Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
1 file | 3.79 MB
Add to list
  1. Search results
  2. Python workflow for segmenting multip...

Python workflow for segmenting multiphase flow in porous rocks

Catherine Spurin, Sharon Ellman (UGent) , Dane Sherburn, Tom Bultreys (UGent) and Hamdi A. Tchelepi
(2024) TRANSPORT IN POROUS MEDIA. 151(15). p.2819-2834
Author
Organization
Project
Abstract
X-ray micro-computed tomography (X-ray micro-CT) is widely employed to investigate flow phenomena in porous media, providing a powerful alternative to core-scale experiments for estimating traditional petrophysical properties such as porosity, single-phase permeability or fluid connectivity. However, the segmentation process, critical for deriving these properties from greyscale images, varies significantly between studies due to the absence of a standardized workflow or any ground truth data. This introduces challenges in comparing results across different studies, especially for properties sensitive to segmentation. To address this, we present a fully open-source, automated workflow for the segmentation of a Bentheimer sandstone filled with nitrogen and brine. The workflow incorporates a traditional image processing pipeline, including non-local means filtering, image registration, watershed segmentation of grains, and a combination of differential imaging and thresholding for segmentation of the fluid phases. Our workflow enhances reproducibility by enabling other research groups to easily replicate and validate findings, fostering consistency in petrophysical property estimation. Moreover, its modular structure facilitates integration into modeling frameworks, allowing for forward-backward communication and parameter sensitivity analyses. We apply the workflow to exploring the sensitivity of the non-wetting phase volume, surface area, and connectivity to image processing. This adaptable tool paves the way for future advancements in X-ray micro-CT analysis of porous media.
Keywords
QUANTITATIVE-ANALYSIS, SEGMENTATION, FLUID, Multiphase flow, Porous media, Segmentation, Image processing, Sensitivity analysis

Downloads

  • Download
    (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 3.79 MB

Citation

Please use this url to cite or link to this publication:

MLA
Spurin, Catherine, et al. “Python Workflow for Segmenting Multiphase Flow in Porous Rocks.” TRANSPORT IN POROUS MEDIA, vol. 151, no. 15, 2024, pp. 2819–34, doi:10.1007/s11242-024-02136-2.
APA
Spurin, C., Ellman, S., Sherburn, D., Bultreys, T., & Tchelepi, H. A. (2024). Python workflow for segmenting multiphase flow in porous rocks. TRANSPORT IN POROUS MEDIA, 151(15), 2819–2834. https://doi.org/10.1007/s11242-024-02136-2
Chicago author-date
Spurin, Catherine, Sharon Ellman, Dane Sherburn, Tom Bultreys, and Hamdi A. Tchelepi. 2024. “Python Workflow for Segmenting Multiphase Flow in Porous Rocks.” TRANSPORT IN POROUS MEDIA 151 (15): 2819–34. https://doi.org/10.1007/s11242-024-02136-2.
Chicago author-date (all authors)
Spurin, Catherine, Sharon Ellman, Dane Sherburn, Tom Bultreys, and Hamdi A. Tchelepi. 2024. “Python Workflow for Segmenting Multiphase Flow in Porous Rocks.” TRANSPORT IN POROUS MEDIA 151 (15): 2819–2834. doi:10.1007/s11242-024-02136-2.
Vancouver
1.
Spurin C, Ellman S, Sherburn D, Bultreys T, Tchelepi HA. Python workflow for segmenting multiphase flow in porous rocks. TRANSPORT IN POROUS MEDIA. 2024;151(15):2819–34.
IEEE
[1]
C. Spurin, S. Ellman, D. Sherburn, T. Bultreys, and H. A. Tchelepi, “Python workflow for segmenting multiphase flow in porous rocks,” TRANSPORT IN POROUS MEDIA, vol. 151, no. 15, pp. 2819–2834, 2024.
@article{01JDRVYNXG7T46BKPP8T0SVXNZ,
  abstract     = {{X-ray micro-computed tomography (X-ray micro-CT) is widely employed to investigate flow phenomena in porous media, providing a powerful alternative to core-scale experiments for estimating traditional petrophysical properties such as porosity, single-phase permeability or fluid connectivity. However, the segmentation process, critical for deriving these properties from greyscale images, varies significantly between studies due to the absence of a standardized workflow or any ground truth data. This introduces challenges in comparing results across different studies, especially for properties sensitive to segmentation. To address this, we present a fully open-source, automated workflow for the segmentation of a Bentheimer sandstone filled with nitrogen and brine. The workflow incorporates a traditional image processing pipeline, including non-local means filtering, image registration, watershed segmentation of grains, and a combination of differential imaging and thresholding for segmentation of the fluid phases. Our workflow enhances reproducibility by enabling other research groups to easily replicate and validate findings, fostering consistency in petrophysical property estimation. Moreover, its modular structure facilitates integration into modeling frameworks, allowing for forward-backward communication and parameter sensitivity analyses. We apply the workflow to exploring the sensitivity of the non-wetting phase volume, surface area, and connectivity to image processing. This adaptable tool paves the way for future advancements in X-ray micro-CT analysis of porous media.}},
  author       = {{Spurin, Catherine and Ellman, Sharon and Sherburn, Dane and Bultreys, Tom and Tchelepi, Hamdi A.}},
  issn         = {{0169-3913}},
  journal      = {{TRANSPORT IN POROUS MEDIA}},
  keywords     = {{QUANTITATIVE-ANALYSIS,SEGMENTATION,FLUID,Multiphase flow,Porous media,Segmentation,Image processing,Sensitivity analysis}},
  language     = {{eng}},
  number       = {{15}},
  pages        = {{2819--2834}},
  title        = {{Python workflow for segmenting multiphase flow in porous rocks}},
  url          = {{http://doi.org/10.1007/s11242-024-02136-2}},
  volume       = {{151}},
  year         = {{2024}},
}
Altmetric
View in Altmetric
Web of Science
Times cited: