Application Of Arx Neural Networks To Model The Rate Of Penetration Of Petroleum Wells Drilling

dc.creatorFonseca T.C.
dc.creatorMendes J.R.P.
dc.creatorSerapiao A.B.S.
dc.creatorGuilherme I.R.
dc.date2006
dc.date2015-06-30T18:04:10Z
dc.date2015-11-26T14:20:21Z
dc.date2015-06-30T18:04:10Z
dc.date2015-11-26T14:20:21Z
dc.date.accessioned2018-03-28T21:22:00Z
dc.date.available2018-03-28T21:22:00Z
dc.identifier0889866023; 9780889866027
dc.identifierProceedings Of The 2nd Iasted International Conference On Computational Intelligence, Ci 2006. , v. , n. , p. 152 - 157, 2006.
dc.identifier
dc.identifier
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-56349150914&partnerID=40&md5=7107786357ebec417c534d35d5d2f78e
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/102939
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/102939
dc.identifier2-s2.0-56349150914
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1244221
dc.descriptionBit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates tend to follow the projects-demand and barrel-price rises. A methodology to model and predict one of the drilling bit performance evaluator, the Rate of Penetration (ROP), is presented herein. As the parameters affecting the ROP are complex and their relationship not easily modeled, the application of a Neural Network is suggested. In the present work, a dynamic neural network, based on the Auto-Regressive with Extra Input Signals model, or ARX model, is used to approach the ROP modeling problem. The network was applied to a real oil offshore field data set, consisted of information from seven wells drilled with an equal-diameter bit.
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dc.description152
dc.description157
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dc.languageen
dc.publisher
dc.relationProceedings of the 2nd IASTED International Conference on Computational Intelligence, CI 2006
dc.rightsfechado
dc.sourceScopus
dc.titleApplication Of Arx Neural Networks To Model The Rate Of Penetration Of Petroleum Wells Drilling
dc.typeActas de congresos


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