Quantifying fracture geometry with X-ray tomography: Technique of Iterative Local Thresholding (TILT) for 3D image segmentation

Deng, Hang; Fitts, Jeffrey P.; Peters, Catherine A.

doi:10.1007/s10596-016-9560-9

Title: Quantifying fracture geometry with X-ray tomography: Technique of Iterative Local Thresholding (TILT) for 3D image segmentation

Journal Article · Mon Feb 01 00:00:00 EST 2016 · Computational Geosciences

DOI:https://doi.org/10.1007/s10596-016-9560-9· OSTI ID:1503055

Deng, Hang; Fitts, Jeffrey P.; Peters, Catherine A.

This paper presents a new method—the Technique of Iterative Local Thresholding (TILT)—for processing 3D X-ray computed tomography (xCT) images for visualization and quantification of rock fractures. The TILT method includes the following advancements. First, custom masks are generated by a fracture-dilation procedure, which significantly amplifies the fracture signal on the intensity histogram used for local thresholding. Second, TILT is particularly well suited for fracture characterization in granular rocks because the multi-scale Hessian fracture (MHF) filter has been incorporated to distinguish fractures from pores in the rock matrix. Third, TILT wraps the thresholding and fracture isolation steps in an optimized iterative routine for binary segmentation, minimizing human intervention and enabling automated processing of large 3D datasets. As an illustrative example, we applied TILT to 3D xCT images of reacted and unreacted fractured limestone cores. Other segmentation methods were also applied to provide insights regarding variability in image processing. The results show that TILT significantly enhanced separability of grayscale intensities, outperformed the other methods in automation, and was successful in isolating fractures from the porous rock matrix. Because the other methods are more likely to misclassify fracture edges as void and/or have limited capacity in distinguishing fractures from pores, those methods estimated larger fracture volumes (up to 80 %), surface areas (up to 60 %), and roughness (up to a factor of 2). In conclusion, these differences in fracture geometry would lead to significant disparities in hydraulic permeability predictions, as determined by 2D flow simulations.

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Research Organization:: Pennsylvania State Univ., University Park, PA (United States)

Sponsoring Organization:: USDOE Office of Fossil Energy and Carbon Management (FECM); USDOE Office of Fossil Energy (FE)

Grant/Contract Number:: FE0023354

OSTI ID:: 1503055

Alternate ID(s):: OSTI ID: 1438833

Journal Information:: Computational Geosciences, Journal Name: Computational Geosciences Vol. 20 Journal Issue: 1; ISSN 1420-0597

Publisher:: Springer Science + Business MediaCopyright Statement

Country of Publication:: Netherlands

Language:: English

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Cited by: 48 works

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