relation: https://khub.utp.edu.my/scholars/17770/
title: A Surrogate Assisted Quantum-Behaved Algorithm for Well Placement Optimization
creator: Islam, J.
creator: Nazir, A.
creator: Hossain, M.M.
creator: Alhitmi, H.K.
creator: Kabir, M.A.
creator: Jallad, A.-H.M.
description: The oil and gas industry faces difficulties in optimizing well placement problems. These problems are multimodal, non-convex, and discontinuous in nature. Various traditional and non-traditional optimization algorithms have been developed to resolve these difficulties. Nevertheless, these techniques remain trapped in local optima and provide inconsistent performance for different reservoirs. This study thereby presents a Surrogate Assisted Quantum-behaved Algorithm to obtain a better solution for the well placement optimization problem. The proposed approach utilizes different metaheuristic optimization techniques such as the Quantum-inspired Particle Swarm Optimization and the Quantum-behaved Bat Algorithm in different implementation phases. Two complex reservoirs are used to investigate the performance of the proposed approach. A comparative study is carried out to verify the performance of the proposed approach. The result indicates that the proposed approach provides a better net present value for both complex reservoirs. Furthermore, it solves the problem of inconsistency exhibited in other methods for well placement optimization. © 2013 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2022
type: Article
type: PeerReviewed
identifier:   Islam, J. and Nazir, A. and Hossain, M.M. and Alhitmi, H.K. and Kabir, M.A. and Jallad, A.-H.M.  (2022) A Surrogate Assisted Quantum-Behaved Algorithm for Well Placement Optimization.  IEEE Access, 10.  pp. 17828-17844.  ISSN 21693536     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123575512&doi=10.1109%2fACCESS.2022.3145244&partnerID=40&md5=1fae89c79005656db307bace134a8bf8
relation: 10.1109/ACCESS.2022.3145244
identifier: 10.1109/ACCESS.2022.3145244