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Personal profile

Research interests

  • Parameter estimation for subsurface flow problems
  • Data Assimilation and nonlinear filtering
  • Bayesian uncertainty quantification and model comparison
  • A posteriori error estimation
  • Mesh generation and mesh adaptivity
  • Carbon Capture and Sequestration

Biography

  • August 2017, Associate Professor, Institute of Petroleum Engineering, Heriot-Watt University, Scotland
  • August 2013 - July 2017, Assistant Professor, Institute of Petroleum Engineering, Heriot-Watt University, Scotland
  • June 2012 - July 2013, Research Fellow, ICES, The University of Texas at Austin, USA
  • 2010-2012, Research Associate, ESE, Imperial College London, UK
  • 2007-2010, Assistant Professor, Al-Azhar Univeristy, Egypt
  • 2007 Ph.D., McMaster University, Ontario, Canada
  • 2002 MASc., McMaster University, Ontario, Canada
  • 1999 BASc., Al-Azhar Univeristy, Cairo, Egypt

Fingerprint Dive into the research topics where Ahmed H. Elsheikh is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

carbon sequestration Earth & Environmental Sciences
data assimilation Earth & Environmental Sciences
subsurface flow Earth & Environmental Sciences
Mesh generation Engineering & Materials Science
simulation Earth & Environmental Sciences
sampling Earth & Environmental Sciences
Chaos theory Engineering & Materials Science
Sampling Engineering & Materials Science

Co Author Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2004 2019

A machine learning based hybrid Multi-Fidelity Multi-Level Monte Carlo method for uncertainty quantification

Kani Jabarullah Khan, N. & Elsheikh, A. H., 27 Aug 2019, In : Frontiers in Environmental Science. 7, 105.

Research output: Contribution to journalArticle

Open Access
File
decomposition
machine learning
method
subsurface flow
cost

Hydrogeophysical parameter estimation using iterative ensemble smoothing and approximate forward solvers

Köpke, C., Elsheikh, A. H. & Irving, J., 20 Mar 2019, In : Frontiers in Environmental Science. 7, 34.

Research output: Contribution to journalArticle

Open Access
File
smoothing
ground penetrating radar
data assimilation
travel time
tomography

Identifiability of model discrepancy parameters in history matching

Rammay, M. H., Elsheikh, A. H. & Chen, Y., 10 Apr 2019, SPE Reservoir Simulation Conference 2019. Society of Petroleum Engineers , SPE-193838-MS

Research output: Chapter in Book/Report/Conference proceedingConference contribution

History Matching
Error Model
Identifiability
Model Error
Discrepancy

Parametric generation of conditional geological realizations using generative neural networks

Chan, S. & Elsheikh, A. H., Oct 2019, In : Computational Geosciences. 23, 5, p. 925-952 28 p.

Research output: Contribution to journalArticle

Open Access
File
Parametrization
conditioning
Conditioning
Neural Networks
Neural networks

Quantification of prediction uncertainty using imperfect subsurface models with model error estimation

Rammay, M. H., Elsheikh, A. H. & Chen, Y., Sep 2019, In : Journal of Hydrology. 576, p. 764-783 20 p.

Research output: Contribution to journalArticle

prediction
data assimilation
modeling
calibration
parameter