Porous media flux sensitivity to pore-scale geostatistics: A bottom-up approach

被引:11
作者
Di Palma, P. R. [1 ]
Guyennon, N. [1 ]
Hesse, F. [2 ]
Romano, E. [1 ]
机构
[1] IRSA, CNR, Water Res Inst, Natl Res Council, Via Solaria km 29 300, Monterotondo, Italy
[2] UFZ Helmholtz Ctr Environm Res, Dept Computat Hydrosystems, Permoserstr 15, D-04318 Leipzig, Germany
关键词
Pore-scale geostatistics; Porous media generation; Lattice Boltzmann method; Pore-scale flow simulation; Seepage velocity; Matern covariance model; LATTICE BOLTZMANN METHOD; HYDRAULIC CONDUCTIVITY; TRANSPORT-PROPERTIES; FLOW; MODELS; PERMEABILITY; RECONSTRUCTION; DISSOLUTION; SIMULATION; DISPERSION;
D O I
10.1016/j.advwatres.2017.02.002
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Macroscopic properties of flow through porous media can be directly computed by solving the Navier-Stokes equations at the scales related to the actual flow processes, while considering the porous structures in an explicit way. The aim of this paper is to investigate the effects of the pore-scale spatial distribution on seepage velocity through numerical simulations of 3D fluid flow performed by the lattice Boltzmann method. To this end, we generate multiple random Gaussian fields whose spatial correlation follows an assigned semi-variogram function. The Exponential and Gaussian semi-variograms are chosen as extreme-cases of correlation for short distances and statistical properties of the resulting porous media (indicator field) are described using the Matern covariance model, with characteristic lengths of spatial autocorrelation (pore size) varying from 2% to 13% of the linear domain. To consider the sensitivity of the modeling results to the geostatistical representativeness of the domain as well as to the adopted resolution, porous media have been generated repetitively with re-initialized random seeds and three different resolutions have been tested for each resulting realization. The main difference among results is observed between the two adopted semi-variograms, indicating that the roughness (short distances autocorrelation) is the property mainly affecting the flux. However, computed seepage velocities show additionally a wide variability (about three orders of magnitude) for each semi-variogram model in relation to the assigned correlation length, corresponding to pore sizes. The spatial resolution affects more the results for short correlation lengths (i.e., small pore sizes), resulting in an increasing underestimation of the seepage velocity with the decreasing correlation length. On the other hand, results show an increasing uncertainty as the correlation length approaches the domain size. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:99 / 110
页数:12
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