122 citations · 284 across the 4 of their papers we have counts for
4 papers
U-FNO -- An enhanced Fourier neural operator-based deep-learning model for multiphase flow
Gege Wen, Zongyi Li, Kamyar Azizzadenesheli +2
Numerical simulation of multiphase flow in porous media is essential for many geoscience applications. Machine learning models trained with numerical simulation data can provide a…
CCSNet: a deep learning modeling suite for CO storage
Gege Wen, Catherine Hay, Sally M. Benson
Numerical simulation is an essential tool for many applications involving subsurface flow and transport, yet often suffers from computational challenges due to the multi-physics na…
A Physics-informed data reconciliation framework for real-time electricity and emissions tracking
Jacques A de Chalendar, Sally M Benson
To encourage and guide decarbonization efforts, better tools are needed to monitor real-time CO2 and criteria air pollutant emissions from electricity consumption, production, impo…
Multiphase flow prediction with deep neural networks
Gege Wen, Meng Tang, Sally M. Benson
This paper proposes a deep neural network approach for predicting multiphase flow in heterogeneous domains with high computational efficiency. The deep neural network model is able…