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Stochastic Modeling of the Permeability of Randomly Generated Porous Media

机译:随机生成多孔介质渗透率的随机模拟

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摘要

Permeability of porous media in subsurface environments is subject to potentially large uncertainties due to the heterogeneity of natural systems. In this study, a first-order reliability method (FORM) is combined with a lattice Boltzmann method (LBM) to estimate the permeability of randomly generated porous media. The proposed procedure provides an increased ease of addressing complex pore structures by employing LBM to model fluid flow, while inheriting the computational efficiency from FORM. Macroscale- equivalent permeability can thus be estimated with significantly reduced computational efforts, while maintaining a connection to the complex microscale fluid dynamics within a pore structure environment. Implemented on several randomly generated porous media domains, the proposed method provides 13–120 times the efficiency compared to Monte Carlo methods.
机译:由于自然系统的异质性,地下环境中多孔介质的渗透性可能存在很大的不确定性。在这项研究中,一阶可靠性方法(FORM)与晶格玻尔兹曼方法(LBM)相结合,以估计随机产生的多孔介质的渗透率。拟议的程序通过使用LBM建模流体流,同时继承了FORM的计算效率,提供了解决复杂孔结构的更高的简便性。因此,在维持与孔隙结构环境内复杂的微观尺度流体动力学的联系的同时,可以用显着减少的计算量来估计宏观尺度等效渗透率。该方法在几个随机生成的多孔介质域上实施,与蒙特卡洛方法相比,其效率提高了13–120倍。

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