dc.contributorFulco, Umberto Laino
dc.contributor
dc.contributorhttp://lattes.cnpq.br/3819069676836512
dc.contributor
dc.contributorhttp://lattes.cnpq.br/9579151361576173
dc.contributorCorso, Gilberto
dc.contributor
dc.contributorhttp://lattes.cnpq.br/0274040885278760
dc.contributorFulco, Paulo
dc.contributor
dc.contributorhttp://lattes.cnpq.br/8531312845628389
dc.contributorBarbosa, Paulo Henrique Ribeiro
dc.contributor
dc.contributorhttp://lattes.cnpq.br/1903813727934214
dc.creatorSilva, Francisco Wilton de Freitas
dc.date.accessioned2015-02-25
dc.date.accessioned2015-03-03T13:59:42Z
dc.date.accessioned2022-10-05T23:09:46Z
dc.date.available2015-02-25
dc.date.available2015-03-03T13:59:42Z
dc.date.available2022-10-05T23:09:46Z
dc.date.created2015-02-25
dc.date.created2015-03-03T13:59:42Z
dc.date.issued2009-05-22
dc.identifierSILVA, Francisco Wilton de Freitas. DFA e análise de agrupamento aplicadas a perfis de porosidade neutrônico em poçosm de petróleo. 2009. 99 f. Dissertação (Mestrado em Pesquisa e Desenvolvimento em Ciência e Engenharia de Petróleo) - Universidade Federal do Rio Grande do Norte, Natal, 2009.
dc.identifierhttps://repositorio.ufrn.br/jspui/handle/123456789/18534
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3948320
dc.description.abstractPeng was the first to work with the Technical DFA (Detrended Fluctuation Analysis), a tool capable of detecting auto-long-range correlation in time series with non-stationary. In this study, the technique of DFA is used to obtain the Hurst exponent (H) profile of the electric neutron porosity of the 52 oil wells in Namorado Field, located in the Campos Basin -Brazil. The purpose is to know if the Hurst exponent can be used to characterize spatial distribution of wells. Thus, we verify that the wells that have close values of H are spatially close together. In this work we used the method of hierarchical clustering and non-hierarchical clustering method (the k-mean method). Then compare the two methods to see which of the two provides the best result. From this, was the parameter � (index neighborhood) which checks whether a data set generated by the k- average method, or at random, so in fact spatial patterns. High values of � indicate that the data are aggregated, while low values of � indicate that the data are scattered (no spatial correlation). Using the Monte Carlo method showed that combined data show a random distribution of � below the empirical value. So the empirical evidence of H obtained from 52 wells are grouped geographically. By passing the data of standard curves with the results obtained by the k-mean, confirming that it is effective to correlate well in spatial distribution
dc.publisherUniversidade Federal do Rio Grande do Norte
dc.publisherBR
dc.publisherUFRN
dc.publisherPrograma de Pós-Graduação em Ciência e Engenharia do Petróleo
dc.publisherPesquisa e Desenvolvimento em Ciência e Engenharia de Petróleo
dc.rightsAcesso Aberto
dc.subjectCampo de Namorado
dc.subjectPetróleo
dc.subjectPorosidade Neutrônica
dc.subjectDFA
dc.subjectAnálise de Agrupamentos
dc.subjectCampo de Namorado
dc.subjectOil
dc.subjectNeutron Porosity
dc.subjectDFA
dc.subjectCluster analysis
dc.titleDFA e análise de agrupamento aplicadas a perfis de porosidade neutrônico em poços de petróleo
dc.typemasterThesis


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