In this paper, we address the expensive computational cost resulting from limited time-step sizes during numerical simulations of two-phase flow in porous media using dynamic pore-network models. To overcome this issue, we propose a numerical method for dynamic pore-network models using a fully implicit approach. The proposed method introduces a regularization strategy considering the historical fluid configuration at the pore throat, which smooths the discontinuities in local conductivity caused by invasion and snap-off events. The results demonstrate the superiority of the proposed method in terms of accuracy, efficiency and consistency in comparison with other numerical schemes. With similar computational cost, determined by time-step sizes and number of Newton iterations, the developed method in this work yields more accurate results compared to similar schemes presented in the literature. Additionally, our results highlight the enhanced robustness of the our scheme, as it exhibits reduced sensitivity to variations in time-step sizes.
%0 Journal Article
%1 Wu2023
%A Wu, Hanchuan
%A Veyskarami, Maziar
%A Schneider, Martin
%A Helmig, Rainer
%D 2023
%J Transport in Porous Media
%K dumuxarticle
%R 10.1007/s11242-023-02031-2
%T A New Fully Implicit Two-Phase Pore-Network Model by Utilizing Regularization Strategies
%U https://doi.org/10.1007/s11242-023-02031-2
%X In this paper, we address the expensive computational cost resulting from limited time-step sizes during numerical simulations of two-phase flow in porous media using dynamic pore-network models. To overcome this issue, we propose a numerical method for dynamic pore-network models using a fully implicit approach. The proposed method introduces a regularization strategy considering the historical fluid configuration at the pore throat, which smooths the discontinuities in local conductivity caused by invasion and snap-off events. The results demonstrate the superiority of the proposed method in terms of accuracy, efficiency and consistency in comparison with other numerical schemes. With similar computational cost, determined by time-step sizes and number of Newton iterations, the developed method in this work yields more accurate results compared to similar schemes presented in the literature. Additionally, our results highlight the enhanced robustness of the our scheme, as it exhibits reduced sensitivity to variations in time-step sizes.
@article{Wu2023,
abstract = {In this paper, we address the expensive computational cost resulting from limited time-step sizes during numerical simulations of two-phase flow in porous media using dynamic pore-network models. To overcome this issue, we propose a numerical method for dynamic pore-network models using a fully implicit approach. The proposed method introduces a regularization strategy considering the historical fluid configuration at the pore throat, which smooths the discontinuities in local conductivity caused by invasion and snap-off events. The results demonstrate the superiority of the proposed method in terms of accuracy, efficiency and consistency in comparison with other numerical schemes. With similar computational cost, determined by time-step sizes and number of Newton iterations, the developed method in this work yields more accurate results compared to similar schemes presented in the literature. Additionally, our results highlight the enhanced robustness of the our scheme, as it exhibits reduced sensitivity to variations in time-step sizes.},
added-at = {2023-11-20T13:26:40.000+0100},
author = {Wu, Hanchuan and Veyskarami, Maziar and Schneider, Martin and Helmig, Rainer},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/292647e00653fd337fd28679378258133/berndflemisch},
doi = {10.1007/s11242-023-02031-2},
interhash = {2644ae1e1fd50fdee56d1333999c40eb},
intrahash = {92647e00653fd337fd28679378258133},
issn = {1573-1634},
journal = {Transport in Porous Media},
keywords = {dumuxarticle},
timestamp = {2023-11-20T13:26:40.000+0100},
title = {A New Fully Implicit Two-Phase Pore-Network Model by Utilizing Regularization Strategies},
url = {https://doi.org/10.1007/s11242-023-02031-2},
year = 2023
}
