Statistical Inference Over Persistent Homology Predicts Fluid Flow in Porous Media

Moon, Chul; Mitchell, Scott A.; Heath, Jason E.; Andrew, Matthew

doi:10.1029/2019wr025171

Statistical Inference Over Persistent Homology Predicts Fluid Flow in Porous Media

Journal Article · Sun Oct 06 00:00:00 EDT 2019 · Water Resources Research

DOI:https://doi.org/10.1029/2019wr025171· OSTI ID:1667397

^[1]; Mitchell, Scott A. ^[2]; Heath, Jason E. ^[2]; Andrew, Matthew ^[3]

Southern Methodist Univ., Dallas, TX (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Carl Zeiss X‐ray Microscopy Inc., Dublin ,CA (United States)

Here, we statistically infer fluid flow and transport properties of porous materials based on their geometry and connectivity, without the need for detailed We summarize structure by persistent homology and then determines the similarity of structures using image analysis and statistics. Longer term, this may enable quick and automated categorization of rocks into known archetypes. We first compute persistent homology of binarized 3D images of material subvolume samples. The persistence parameter is the signed Euclidean distance from inferred material interfaces, which captures the distribution of sizes of pores and grains. Each persistence diagram is converted into an image vector. Here, we infer structural similarity by calculating image similarity. For each image vector, we compute principal components to extract features. We fit statistical models to features estimates material permeability, tortuosity, and anisotropy. We develop a Structural SIMilarity index to determine statistical representative elementary volumes.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF)

Grant/Contract Number:: AC04-94AL85000; SC0014664; SC0006883

OSTI ID:: 1667397

Report Number(s):: SAND--2020-8596J; 690046

Journal Information:: Water Resources Research, Journal Name: Water Resources Research Journal Issue: 11 Vol. 55; ISSN 0043-1397

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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