Modeling of heterogeneous materials and media is a problem of fundamental importance to
a wide variety of phenomena with applications to many disciplines, ranging from condensed …

This paper reviews the application of the algorithm particle swarm optimization (PSO) to
perform stochastic inverse modeling of geophysical data. The main features of PSO are …

Providing an up-to-date overview of the most popular global optimization methods used in
interpreting geophysical observations, this new edition includes a detailed description of the …

This paper describes a new method for gradually deforming realizations of Gaussian-related
stochastic models while preserving their spatial variability. This method consists in building …

Generating one realization of a random permeability field that is consistent with observed
pressure data and a known variogram model is not a difficult problem. If, however, one …

The need to determine the optimum well placement which causes maximum cumulative oil
production has dramatically raised in recent years. Hence, there is a need for a reliable and …

The process of conditioning the geological or the static model to production data is typically
known as history matching (HM). The economic viability of a petroleum recovery project is …

Abstract Steam-Assisted Gravity Drainage (SAGD) is a commercial in situ recovery
technology that is effective at recovering heavy oil and bitumen. However, generation of …

Uncertainty quantification is an increasingly important aspect of many areas of
computational science, where the challenge is to make reliable predictions about the …

This paper describes the implementation of a Genetic Algorithm (GA) to carry out
hydrocarbon reservoir characterisation by conditioning the reservoir simulation model to …