Incomplete mixing in porous media: Todd-Longstaff upscaling approach versus a dynamic local grid refinement method
Incomplete mixing in porous media: Todd-Longstaff upscaling approach versus a dynamic local grid refinement method
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多孔介质中的不完全混合：Todd-Longstaff 放大方法与动态局部网格细化方法
DOI：
10.1007/s10596-018-9802-0
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发表时间：
2018
影响因子：
2.5
通讯作者：
H. Hajibeygi
中科院分区：
文献类型：
--
作者：
M. Cusini;Robin Gielisse;H. Groot;C. van Kruijsdijk;H. Hajibeygi
在不完全混合的情况下，多孔介质中流动的场尺度模拟需要高分辨率的计算网格，这远远超出了最先进的模拟器的范围。因此，通常使用基于放大的托德和朗斯塔夫（TL）方法，其中采用粗网格单元，并通过匹配与完全解析的参考模拟获得的结果来找到有效的混合流体特性和参数。动态局部网格加密（DLGR）技术，另一方面，只采用细尺度网格分辨率的完全混合的假设是无效的。然后以较粗的分辨率求解域的其余部分，其中完全混合的假设是有效的。在这里，我们评估的准确性和鲁棒性DLGR和TL为基础的模拟混溶位移均匀和非均匀多孔介质。由于内在的不稳定位移性质的研究不完全混合过程的不确定性，该方法的性能也进行了研究的基础上的一系列可接受的解决方案，而不是只依赖于一个单一的参考。系统的数值结果表明，DLGR方法是更强大的和更准确的比升尺度的TL方法，只需要一小部分的细尺度参考网格。特别是，TL放大的结果（虽然历史匹配计算昂贵的精细尺度的结果）是非常敏感的模拟参数的变化。在此基础上，我们提出了一种动态多级模拟策略，用于复杂不完全混合过程的高效、可靠的大规模模拟。
Field-scale simulation of flow in porous media in presence of incomplete mixing demands for high-resolution computational grids, much beyond the scope of state-of-the-art simulators. Hence, the upscaling-based Todd and Longstaff (TL) approach is typically used, where coarse grid cells are employed with effective mixing fluid properties and parameters found by matching results obtained with fully resolved reference simulations. Dynamic local grid refinement (DLGR) techniques, on the other hand, only employ fine-scale grid resolution where the fully mixed assumption is not valid. The rest of the domain is then solved at coarser resolutions, where the fully mixed assumption is valid. Here, we assess the accuracy and the robustness of DLGR- and TL-based simulations of miscible displacements in homogeneous and heterogeneous porous media. Due to the intrinsic uncertainty within the unstable displacement nature of the studied incomplete mixing processes, the performance of the methods is also investigated based on a range of acceptable solutions rather than relying only on a single reference one. Systematic numerical results illustrate that the DLGR method is much more robust and accurate than the upscaling-based TL approach, and employs only a small fraction of fine-scale reference grids. Especially, the TL upscaling results (though history matched with computationally expensive fine-scale results) are very sensitive to the change of the simulation parameters. Based on this study, we propose a dynamic multilevel simulation strategy for efficient and reliable large-scale simulation of the complex incomplete mixing processes.
使用 MPFA 方法进行自适应网格细化的高效多物理场建模
影响因子：
2.5
作者：
Faigle;Helmig;Aavatsmark;Flemisch
通讯作者：
Flemisch