activity
20222024
most citedStochastic optimal well control in subsurface reservoirs using reinforcement learning

26 citations · 34 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

A Recurrent YOLOv8-based framework for Event-Based Object Detection

Diego A. Silva, Kamilya Smagulova, Ahmed Elsheikh +2

Object detection is crucial in various cutting-edge applications, such as autonomous vehicles and advanced robotics systems, primarily relying on data from conventional frame-based…

cs.LG2023

Gym-preCICE: Reinforcement Learning Environments for Active Flow Control

Mosayeb Shams, Ahmed H. Elsheikh

Active flow control (AFC) involves manipulating fluid flow over time to achieve a desired performance or efficiency. AFC, as a sequential optimisation task, can benefit from utilis…

cs.LG2022

Robust optimal well control using an adaptive multi-grid reinforcement learning framework

Atish Dixit, Ahmed H. ElSheikh

Reinforcement learning (RL) is a promising tool to solve robust optimal well control problems where the model parameters are highly uncertain, and the system is partially observabl…

cs.LG202226 cited

Stochastic optimal well control in subsurface reservoirs using reinforcement learning

Atish Dixit, Ahmed H. ElSheikh

We present a case study of model-free reinforcement learning (RL) framework to solve stochastic optimal control for a predefined parameter uncertainty distribution and partially ob…

physics.geo-ph20228 cited

Probabilistic forecasting for geosteering in fluvial successions using a generative adversarial network

Sergey Alyaev, Jan Tveranger, Kristian Fossum +1

Quantitative workflows utilizing real-time data to constrain ahead-of-bit uncertainty have the potential to improve geosteering significantly. Fast updates based on real-time data…