Convolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade Estadual de Campinas (UNICAMP)-
Autor(es): dc.contributorDevelopment and Innovation Center (Cenpes)-
Autor(es): dc.creatorRoder, Mateus-
Autor(es): dc.creatorPassos, Leandro Aparecido-
Autor(es): dc.creatorPereira, Clayton-
Autor(es): dc.creatorPapa, João Paulo-
Autor(es): dc.creatorde Mello, Altanir Flores-
Autor(es): dc.creatorde Rezende, Marcelo Fagundes-
Autor(es): dc.creatorSilva, Yaro Moisés Parizek-
Autor(es): dc.creatorVidal, Alexandre-
Data de aceite: dc.date.accessioned2025-08-21T18:19:58Z-
Data de disponibilização: dc.date.available2025-08-21T18:19:58Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.5220/0012429100003660-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/308675-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/308675-
Descrição: dc.descriptionLithological classification is a process employed to recognize and interpret distinct structures of rocks, providing essential information regarding their petrophysical, morphological, textural, and geological aspects. The process is particularly interesting regarding carbonate sedimentary rocks in the context of petroleum basins since such rocks can store large quantities of natural gas and oil. Thus, their features are intrinsically correlated with the production potential of an oil reservoir. This paper proposes an automatic pipeline for the lithological classification of carbonate rocks into seven distinct classes, comparing nine state-of-the-art deep learning architectures. As far as we know, this is the largest study in the field. Experiments were performed over a private dataset obtained from a Brazilian petroleum company, showing that MobileNetV3large is the more suitable approach for the undertaking.-
Descrição: dc.descriptionDepartment of Computing São Paulo State University (UNESP)-
Descrição: dc.descriptionInstitute of Geosciences Campinas State University (UNICAMP)-
Descrição: dc.descriptionResearch Center Leopoldo Americo Miguez de Mello Research Development and Innovation Center (Cenpes)-
Descrição: dc.descriptionDepartment of Computing São Paulo State University (UNESP)-
Formato: dc.format648-655-
Idioma: dc.languageen-
Relação: dc.relationProceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectConvolutional Neural Networks-
Palavras-chave: dc.subjectLithological Classification-
Palavras-chave: dc.subjectPre-Salt Rocks-
Título: dc.titleConvolutional Neural Networks and Image Patches for Lithological Classification of Brazilian Pre-Salt Rocks-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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