Topological study of reservoir rocks and acidification processes using complex networks methods

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Andreeta, Mariane Barsi
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.teses.usp.br/teses/disponiveis/76/76132/tde-30012018-154357/
Resumo: The X-Ray imaging technology opened a new branch of science in which the internal porous structure can be captured and the reconstructed volume can be used for fluid flow simulations and structural measurements. However, there is still the question of how the internal structure of the pore space impacts in the observed simulations. A way to characterize this internal structure is by simplifying it into well-defined elements and the interaction between them, describing it as a network. The interaction between elements are the edges of the network and elements are the nodes. This opens the possibility of applying complex network theory on the characterization of porous media which has proven to give powerful insights into how the structure of porous materials influences on the dynamics of the permeating fluid. The problem with this description is in definition of the basic elements that will compose the network, since there isnt a consensus on this definition. The purpose of this work is to provide a method to analyze μCT data through networks in which the separation of the space is done in a semi-continuous method. The recovering of the pores local geometry is captured through a network analysis method of centrality, instead of a geometrical definition. This way the intrinsic morphology of the samples is what governs the pore-space separation into different entities. The method developed is based on the network extraction method Max Spheres Algorithm (MSA). The volumetric data is recovered through a network composed by sphere cells. The output of this process are two distinct networks: the complete volume network and a network which represents the variation of the channels diameter. These networks give unbiased real information on pore connectivity and can provide important data to better understand the morphology and topology of the samples. This method was successfully applied to samples of Berea sandstone, Estaillades carbonate, and to characterize the morphology of wormholes. Wormhole is the denomination of the channel formed after the application of an acid treatment as a stimulation procedure of an oil reservoir, a method of EOR (Enhanced oil recovery). This treatment consists of a reactive fluid flow injected in the inner rock of the reservoir, which creates a preferential path (wormhole) that optimizes the extraction of the hydrocarbon fluids.