403 citations · 831 across the 26 of their papers we have counts for
5 papers · 1 filter
Multi-Asset Closed-Loop Reservoir Management Using Deep Reinforcement Learning
Yusuf Nasir, Louis J. Durlofsky
Closed-loop reservoir management (CLRM), in which history matching and production optimization are performed multiple times over the life of an asset, can provide significant impro…
Use of Multifidelity Training Data and Transfer Learning for Efficient Construction of Subsurface Flow Surrogate Models
Su Jiang, Louis J. Durlofsky
Data assimilation presents computational challenges because many high-fidelity models must be simulated. Various deep-learning-based surrogate modeling techniques have been develop…
Deep reinforcement learning for optimal well control in subsurface systems with uncertain geology
Yusuf Nasir, Louis J. Durlofsky
A general control policy framework based on deep reinforcement learning (DRL) is introduced for closed-loop decision making in subsurface flow settings. Traditional closed-loop mod…
Convolutional-Recurrent Neural Network Proxy for Robust Optimization and Closed-Loop Reservoir Management
Yong Do Kim, Louis J. Durlofsky
Production optimization under geological uncertainty is computationally expensive, as a large number of well control schedules must be evaluated over multiple geological realizatio…
A new flow-kinematics-based model for time-dependent effective dispersion in mixing-limited reactions
Ricardo H. Deucher, Louis J. Durlofsky
A new upscaling procedure that provides 1D representations of 2D mixing-limited reactive transport systems is developed and applied. A key complication with upscaled models in this…