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Estatística
Título: A NON-DETERMINISTIC PORE-THROAT NETWORK EXTRACTION FROM SKELETON BY THINNING ALGORITHM
Autor: TAMIRES PEREIRA PINTO DA SILVA
Colaborador(es): SINESIO PESCO - Orientador
ABELARDO BORGES BARRETO JR - Coorientador
Catalogação: 31/OUT/2023 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=64552&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=64552&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.64552
Resumo:
Computerized microtomography of a rock sample enables a characterization of the porous medium and can be used to estimate rock properties at the macro-scale, i.e., reservoir-scale. Methods based on distance maps and thinning algorithms are the main approaches used for extracting a pore and throats network from microtomographic rock images. This paper proposes a hybrid method for constructing the network. So that during the pore-scale modeling process, we obtain a skeleton of the pore space by using a thinning algorithm and a distance map to build a network of pores and throats. The determination of pores and throats from the skeleton assumes a non-deterministic approach enabling the generation of multiple networks with distinct configurations from the same skeleton. We evaluate the variability of the generated scenarios and compare the estimates for the petrophysical properties with those obtained by the Maximum Ball Method through the results of a single-phase flow simulation on the network.
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