… The main objective of this paper is to evaluate the feasibility of CMAES in the well placement
optimization and to compare CMAES and the genetic algorithm. However, if the NPV is …

… In this study, a novel data-driven evolutionary algorithm called GDDE is proposed for well-placement
and joint optimization problems. The main framework of GDDE is introduced first, …

… This algorithm has been used previously in many other … the optimization of well placement
problem. We demonstrate that the DE method outperforms an existing Genetic Algorithm for …

… -added optimization tool, which can solve the well placement … with a real well placement
problem with arbitrary well trajectories, … In this intelligent approach, a Genetic Algorithm (GA) …

… it is a member of the evolutionary algorithm family. Like the well-known genetic algorithm (GA),
it is … We describe the implementation of the DE algorithm for a well placement optimization …

… or nonconventional wells) is a crucial task. In order to optimize well placement, several …
These are the parameter sought to be optimized, for instance well location and trajectory. …

… on a Genetic Algorithm for the simultaneous optimization of number, location and trajectory
for producer and injector wells. … -aided optimization tool to deal with realistic well placement …

… optimizing well placement under field constraints is presented that use a constrained
space-filling experimental design, genetic algorithm … , as its basis for optimization. The hybrid …

… For completeness, we include comparisons with the Nelder–Mead (N–M) and genetic
algorithm (GA) approaches. Using the revenue surface information defined on each of the 3904 …

… DE is another popular stochastic optimization algorithm. It is essentially the genetic algorithm
… DE and genetic algorithms assume that selectively breeding well-performing genes over …