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A new parameter estimation algorithm based on ensemble Kalman filter (EnKF) is developed. The developed algorithm combined with the proposed problem parametrization offers an efficient parameter estimation method that converges using very small ensembles. The inverse problem is formulated as a sequential data integration problem. Gaussian Process Regressionâ€¦ (More)

- Laureline Josset, Vasily V. Demyanov, Ahmed H. Elsheikh, Ivan Lunati
- Computers & Geosciences
- 2015

5 In groundwater modeling, Monte Carlo Markov Chain (MCMC) simulations are often used to calibrate aquifer parameters and propagate the uncertainty to the quantity of interest (e.g., pollutant concentration). However, this approach requires a large number of flow simulations and incurs high computational cost, which prevents a systematic evaluation of theâ€¦ (More)

- J. Nagoor Kani, Ahmed H. Elsheikh
- ArXiv
- 2017

We introduce a deep residual recurrent neural network (DR-RNN) as an efficient model reduction technique for nonlinear dynamical systems. The developed DR-RNN is inspired by the iterative steps of line search methods in finding the residual minimiser of numerically discretized differential equations. We formulate this iterative scheme as stacked recurrentâ€¦ (More)

- Ahmed H. Elsheikh, Mary F. Wheeler, Ibrahim Hoteit
- J. Comput. Physics
- 2014

a r t i c l e i n f o a b s t r a c t A Hybrid Nested Sampling (HNS) algorithm is proposed for efficient Bayesian model calibration and prior model selection. The proposed algorithm combines, Nested Sampling (NS) algorithm, Hybrid Monte Carlo (HMC) sampling and gradient estimation using Stochastic Ensemble Method (SEM). NS is an efficient sampling algorithmâ€¦ (More)

Ensemble-based algorithms have been successfully implemented for history matching of geological models. However, their performance is optimal only if the prior-state vector is linearly related to the predicted data and if the joint distribution of the prior-state vector is multivariate Gaussian. Moreover, the number of degrees of freedom is as large as theâ€¦ (More)

- Ahmed H. Elsheikh, Mustafa Elsheikh
- Engineering with Computers
- 2012

We introduce a reliable intersection algorithm for manifold surface meshes. The proposed algorithm builds conforming surface meshes from a set of intersecting triangulated surfaces. This algorithm effectively handles all degenerate triangleâ€“triangle intersection cases. The key idea of the algorithm is based on an extensive set of triangleâ€“edge intersectionâ€¦ (More)

- Ahmed H. Elsheikh, Mary F. Wheeler, Ibrahim Hoteit
- J. Comput. Physics
- 2013

- Ahmed H. Elsheikh, Mustafa Elsheikh
- Advances in Engineering Software
- 2014

A novel parameter estimation algorithm is proposed. The inverse problem is formulated as a sequential data integration problem in which Gaussian process regression (GPR) is used to integrate the prior knowledge (static data). The search space is further parameterized using Karhunenâ€“LoÃ¨ve expansion to build a set of basis functions that spans the searchâ€¦ (More)

- Shing Chan, Ahmed H. Elsheikh
- J. Comput. Physics
- 2018

Several multiscale methods account for sub-grid scale features using coarse scale basis functions. For example, in the Multiscale Finite Volume method the coarse scale basis functions are obtained by solving a set of local problems over dual-grid cells. We introduce a data-driven approach for the estimation of these coarse scale basis functions.â€¦ (More)

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