Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Effect of image scaling and segmentation in digital rock characterisation

Effect of image scaling and segmentation in digital rock characterisation

Thumbnail Image
Download
Name

40571_2015_77_ReferencePDF.pdf

Size

5.86 MB

Format

Adobe PDF

Checksum (MD5)

0972411d50c23afbc60863b4f2896df1

Download all files submitted through automated deposit
art_7637166491556162226.zip (5.83 MB)
Author(s)
Feng, Y. T.
•
Jones, Bruce David
Date Issued
October 2015
Journal
Computational Particle Mechanics
Publisher
Springer International Publishing
Citation
Jones, B. D., and Y. T. Feng. “Effect of Image Scaling and Segmentation in Digital Rock Characterisation.” Computational Particle Mechanics 3, no. 2 (October 19, 2015): 201–213.
Version
Author's final manuscript
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 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.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
http://hdl.handle.net/1721.1/103309
DOI of Published Version
https://doi.org/10.1007/s40571-015-0077-0
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.