Linking Scales in Multiphase Flow: A Framework Incorporating Data-Driven Methods for Predicting Relative Permeability

Linking Scales in Multiphase Flow: A Framework Incorporating Data-Driven Methods for Predicting Relative Permeability | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 10 February 2025 V1 Latest version Share on Linking Scales in Multiphase Flow: A Framework Incorporating Data-Driven Methods for Predicting Relative Permeability Authors : Mohammad Ebadi 0000-0002-9298-9519 [email protected] , Peyman Mostaghimi 0000-0002-2071-6247 , and Ryan Armstrong 0000-0001-6431-7902 Authors Info & Affiliations https://doi.org/10.22541/au.173921708.85012858/v1 Published Water Resources Research Version of record Peer review timeline 356 views 207 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Accurate prediction of relative permeability is essential for continuum-scale simulations of multiphase flow in porous media. Fluid configurations obtained from pore-scale simulations can be upscaled to derive relative permeability at the continuum-scale. To address the limitations of traditional methods, this study proposes a thermodynamically consistent workflow that employs a data-driven approach to predict relative permeability from fluid configurations based on wettability at the continuum-scale. By leveraging pre-trained models, the workflow eliminates the need for repetitive pore-scale simulations. Validation using μCT images demonstrates the accuracy and reliability of the proposed workflow. The integration with continuum-scale simulators like MRST further highlights its practical applicability, providing robust and scalable modeling capabilities. This study introduces an innovative and efficient solution for modeling complex multiphase flow in porous media, advancing the computational tools available for continuum-scale simulations. Supplementary Material File (1023192_0_merged_1738474421.pdf) Download 3.77 MB File (supporting information.pdf) Download 184.04 KB Information & Authors Information Version history V1 Version 1 10 February 2025 Peer review timeline Published Water Resources Research Version of Record 2 Nov 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords continuum-scale data-driven approach fluid configurations relative permeability upscaling wettability Authors Affiliations Mohammad Ebadi 0000-0002-9298-9519 [email protected] University of New South Wales View all articles by this author Peyman Mostaghimi 0000-0002-2071-6247 University of New South Wales View all articles by this author Ryan Armstrong 0000-0001-6431-7902 University of New South Wales, Australia View all articles by this author Funding Information Australian Research Council FT210100165 Ryan T. Armstrong Metrics & Citations Metrics Article Usage 356 views 207 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Mohammad Ebadi, Peyman Mostaghimi, Ryan Armstrong. Linking Scales in Multiphase Flow: A Framework Incorporating Data-Driven Methods for Predicting Relative Permeability. Authorea . 10 February 2025. DOI: https://doi.org/10.22541/au.173921708.85012858/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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