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A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

dc.contributor.authorFonseca, Tiago C.
dc.contributor.authorMendes, José Ricardo P.
dc.contributor.authorSerapião, Adriane B.S. [UNESP]
dc.contributor.authorGuilherme, Ivan R. [UNESP]
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:22:39Z
dc.date.available2014-05-27T11:22:39Z
dc.date.issued2007-12-01
dc.description.abstractMotivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.en
dc.description.affiliationState University of Campinas UNICAMP/FEM/DEP, CP.6122, Campinas, SP 13083-970
dc.description.affiliationSão Paulo State University UNESP/IGCE/DEMAC, Avenida 24-A, 1515, CP. 178, Rio Claro, SP 13506-700
dc.description.affiliationUnespSão Paulo State University UNESP/IGCE/DEMAC, Avenida 24-A, 1515, CP. 178, Rio Claro, SP 13506-700
dc.identifierhttp://dx.doi.org/10.1109/CIMCA.2006.8
dc.identifier.citationCIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies ....
dc.identifier.doi10.1109/CIMCA.2006.8
dc.identifier.lattes6997814343189860
dc.identifier.orcid0000-0001-9728-7092
dc.identifier.scopus2-s2.0-38849162361
dc.identifier.urihttp://hdl.handle.net/11449/70013
dc.language.isoeng
dc.relation.ispartofCIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies ...
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectGenetic algorithms
dc.subjectMathematical models
dc.subjectOil well drilling
dc.subjectProblem solving
dc.subjectRobust control
dc.subjectPerformance evaluators
dc.subjectRate of Penetration (ROP)
dc.subjectAdaptive control systems
dc.titleA genetic neuro-model reference adaptive controller for petroleum wells drilling operationsen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dspace.entity.typePublication
unesp.author.lattes6997814343189860[3]
unesp.author.orcid0000-0001-9728-7092[3]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Geociências e Ciências Exatas, Rio Claropt
unesp.departmentEstatística, Matemática Aplicada e Computação - IGCEpt

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