A New Energy-Aware Method for Gas Lift Allocation in IoT-Based Industries Using a Chemical Reaction-Based Optimization Algorithm

dc.authoridJafari Navimipour, Nima/0000-0002-5514-5536
dc.authoridZanbouri, Kouros/0000-0003-0252-8282;
dc.authorwosidJafari Navimipour, Nima/AAF-5662-2021
dc.authorwosidZanbouri, Kouros/C-5031-2019
dc.authorwosidNasarian, Elham/ISB-6863-2023
dc.contributor.authorJafari Navimipour, Nima
dc.contributor.authorBastak, Mostafa Razoughi
dc.contributor.authorAlizadeh, Seyed Mehdi
dc.contributor.authorNavimipour, Nima Jafari
dc.contributor.authorYalcin, Senay
dc.date.accessioned2023-10-19T15:12:03Z
dc.date.available2023-10-19T15:12:03Z
dc.date.issued2022
dc.department-temp[Zanbouri, Kouros] Islamic Azad Univ, Dept Comp Engn, Tabriz Branch, Tabriz 5157944533, Iran; [Bastak, Mostafa Razoughi] Univ Regina, Petr Syst Engn Engn & Appl Sci, Regina, SK S4S 0A2, Canada; [Alizadeh, Seyed Mehdi] Australian Univ, Petr Engn Dept, West Mishref 13015, Kuwait; [Navimipour, Nima Jafari] Kadir Has Univ, Dept Comp Engn, TR-34083 Istanbul, Turkey; [Yalcin, Senay] Nisantasi Univ, Dept Comp Engn, TR-34398 Istanbul, Turkeyen_US
dc.description.abstractThe Internet of Things (IoT) has recently developed opportunities for various industries, including the petrochemical industry, that allow for intelligent manufacturing with real-time management and the analysis of the produced big data. In oil production, extracting oil reduces reservoir demand, causing oil supply to fall below the economically viable level. Gas lift is a popular artificial lift system that is both efficient and cost-effective. If gas supplies in the gas lift process are not limited, a sufficient amount of gas may be injected into the reservoir to reach the highest feasible production rate. Because of the limited supply of gas, it is essential to achieve the sustainable utilization of our limited resources and manage the injection rate of the gas into each well in order to enhance oil output while reducing gas injection. This study describes a novel IoT-based chemical reaction optimization (CRO) technique to solve the gas lift allocation issue. The CRO algorithm is inspired by the interaction of molecules with each other and achieving the lowest possible state of free energy from an unstable state. The CRO algorithm has excellent flexibility, enabling various operators to modify solutions and a favorable trade-off between intensification and diversity. A reasonably fast convergence rate serves as a powerful motivator to use as a solution. The extensive simulation and computational study have presented that the proposed method using CRO based on IoT systems significantly improves the overall oil production rate and reduces gas injection, energy consumption and cost compared to traditional algorithms. Therefore, it provides a more efficient system for the petroleum production industry.en_US
dc.identifier.citation2
dc.identifier.doi10.3390/electronics11223769en_US
dc.identifier.issn2079-9292
dc.identifier.issue22en_US
dc.identifier.scopus2-s2.0-85142426626en_US
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.3390/electronics11223769
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5328
dc.identifier.volume11en_US
dc.identifier.wosWOS:000887132600001en_US
dc.identifier.wosqualityN/A
dc.khas20231019-WoSen_US
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.ispartofElectronicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectScheduling ProblemEn_Us
dc.subjectWellsEn_Us
dc.subjectConstraintsEn_Us
dc.subjectFrameworkEn_Us
dc.subjectinternet of thingsen_US
dc.subjectenergyen_US
dc.subjectScheduling Problem
dc.subjectchemical reaction optimizationen_US
dc.subjectWells
dc.subjectgas lift allocationen_US
dc.subjectConstraints
dc.subjectmulti-objective optimizationen_US
dc.subjectFramework
dc.subjectgas injection rateen_US
dc.titleA New Energy-Aware Method for Gas Lift Allocation in IoT-Based Industries Using a Chemical Reaction-Based Optimization Algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e
relation.isAuthorOfPublication.latestForDiscovery0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e

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