A Surrogate Assisted Quantum-Behaved Algorithm for Well Placement Optimization

The oil and gas industry faces difficulties in optimizing well placement problems. These problems are multimodal, non-convex, discontinuous nature. Various traditional non-traditional optimization algorithms have been developed to resolve these difficulties. Nevertheless, techniques remain trapped local optima provide inconsistent performance for different reservoirs. This study thereby presents a Surrogate Assisted Quantum-behaved Algorithm obtain better solution the problem. proposed approach utilizes metaheuristic such as Quantum-inspired Particle Swarm Optimization Bat implementation phases. Two complex reservoirs used investigate of approach. A comparative is carried out verify result indicates that provides net present value both Furthermore, it solves problem inconsistency exhibited other methods optimization.