A cyclic learning approach for improving pre-stack seismic processing

Current seismic processing workflows in the oil and gas industry involve several interactions between different experts to optimize the overall data quality in various tasks, such as noise attenuation, velocity analysis and horizon picking. While many machine learning-based approaches have been prop...

Descripción completa

Detalles Bibliográficos
Autores principales: Borges Oliveira, Dario Augusto, Szwarcman, Daniela, da Silva Ferreira, Rodrigo, Zaytsev, Semen, Semin, Daniil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060324/
https://www.ncbi.nlm.nih.gov/pubmed/33883586
http://dx.doi.org/10.1038/s41598-021-87794-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8060324/
https://www.ncbi.nlm.nih.gov/pubmed/33883586
http://dx.doi.org/10.1038/s41598-021-87794-8

Ejemplares similares