6 citations · 10 across the 3 of their papers we have counts for
3 papers
physics.data-an2024
Building a Life Cycle Assessment Model using Bayesian Networks
Cedric Fraces Gasmi, Wennan Long
This paper introduces the Oilfield Pollutant Graphical Model (OPGM), an innovative approach designed to improve the benchmarking and uncertainty analysis of greenhouse gas (GHG) em…
cs.CE2022★ 4 cited
Uncertainty Quantification for Transport in Porous media using Parameterized Physics Informed neural Networks
Cedric Fraces Gasmi, Hamdi Tchelepi
We present a Parametrization of the Physics Informed Neural Network (P-PINN) approach to tackle the problem of uncertainty quantification in reservoir engineering problems. We demo…
physics.flu-dyn2021★ 6 cited
Physics Informed Deep Learning for Flow and Transport in Porous Media
Cedric Fraces Gasmi, Hamdi Tchelepi
We present our progress on the application of physics informed deep learning to reservoir simulation problems. The model is a neural network that is jointly trained to respect gove…