Imperial College London
Alternate

ProfessorPeterKing

Faculty of Engineering, Department of Earth Science & Engineering

Chair in Porous Media Physics
 
 
 
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Contact

 

+44 (0)20 7594 7362peter.king

 
 
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Location

 

1.40Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Masihi:2022:10.1016/j.petrol.2022.110113,
author = {Masihi, M and Shams, R and King, PR},
doi = {10.1016/j.petrol.2022.110113},
journal = {Journal of Petroleum Science and Engineering},
pages = {110113--110113},
title = {Pore level characterization of Micro-CT images using percolation theory},
url = {http://dx.doi.org/10.1016/j.petrol.2022.110113},
volume = {211},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Flow through porous media depends strongly on the spatial distribution of the geological heterogeneities which appear on all length scales. We lack precise information about heterogeneity distribution on various scales, from pore level to reservoir scale. However, some sources provide suitable information. At pore scale, for example, the micro-CT images show considerable insights into pore space structures and play valuable role in porous media characterization. The consequence of all geological heterogeneities is a great deal of uncertainty in dynamic performance of porous media which can be investigated using percolation theory. The main percolation quantities include the connected pore fraction; , the backbone fraction; , the dangling ends fraction; , and the effective permeability; . By finite size scaling within percolation theory, these quantities (i.e. ) become some functions of total pore fraction; , and the system dimensionless length; . In this work we examine the functional forms of percolation quantities on two-dimensional micro-CT images and develop new correlations for such quantities in three-dimensions. The results show good agreement on micro-CT samples with different pore size distribution and wide level of connectivity.
AU  - Masihi,M
AU  - Shams,R
AU  - King,PR
DO  - 10.1016/j.petrol.2022.110113
EP  - 110113
PY  - 2022///
SN  - 0920-4105
SP  - 110113
TI  - Pore level characterization of Micro-CT images using percolation theory
T2  - Journal of Petroleum Science and Engineering
UR  - http://dx.doi.org/10.1016/j.petrol.2022.110113
UR  - https://www.sciencedirect.com/science/article/pii/S0920410522000109?via%3Dihub
UR  - http://hdl.handle.net/10044/1/94266
VL  - 211
ER  -
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