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TitlePore characterization of organic-rich shales through application of topological data analysis and persistent homology
AuthorBizhani, MORCID logo; Ardakani, O HORCID logo
SourceEnergy & Fuels vol. 35, 2021 p. 18563-18573,
Alt SeriesNatural Resources Canada, Contribution Series 20210352
PublisherAmerican Chemical Society
Mediapaper; digital; on-line
File formatpdf
SubjectsScience and Technology; sedimentology; pore size; shales; sandstones
Illustrationstables; 3-D images; distribution diagrams; plots
ProgramEnergy Geoscience Clean Energy Resources - Decreasing Environmental Risk
Released2021 11 08
AbstractThis paper discusses pore characterization of organic-rich using 3D high-resolution imaging and topological data analysis (TDA) framework. In particular, our focus is on persistent homology. Our dataset contains four organic-rich shale samples (imaged at 10 nm3/voxel) and a Bentheimer sandstone as the anchor point for comparison. The analysis shows pores larger than 12.4nm have poor connectivity, and there is no evidence of percolating path through any of the shale samples. In contrast, the Bentheimer sandstone shows remarkable differences from the shales in terms of pore connectivity. In terms of geometry, pores and grains in shale are shown to be highly non-convex, while sandstone exhibits a more uniform and convex distribution of pore and grain size. Euler characteristics of the samples are also computed and discussed along with the pore network extracted on the segmented images. The results show all three methods have an agreement in the overall description of the pore space. However, persistent homology data reveals more information on the pore and grain phase as compared to the other methods. In the last section of the paper, we present an investigation of topological changes in the pore space as a function of pore radius. The analysis indicates most pores must be enlarged by approximately equal to 70-80nm for the pore space to span into a connected network. The implication is that flow mainly occurs through independent channels in shales, as opposed to sandstone where many redundant flow pathways exist.
Summary(Plain Language Summary, not published)
The use of high-resolution microscopic images is a common method for the characterization of internal micro-structures of various rock types. We apply a mathematical framework (topological data analysis method) to decode various aspects of pore and grain geometry and morphology of several shale samples. The topological approach demonstrates a superior capability compared to traditional methods in revealing low-level features of the internal structures of the rocks. Additionally, the analysis helps better understanding the fluid flow mechanism in organic-rich shales.

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