Ahmed H. Elsheikh

Professor

Heriot-Watt University

United Kingdom

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Ahmed H. Elsheikh is a Professor at Heriot-Watt University in the United Kingdom. His research encompasses various areas including Bayesian methods for model correction, reinforcement learning applications in flow control, and deep learning techniques for seismic data analysis. Recent publications reflect his work on generative adversarial networks and the development of innovative approaches for geological model verification and inversion.

Articles (15)

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2025

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2025

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2025

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2024

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2023

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2023

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2022

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2022

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2022

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2022

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2022

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2021

Collaborators (3)

Florian Doster

Heriot-Watt University

UNITED KINGDOM

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Morteza Haghighat Sefat

Heriot-Watt University

UNITED KINGDOM

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Andreas Busch

Professor

Heriot-Watt University

UNITED KINGDOM

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Ahmed H. Elsheikh

Research Interests

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Articles (15)

When Cubic Law and Darcy Fail: Bayesian Correction of Model Misspecification in Fracture Conductivities

Model-based reinforcement learning for active flow control

Generation of non-stationary stochastic fields using generative adversarial networks

A Deep Semi-Supervised Learning Approach for Seismic Reflectivity Inversion

Ensemble history-matching workflow using interpretable SPADE-GAN geomodel

Automated seismic semantic segmentation using Attention U-Net

Gym-preCICE: Reinforcement learning environments for active flow control

Robust Optimal Well Control using an Adaptive Multigrid Reinforcement Learning Framework

Verification of a real-time ensemble-based method for updating earth model based on GAN

Direct Multi-Modal Inversion of Geophysical Logs Using Deep Learning

Stochastic optimal well control in subsurface reservoirs using reinforcement learning

Probabilistic model-error assessment of deep learning proxies: an application to real-time inversion of borehole electromagnetic measurements

Generating unrepresented proportions of geological facies using Generative Adversarial Networks

Machine learning-based multiscale constitutive modelling: Development and application to dual-porosity mass transfer

Development of a Probabilistic Framework for Risk-Based Well Decommissioning Design

Collaborators (3)

Florian Doster

Morteza Haghighat Sefat

Andreas Busch

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