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Effect of image scaling and segmentation in digital rock characterisation

B. D. Jones, Y. T. Feng, Yuntian Feng Orcid Logo

Computational Particle Mechanics, Volume: 3, Issue: 2, Pages: 201 - 213

Swansea University Author: Yuntian Feng Orcid Logo

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DOI (Published version): 10.1007/s40571-015-0077-0

Abstract

Digital material characterisation from microstructural geometry is an emerging field in computer simulation. For permeability characterisation, a variety of studies exist where the lattice Boltzmann method (LBM) has been used in conjunction with computed tomography (CT) imaging to simulate fluid flo...

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Published in: Computational Particle Mechanics
ISSN: 2196-4378 2196-4386
Published: 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa25671
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first_indexed 2016-01-16T01:56:07Z
last_indexed 2018-02-09T05:06:48Z
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spelling 2017-06-30T15:16:19.1322560 v2 25671 2016-01-15 Effect of image scaling and segmentation in digital rock characterisation d66794f9c1357969a5badf654f960275 0000-0002-6396-8698 Yuntian Feng Yuntian Feng true false 2016-01-15 CIVL Digital material characterisation from microstructural geometry is an emerging field in computer simulation. For permeability characterisation, a variety of studies exist where the lattice Boltzmann method (LBM) has been used in conjunction with computed tomography (CT) imaging to simulate fluid flow through microscopic rock pores. While these previous works show that the technique is applicable, the use of binary image segmentation and the bounceback boundary condition results in a loss of grain surface definition when the modelled geometry is compared to the original CT image. We apply the immersed moving boundary (IMB) condition of Noble and Torczynski as a partial bounceback boundary condition which may be used to better represent the geometric definition provided by a CT image. The IMB condition is validated against published work on idealised porous geometries in both 2D and 3D. Following this, greyscale image segmentation is applied to a CT image of Diemelstadt sandstone. By varying the mapping of CT voxel densities to lattice sites, it is shown that binary image segmentation may underestimate the true permeability of the sample. A CUDA-C-based code, LBM-C, was developed specifically for this work and leverages GPU hardware in order to carry out computations. Journal Article Computational Particle Mechanics 3 2 201 213 2196-4378 2196-4386 Lattice Boltzmann, CT imaging, Permeability, GPU computing 30 4 2016 2016-04-30 10.1007/s40571-015-0077-0 COLLEGE NANME Civil Engineering COLLEGE CODE CIVL Swansea University 2017-06-30T15:16:19.1322560 2016-01-15T20:47:46.1233904 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering B. D. Jones 1 Y. T. Feng 2 Yuntian Feng 0000-0002-6396-8698 3
title Effect of image scaling and segmentation in digital rock characterisation
spellingShingle Effect of image scaling and segmentation in digital rock characterisation
Yuntian Feng
title_short Effect of image scaling and segmentation in digital rock characterisation
title_full Effect of image scaling and segmentation in digital rock characterisation
title_fullStr Effect of image scaling and segmentation in digital rock characterisation
title_full_unstemmed Effect of image scaling and segmentation in digital rock characterisation
title_sort Effect of image scaling and segmentation in digital rock characterisation
author_id_str_mv d66794f9c1357969a5badf654f960275
author_id_fullname_str_mv d66794f9c1357969a5badf654f960275_***_Yuntian Feng
author Yuntian Feng
author2 B. D. Jones
Y. T. Feng
Yuntian Feng
format Journal article
container_title Computational Particle Mechanics
container_volume 3
container_issue 2
container_start_page 201
publishDate 2016
institution Swansea University
issn 2196-4378
2196-4386
doi_str_mv 10.1007/s40571-015-0077-0
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering
document_store_str 0
active_str 0
description Digital material characterisation from microstructural geometry is an emerging field in computer simulation. For permeability characterisation, a variety of studies exist where the lattice Boltzmann method (LBM) has been used in conjunction with computed tomography (CT) imaging to simulate fluid flow through microscopic rock pores. While these previous works show that the technique is applicable, the use of binary image segmentation and the bounceback boundary condition results in a loss of grain surface definition when the modelled geometry is compared to the original CT image. We apply the immersed moving boundary (IMB) condition of Noble and Torczynski as a partial bounceback boundary condition which may be used to better represent the geometric definition provided by a CT image. The IMB condition is validated against published work on idealised porous geometries in both 2D and 3D. Following this, greyscale image segmentation is applied to a CT image of Diemelstadt sandstone. By varying the mapping of CT voxel densities to lattice sites, it is shown that binary image segmentation may underestimate the true permeability of the sample. A CUDA-C-based code, LBM-C, was developed specifically for this work and leverages GPU hardware in order to carry out computations.
published_date 2016-04-30T03:30:41Z
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score 11.016235

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