This paper presents a review of history matching and oil field development optimization
techniques with a focus on optimization algorithms. History matching algorithms are …

We consider a technique to estimate an approximate gradient using an ensemble of
randomly chosen control vectors, known as Ensemble Optimization (EnOpt) in the oil and …

Solving a large‐scale optimization problem with nonlinear state constraints is challenging
when adjoint gradients are not available for computing the derivatives needed in the basic …

With the energy demand arising globally, geothermal recovery by Enhanced Geothermal
Systems (EGS) becomes a promising option to bring a sustainable energy supply and …

We develop a framework based on the lexicographic method and the newly developed
Stochastic-Simplex-Approximate-Gradient (StoSAG) algorithm to maximize the expected net …

In science and engineering, non-linear constrained optimization has been a useful
mathematical technique for many practical applications. Of interest to us is its applicability in …

With the energy demand arising globally, geothermal recovery by Enhanced Geothermal
Systems (EGS) becomes a promising option to bring sustainable energy supply along with …

In well control (production) optimization, the computational cost of conducting a full-physics
flow simulation on a 3D, rich grid-based model poses a significant challenge. This challenge …

Geothermal energy is clean, renewable, and cost-effective and its efficient recovery
management mandates optimizing engineering parameters while considering the …

When planning wind farms it is important to optimize the layout to increase production and
reduce costs. In this paper we minimize the levelized cost of energy (LCOE) for a floating …