2019-08-192019-08-192015-10-26ROSELLÓN GUZMAN, Laura Yesenia. Cálculo de porosidade com a rede neural competitiva. Orientador: André José Neves Andrade. 2015. 64 f. Dissertação (Mestrado em Geofísica) - Instituto de Geociências, Universidade Federal do Pará, Belém, 2015. Disponível em: http://repositorio.ufpa.br/jspui/handle/2011/11461. Acesso em:.https://repositorio.ufpa.br/handle/2011/11461Porosity is the petrophysical property that quantifies the fluid volume in the reservoir rock under for subsurface original condition. However, its calculation by the densityneutron method is extremely difficult in non cored borehole by the lack of the knowledge about the matrix physical properties (density and neutron porosity). This work presents a method for enabling the use of density-neutron Method in non cored boreholes, showing a realistic estimate of the matrix physical properties for each reservoir layer, using a angular competitive neural network. For each layer, network training is performed in the density-neutron plot built with the points of this layer and the information about the grain density (matrix density), obtained in the core analysis. This method is presented with synthetic data, which satisfy the petrophysical model and real data from two cored wells in the Namorado field, Campos basin.Acesso AbertoProspecção - Métodos geofísicosPerfilagem geofísica de poçosPorosidadeRedes neurais (Computação)Método densidade-neutrônicoRede neural competitiva angularPorosityDensity-neutron methodAngular competitive neural networkDissertaçãoCNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::GEOFISICAAPLICAÇÃO E DESENVOLVIMENTO DE ALGORITMOS INTELIGENTES AO ESTUDO DE RESERVATÓRIOS DE HIDROCARBONETOSGEOFÍSICA DE POÇO