A case study of petrophysical rock typing and permeability prediction using machine learning in a heterogenous carbonate reservoir in Iran

Petrophysical rock typing (PRT) and permeability prediction are of great significance for various disciplines of oil and gas industry. This study offers a novel, explainable data-driven approach to enhance the accuracy of petrophysical rock typing via a combination of supervised and unsupervised mac...

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Detalles Bibliográficos
Autores principales: Mohammadian, Erfan, Kheirollahi, Mahdi, Liu, Bo, Ostadhassan, Mehdi, Sabet, Maziyar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8927145/
https://www.ncbi.nlm.nih.gov/pubmed/35296761
http://dx.doi.org/10.1038/s41598-022-08575-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8927145/
https://www.ncbi.nlm.nih.gov/pubmed/35296761
http://dx.doi.org/10.1038/s41598-022-08575-5

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