A cyclic learning approach for improving pre-stack seismic processing

A cyclic learning approach for improving pre-stack seismic processing

Abstract 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...

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Autores principales: Dario Augusto Borges Oliveira, Daniela Szwarcman, Rodrigo da Silva Ferreira, Semen Zaytsev, Daniil Semin
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/3058d7ac66554cf2a714ebf9122e8ffb
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