160 citations · 162 across the 14 of their papers we have counts for
7 papers · 1 filter
Vision Mamba for Permeability Prediction of Porous Media
Ali Kashefi, Tapan Mukerji
Vision Mamba has recently received attention as an alternative to Vision Transformers (ViTs) for image classification. The network size of Vision Mamba scales linearly with input i…
Pix2Geomodel: A Next-Generation Reservoir Geomodeling with Property-to-Property Translation
Abdulrahman Al-Fakih, Ardiansyah Koeshidayatullah, Nabil A. Saraih +4
Accurate geological modeling is critical for reservoir characterization, yet traditional methods struggle with complex subsurface heterogeneity, and they have problems with conditi…
Deep learning forecasts the spatiotemporal evolution of fluid-induced microearthquakes
Jaehong Chung, Michael Manga, Timothy Kneafsey +2
Microearthquakes (MEQs) generated by subsurface fluid injection record the evolving stress state and permeability of reservoirs. Forecasting their full spatiotemporal evolution is…
Image registration of 2D optical thin sections in a 3D porous medium: Application to a Berea sandstone digital rock image
Jaehong Chung, Wei Cai, Tapan Mukerji
This study proposes a systematic image registration approach to align 2D optical thin-section images within a 3D digital rock volume. Using template image matching with differentia…
Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometries
Ali Kashefi, Tapan Mukerji
Kolmogorov-Arnold Networks (KANs) have gained attention as an alternative to traditional multilayer perceptrons (MLPs) for deep learning applications in computational physics, part…
Seismic inversion using hybrid quantum neural networks
Divakar Vashisth, Rohan Sharma, Tejas Ganesh Iyer +2
Seismic inversion-including post-stack, pre-stack, and full waveform inversion is compute and memory-intensive. Recently, several approaches, including physics-informed machine lea…
Pre-stack and post-stack seismic inversion using quantum computing
Divakar Vashisth, Rodney Lessard, Tapan Mukerji
Quantum computing harnesses the principles of quantum mechanics to solve problems that are intractable for classical computers. Quantum annealing, a specialized approach within qua…