Geophysical model generation with generative adversarial networks

Geophysical model generation with generative adversarial networks

Abstract With the rapid development of deep learning technologies, data-driven methods have become one of the main research focuses in geophysical inversion. Applications of various neural network architectures to the inversion of seismic, electromagnetic, gravity and other types of data confirm the...

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Bibliographic Details
Main Authors: Vladimir Puzyrev, Tristan Salles, Greg Surma, Chris Elders
Format: Article
Language:English
Published: SpringerOpen 2022-08-01
Series:Geoscience Letters
Subjects:
Convolutional neural network
Generative adversarial network
Deep learning
Inverse problem
Online Access:https://doi.org/10.1186/s40562-022-00241-y

Internet

https://doi.org/10.1186/s40562-022-00241-y

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