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A reconstruction method for three‐dimensional pore space using multiple‐point geology statistic based on statistical pattern recognition and microstructure characterization
Authors:Zhi Xu  Qizhi Teng  Xiaohai He  Zhengji Li
Institution:School of Electronics and Information Engineering, Sichuan University, , Chengdu, China
Abstract:To predict the macroscopic properties (e.g., transport, electromagnetic, and mechanical properties) of porous media, it is necessary to have a three‐dimensional (3D) representation of porous media. We reconstruct the geologically realistic 3D structure of Fontainebleau sandstone based on the two‐dimensional (2D) thin sections by using the multiple‐point statistics method. For this method, the size of template is an important parameter that reflects the perceived scale of spatial structure of porous media. In this paper, we take advantage of entropy method to obtain the appropriate size of the template, which is proven to be correct and feasible. The reconstruction method proposed by us combines successive 2D MPS simulations as well as 3D MPS simulation, which takes account into the pore structure information (e.g., heterogeneity and connectivity) both intralayer and interlayer. This reconstruction method is tested on Fontainebleau sandstone for which 3D images from micro‐CT scanning are available. Applying local percolation theory analysis, this new approach can depict the expected patterns of geological heterogeneities. In addition, it also can well reproduce a high degree of connectivity of the pore space better than other reconstruction methods based on lower‐order statistics. Copyright © 2011 John Wiley & Sons, Ltd.
Keywords:porous media  3D reconstruction  training image  template select algorithm  MPS  local percolation theory
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