Publication:
Analytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipeline

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dc.citedby0
dc.contributor.authorIsmail F.B.en_US
dc.contributor.authorYuhana M.I.F.en_US
dc.contributor.authorMohammed S.A.en_US
dc.contributor.authorSabri L.S.en_US
dc.contributor.authorid58027086700en_US
dc.contributor.authorid59155962700en_US
dc.contributor.authorid57189212521en_US
dc.contributor.authorid57201654441en_US
dc.date.accessioned2025-03-03T07:47:30Z
dc.date.available2025-03-03T07:47:30Z
dc.date.issued2024
dc.description.abstractAbstract: Oil and gas production operations, particularly those involving subsea production systems, are frequently subjected to harsh underwater conditions characterized by low temperatures and high pressures, owing to the placement of most subsea facilities on the seabed. These challenging environmental factors often lead to the formation of gas hydrates, especially in the presence of moisture within the production fluidIn this study, A suggestion is made to employ an underwater wireless sensor network (UWSN) to showcase the viability of real-time monitoring of pipeline health conditions, aiming to mitigate problems associated with hydrate formation in oil and gas pipelines. Additionally, A predictive analytical model for gas hydrate formation in these pipelines is crafted using Aspen HYSYS simulation and Feed-Forward Artificial Neural Network (ANN) modeling. The development of this prediction model and the potential application of UWSN technology in the oil and gas production field could assist operators in making informed decisions regarding intervention processes for addressing hydrate-related challenges in pipelines. ? Pleiades Publishing, Ltd. 2024.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1134/S107042722401004X
dc.identifier.epage45
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85195139667
dc.identifier.spage36
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85195139667&doi=10.1134%2fS107042722401004X&partnerID=40&md5=0ea26b9cf677235759c1e7fa0bd83faf
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/37102
dc.identifier.volume97
dc.pagecount9
dc.publisherPleiades Publishingen_US
dc.sourceScopus
dc.sourcetitleRussian Journal of Applied Chemistry
dc.subjectFeedforward neural networks
dc.subjectGases
dc.subjectHydration
dc.subjectWireless sensor networks
dc.subjectAnalytical predictions
dc.subjectFlow assurance
dc.subjectGas hydrates formation
dc.subjectHydrate formation
dc.subjectHydrate formation conditions
dc.subjectOil and gas production
dc.subjectOil-and-Gas pipelines
dc.subjectProduction operations
dc.subjectSubsea production systems
dc.subjectUnderwater wireless sensor networks
dc.subjectGas hydrates
dc.titleAnalytical Prediction of Gas Hydrate Formation Conditions for Oil and Gas Pipelineen_US
dc.typeArticleen_US
dspace.entity.typePublication
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