基于流体体积法的矿物沉淀模型

IF 2.1 3区 地球科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Ziyan Wang, Ilenia Battiato
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引用次数: 0

摘要

针对矿物沉淀与流体流动和反应传输的耦合,提出了一种新颖的流体体积法。该方法将流固界面描述为一个光滑的过渡区域,旨在提供与尖锐界面相同的析出率和粘性阻力。具体来说,矿物析出的控制方程采用上风方案离散化,并在界面周围推导出严格的有效粘度模型。该模型与通道和环形结构中矿物析出的分析解进行了验证。该模型还与平流-扩散-反应问题的界面跟踪模拟结果进行了比较。该方法最后被用于模拟断裂网络中的矿物沉淀,由于断裂网络孔隙率低、几何形状复杂,因此具有挑战性。与其他方法相比,所提出的模型算法简洁,不包含自由参数。在建模过程中,只需要对孔隙空间进行网格划分,从而提高了计算效率,特别是对于低孔隙率介质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A mineral precipitation model based on the volume of fluid method

A novel volume of fluid method is presented for mineral precipitation coupled with fluid flow and reactive transport. The approach describes the fluid-solid interface as a smooth transitional region, which is designed to provide the same precipitation rate and viscous drag force as a sharp interface. Specifically, the governing equation of mineral precipitation is discretized by an upwind scheme, and a rigorous effective viscosity model is derived around the interface. The model is validated against analytical solutions for mineral precipitation in channel and ring-shaped structures. It also compares well with interface tracking simulations of advection-diffusion-reaction problems. The methodology is finally employed to model mineral precipitation in fracture networks, which is challenging due to the low porosity and complex geometry. Compared to other approaches, the proposed model has a concise algorithm and contains no free parameters. In the modeling, only the pore space requires meshing, which improves the computational efficiency especially for low-porosity media.

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来源期刊
Computational Geosciences
Computational Geosciences 地学-地球科学综合
CiteScore
6.10
自引率
4.00%
发文量
63
审稿时长
6-12 weeks
期刊介绍: Computational Geosciences publishes high quality papers on mathematical modeling, simulation, numerical analysis, and other computational aspects of the geosciences. In particular the journal is focused on advanced numerical methods for the simulation of subsurface flow and transport, and associated aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing. Papers treating similar topics but with applications to other fields in the geosciences, such as geomechanics, geophysics, oceanography, or meteorology, will also be considered. The journal provides a platform for interaction and multidisciplinary collaboration among diverse scientific groups, from both academia and industry, which share an interest in developing mathematical models and efficient algorithms for solving them, such as mathematicians, engineers, chemists, physicists, and geoscientists.
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