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research-article

A new method of porous space reconstruction using multipoint histogram technology

[+] Author and Article Information
Na Zhang

Petroleum Engineering, Texas A&M University at Qatar, Education City, PO Box 23874, Doha, Qatar
na.zhang@qatar.tamu.edu

Qian Sun

Petroleum Engineering, Texas A&M University at Qatar, Education City, PO Box 23874, Doha, Qatar
qian.sun@qatar.tamu.edu

Mohamed Fadlelmula

Petroleum Engineering, Texas A&M University at Qatar, Education City, PO Box 23874, Doha, Qatar
mohamed.fadlelmula@qatar.tamu.edu

Aziz Rahman

Petroleum Engineering, Texas A&M University at Qatar, Education City, PO Box 23874, Doha, Qatar
marahman@tamu.edu

Yuhe Wang

Petroleum Engineering, Texas A&M University at Qatar, Education City, PO Box 23874, Doha, Qatar
yuhe.wang@qatar.tamu.edu

1Corresponding author.

ASME doi:10.1115/1.4038379 History: Received January 30, 2017; Revised October 31, 2017

Abstract

Pore-scale modeling is becoming a hot topic in overall reservoir characterization process. In this paper, a new reconstruction method is proposed to reproduce the characteristics of a 2D thin section based on the multipoint histogram by using a unit configuration. Firstly, the two-point correlation coefficient matrix will be introduced to determine an optimal unit configuration of a multipoint histogram. Secondly, five different types of 7-point unit configurations will be used to test the unit configuration selection algorithm. Thirdly, the multipoint histogram technology is used for generating the porous space reconstruction based on the prior unit configuration with a different calculation of the objective function. Finally, the spatial connectivity, patterns reproduction, the local percolation theory and hydraulic connectivity are used to compare with those of the reference model. The results show that the multipoint histogram technology can produce better multipoint connectivity information than SAM. The reconstructed system matches the training image very well, which reveals that the reconstruction captures the geometry and topology information of the training image, for instance, the shape and distribution of pore space. The 7-point unit configuration is enough to get the spatial characters of the training image. The quality of pattern reproduction of the reconstruction is assessed by computing the multipoint histogram, and the similarity is around 97.3%. Applying the local percolation theory analysis, the multipoint histogram can describe the anticipated patterns of geological heterogeneities and reproduce the connectivity of pore media with a high degree.

Copyright (c) 2017 by ASME
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