Diffusion model-based generation of three-dimensional multiphase pore-scale images
File(s)
Published version
Author(s)
Zhu, Linqi
Bijeljic, Branko
Blunt, Martin J
Type
Journal Article
Abstract
We propose a diffusion model-based machine learning method for generating three-dimensional images of both the pore space of rocks and the fluid phases within it. This approach overcomes the limitations of current methods, which are restricted to generating only the pore space. Our reconstructed images accurately reproduce multiphase fluid pore-scale details in water-wet Bentheimer sandstone, matching experimental images in terms of two-point correlation, porosity, and fluid flow parameters. This method outperforms generative adversarial networks with a broader and more accurate parameter range. By enabling the generation of multiphase fluid pore-scale images of any size subject to computational constraints, this machine learning technique provides researchers with a powerful tool to understand fluid distribution and movement in porous materials without the need for costly experiments or complex simulations. This approach has wide-ranging potential applications, including carbon dioxide and underground hydrogen storage, the design of electrolyzers, and fuel cells.
Date Issued
2025-03-17
Date Acceptance
2025-02-22
Citation
Transport in Porous Media, 2025, 152 (3)
ISSN
0169-3913
Publisher
Springer
Journal / Book Title
Transport in Porous Media
Volume
152
Issue
3
Copyright Statement
© The Author(s) 2025 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Subjects
Curvature
Diffusion models
Engineering
Engineering, Chemical
FLOW
Flow in porous media
Multiphase image generation
POROUS-MEDIA
RECONSTRUCTION
Science & Technology
Technology
Transformer
Publication Status
Published
Article Number
22
Date Publish Online
2025-03-17