Generation of pore-space images using improved pyramid Wasserstein generative adversarial networks-Reference-Cited by-同舟云学术

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Generation of pore-space images using improved pyramid Wasserstein generative adversarial networks

Published:2024-08 Issue: Volume:190 Page:104748
ISSN:0309-1708
Container-title:Advances in Water Resources
language:en
Short-container-title:Advances in Water Resources

Author:

Zhu Linqi^ORCID,Bijeljic Branko^ORCID,Blunt Martin J.^ORCID

Publisher

Elsevier BV

Reference49 articles.

1. Pore-GNN: A graph neural network-based framework for predicting flow properties of porous media from micro-CT images.;Alzahrani;Adv. Geo-Energy Res.,2023

2. Kinetics of wettability alteration and droplet detachment from a solid surface by low-salinity: A lattice-Boltzmann method;An;Fuel,2022

3. Predictions of non-fickian solute transport in different classes of porous media using direct simulation on pore-scale images;Bijeljic;Phys. Rev. E,2013

4. Using two-point correlation functions to characterize microgeometry and estimate permeabilities of sandstones and porous glass;Blair;J. Geophys. Res. Solid Earth,1996

5. Investigating the relative permeability behavior of microporosity-rich carbonates and tight sandstones with multiscale pore network models;Bultreys;J. Geophys. Res. Solid Earth,2016

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