Computational Permeability Determination from Pore-Scale Imaging: Sample Size, Mesh and Method Sensitivities
Computational Permeability Determination from Pore-Scale Imaging: Sample Size, Mesh and Method Sensitivities
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DOI：
10.1007/s11242-015-0458-0
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发表时间：
2015-04-01
影响因子：
2.7
通讯作者：
Debenest, G.
中科院分区：
文献类型：
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作者：
Guibert, R.;Nazarova, M.;Debenest, G.
在这项工作中，一个完整的工作流程，从孔隙尺度成像的绝对渗透率测定的描述和讨论。解决了两个具体问题，涉及（1）固定图像分辨率的网格细化和（2）所用确定方法的影响。这种方法的一个关键点是要在足够大的样本上工作，以检查所获得的评估的代表性，这需要有效的并行能力。图像采集和处理使用商业显微断层摄影机实现。然后使用在开源平台OpenFOAM（A（R））中实现的有限体积法来评估孔隙尺度流动。对于这种数值方法，上述不同方面的影响进行了研究。此外，还测试和讨论了并行效率。我们观察到网格细化的水平对渗透率张量有不可忽略的影响。此外，提高细化水平往往会减少计算测量方法之间的差距。网格计算时间的增加与平台的良好并行效率相平衡。
In this work, a complete work flow from pore-scale imaging to absolute permeability determination is described and discussed. Two specific points are tackled, concerning (1) the mesh refinement for a fixed image resolution and (2) the impact of the determination method used. A key point for this kind of approach is to work on enough large samples to check the representativity of the obtained evaluations, which requires efficient parallel capabilities. Image acquisition and processing are realized using a commercial micro-tomograph. The pore-scale flows are then evaluated using the finite volume method implemented in the open-source platform OpenFOAM(A (R)). For this numerical method, the influence of the different aspects mentioned above are studied. Moreover, the parallel efficiency is also tested and discussed. We observe that the level of mesh refinement has a non-negligible impact on permeability tensor. Moreover, increasing the refinement level tends to reduce the gap between the methods of computational measurements. The increase in computation time with the mesh is balanced with the good parallel efficiency of the platform.