13 citations · 20 across the 7 of their papers we have counts for
3 papers · 1 filter
A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems
Meng Tang, Yimin Liu, Louis J. Durlofsky
A deep-learning-based surrogate model is developed and applied for predicting dynamic subsurface flow in channelized geological models. The surrogate model is based on deep convolu…
Deep-learning-based reduced-order modeling for subsurface flow simulation
Zhaoyang Larry Jin, Yimin Liu, Louis J. Durlofsky
A new deep-learning-based reduced-order modeling (ROM) framework is proposed for application in subsurface flow simulation. The reduced-order model is based on an existing embed-to…
Well control optimization using a two-step surrogate treatment
Daniel Ullmann de Brito, Louis J. Durlofsky
Large numbers of flow simulations are typically required for determining optimal well settings. These simulations are often computationally demanding, which poses challenges for th…