222 citations · 372 across the 17 of their papers we have counts for
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physics.geo-ph2022★ 19 cited
Direct Estimation of Porosity from Seismic Data using Rock and Wave Physics Informed Neural Networks (RW-PINN)
Divakar Vashisth, Tapan Mukerji
Petrophysical inversion is an important aspect of reservoir modeling. However due to the lack of a unique and straightforward relationship between seismic traces and rock propertie…
physics.geo-ph2022★ 9 cited
Computation of effective elastic moduli of rocks using hierarchical homogenization
Rasool Ahmad, Mingliang Liu, Michael Ortiz +2
This work focuses on computing the homogenized elastic properties of rocks from 3D micro-computed-tomography (micro-CT) scanned images. The accurate computation of homogenized prop…
physics.flu-dyn2022★ 1 cited
Prediction of fluid flow in porous media by sparse observations and physics-informed PointNet
Ali Kashefi, Tapan Mukerji
We predict steady-state Stokes flow of fluids within porous media at pore scales using sparse point observations and a novel class of physics-informed neural networks, called "phys…