eprintid: 17770
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/77/70
datestamp: 2023-12-19 03:24:05
lastmod: 2023-12-19 03:24:05
status_changed: 2023-12-19 03:08:39
type: article
metadata_visibility: show
creators_name: Islam, J.
creators_name: Nazir, A.
creators_name: Hossain, M.M.
creators_name: Alhitmi, H.K.
creators_name: Kabir, M.A.
creators_name: Jallad, A.-H.M.
title: A Surrogate Assisted Quantum-Behaved Algorithm for Well Placement Optimization
ispublished: pub
keywords: Gas industry; Heuristic algorithms; Nonlinear programming; Petroleum reservoirs; Quantum computers, Heuristics algorithm; Metaheuristic; Multi-modal optimization; Nonlinear optimization problems; Oil; Optimisations; Reservoir-simulation; Search problem; Tuning; Well placement optimization, Particle swarm optimization (PSO)
note: cited By 4
abstract: 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.
date: 2022
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123575512&doi=10.1109%2fACCESS.2022.3145244&partnerID=40&md5=1fae89c79005656db307bace134a8bf8
id_number: 10.1109/ACCESS.2022.3145244
full_text_status: none
publication: IEEE Access
volume: 10
pagerange: 17828-17844
refereed: TRUE
issn: 21693536
citation:   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