Subjects: CARBONATOS, RESERVATÓRIOS, APRENDIZADO COMPUTACIONAL, INJEÇÃO (ENGENHARIA)
ABNT
REGINATO, Leonardo Fonseca. Application of machine learning techniques for modeling of relative permeability in engineered water injection in carbonate reservoirs. 2022. Dissertação (Mestrado) – Universidade de São Paulo, São Paulo, 2022. Disponível em: https://www.teses.usp.br/teses/disponiveis/3/3134/tde-26082022-083727/. Acesso em: 22 maio 2024.APA
Reginato, L. F. (2022). Application of machine learning techniques for modeling of relative permeability in engineered water injection in carbonate reservoirs (Dissertação (Mestrado). Universidade de São Paulo, São Paulo. Recuperado de https://www.teses.usp.br/teses/disponiveis/3/3134/tde-26082022-083727/NLM
Reginato LF. Application of machine learning techniques for modeling of relative permeability in engineered water injection in carbonate reservoirs [Internet]. 2022 ;[citado 2024 maio 22 ] Available from: https://www.teses.usp.br/teses/disponiveis/3/3134/tde-26082022-083727/Vancouver
Reginato LF. Application of machine learning techniques for modeling of relative permeability in engineered water injection in carbonate reservoirs [Internet]. 2022 ;[citado 2024 maio 22 ] Available from: https://www.teses.usp.br/teses/disponiveis/3/3134/tde-26082022-083727/