A multiple-point statistics algorithm for 3D pore space reconstruction from 2D images

被引:150
作者
Hajizadeh, Alireza [1 ]
Safekordi, Aliakbar [1 ]
Farhadpour, Farhad A. [1 ]
机构
[1] Sharif Univ Technol, Dept Chem & Petr Engn, Tehran, Iran
关键词
Porous media reconstruction; Multiple-point statistics; Micro-CT imaging; Two-phase flow; POROUS-MEDIA; MICROTOMOGRAPHY; SIMULATION;
D O I
10.1016/j.advwatres.2011.06.003
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Fluid flow behavior in a porous medium is a function of the geometry and topology of its pore space. The construction of a three dimensional pore space model of a porous medium is therefore an important first step in characterizing the medium and predicting its flow properties. A stochastic technique for reconstruction of the 3D pore structure of unstructured random porous media from a 2D thin section training image is presented. The proposed technique relies on successive 2D multiple point statistics simulations coupled to a multi-scale conditioning data extraction procedure. The Single Normal Equation Simulation Algorithm (SNESIM), originally developed as a tool for reproduction of long-range, curvilinear features of geological structures, serves as the simulation engine. Various validating criteria such as marginal distributions of pore and grain, directional variograms, multiple-point connectivity curves, single phase effective permeability and two phase relative permeability calculations are used to analyze the results. The method is tested on a sample of Berea sandstone for which a 3D micro-CT scanning image is available. The results confirm that the equi-probable 3D realizations obtained preserve the typical patterns of the pore space that exist in thin sections, reproduce the long-range connectivities, capture the characteristics of anisotropy in both horizontal and vertical directions and have single and two phase flow characteristics consistent with those of the measured 3D micro-CT image. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1256 / 1267
页数:12
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