methods coupling lattice Boltzmann method and pore network model are summarized, in terms of single-phase flow, quasi-static two-phase drainage flow and dynamic two-phase flow in porous media, demonstrating that coupling the lattice Boltzmann method and pore network model offers a promising and effective approach for addressing the up-scaling problem of flow in porous media.

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Capillarity
Pages 41-46
Cite this article:
Zhao J, Liu Y, Qin F, et al. Pore-scale fluid flow simulation coupling lattice Boltzmann method and pore network model. Capillarity, 2023, 7(3): 41-46. https://doi.org/10.46690/capi.2023.06.01

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Received: 16 April 2023
Revised: 05 May 2023
Accepted: 20 May 2023
Published: 23 May 2023
© The Author(s) 2023.

This article is distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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