dc.contributor.author | Magnusson, Lars Vidar | |
dc.contributor.author | Olsson, Roland J. | |
dc.contributor.author | Tran, Chau Thi Thuy | |
dc.date.accessioned | 2023-10-17T06:56:12Z | |
dc.date.available | 2023-10-17T06:56:12Z | |
dc.date.created | 2023-05-25T10:53:42Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | IEEE Intelligent Systems. 2023, 38 (2), 73-80. | en_US |
dc.identifier.issn | 1541-1672 | |
dc.identifier.uri | https://hdl.handle.net/11250/3096837 | |
dc.description.abstract | We have conducted a comparison between three types of recurrent neural networks and their ability to predict anomalies occurring in oil wells using a publicly available dataset. We have included two types of well-known state-of-the-art recurrent neural networks and a new type with neurons evolved specifically for the dataset using automatic programming. We show that the new type of recurrent neuron offers a massive improvement over the state of the art. The overall test accuracy of the new network type is 94.6%, which is an improvement by 18.3%, or 14.6 percentage points. We also show that a network with the new neuron performs better than any other solution proposed for the dataset. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | IEEE | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.subject | neurons | en_US |
dc.subject | mathematical models | en_US |
dc.subject | predictive models | en_US |
dc.subject | recurrent neural networks | en_US |
dc.subject | intelligent systems | en_US |
dc.subject | oil drilling | en_US |
dc.subject | DH-HEMTs | en_US |
dc.subject | hydrocarbon reservoirs | en_US |
dc.subject | oil drilling | en_US |
dc.subject | production engineering computing | en_US |
dc.subject | recurrent neural nets | en_US |
dc.subject | automatic programming | en_US |
dc.subject | network type | en_US |
dc.subject | oil well event prediction | en_US |
dc.subject | publicly available dataset | en_US |
dc.subject | recurrent neural networks | en_US |
dc.subject | recurrent neuron | en_US |
dc.title | Recurrent Neural Networks for Oil Well Event Prediction | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.subject.nsi | VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 | en_US |
dc.source.pagenumber | 73-80 | en_US |
dc.source.volume | 38 | en_US |
dc.source.journal | IEEE Intelligent Systems | en_US |
dc.source.issue | 2 | en_US |
dc.identifier.doi | 10.1109/MIS.2023.3252446 | |
dc.identifier.cristin | 2149166 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |