5 papers
Property-Constrained 3D Porous Media Reconstruction from 2D Images via Conditional Generative Adversarial Networks
Ali Sadeghkhani, Brandon Bennett, Arash Rabbani
This study presents a conditional Generative Adversarial Network (cGAN) framework for generating 3D porous media volumes with controlled porosity, trained exclusively on 2D thin se…
A Decade of Generative Adversarial Networks for Porous Material Reconstruction
Ali Sadeghkhani, Brandon Bennett, Masoud Babaei +1
Digital reconstruction of porous materials has become increasingly critical for applications ranging from geological reservoir characterization to tissue engineering and electroche…
Well Log-Guided Synthesis of Subsurface Images from Sparse Petrography Data Using cGANs
Ali Sadeghkhani, A. Assadi, B. Bennett +1
Pore-scale imaging of subsurface formations is costly and limited to discrete depths, creating significant gaps in reservoir characterization. To address this, we present a conditi…
PCP-GAN: Property-Constrained Pore-scale image reconstruction via conditional Generative Adversarial Networks
Ali Sadeghkhani, Brandon Bennett, Masoud Babaei +1
Obtaining truly representative pore-scale images that match bulk formation properties remains a fundamental challenge in subsurface characterization, as natural spatial heterogenei…
Multivariate Interval-Valued Models in Frequentist and Bayesian Schemes
Ali Sadeghkhani, Abdolnasser Sadeghkhani
In recent years, addressing the challenges posed by massive datasets has led researchers to explore aggregated data, particularly leveraging interval-valued data, akin to tradition…