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dc.contributor.advisorRong, Chunming
dc.contributor.authorHaugsand, Fredrik
dc.date.accessioned2018-09-25T12:32:10Z
dc.date.available2018-09-25T12:32:10Z
dc.date.issued2018-06-15
dc.identifier.urihttp://hdl.handle.net/11250/2564400
dc.descriptionMaster's thesis in Computer sciencenb_NO
dc.description.abstractThis thesis focuses on evaluation and testing different approaches of image recognition, neural networks and data analytics with application to the analysis of data collected from sensors installed in wells operated in the oil and gas industry. Simple image recognition algorithms are compared with a newly implemented approach for feature extraction. Two different neural networks are also described and implemented, to compare against the image recognition. Image recognition algorithms had a limited amount of success due to the sample size of images, while neural networks and feature extraction are viable methods to analyse and classify pressure transients.nb_NO
dc.language.isoengnb_NO
dc.publisherUniversity of Stavanger, Norwaynb_NO
dc.relation.ispartofseriesMasteroppgave/UIS-TN-IDE/2018;
dc.subjectinformasjonsteknologinb_NO
dc.subjectdatateknikknb_NO
dc.subjectnevrale nettverknb_NO
dc.subjectneural networksnb_NO
dc.subjectoljeanalysenb_NO
dc.titleTesting Different Ways to analyse Data from Well Sensors Using Neural Networks and Image Processingnb_NO
dc.typeMaster thesisnb_NO
dc.subject.nsiVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550::Datateknologi: 551nb_NO


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