Learning-Based Seismic Velocity Inversion with Synthetic and Field Data

Learning-Based Seismic Velocity Inversion with Synthetic and Field Data

Building accurate acoustic subsurface velocity models is essential for successful industrial exploration projects. Traditional inversion methods from field-recorded seismograms struggle in regions with complex geology. While deep learning (DL) presents a promising alternative, its robustness using f...

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Bibliographic Details
Main Authors: Stuart Farris, Robert Clapp, Mauricio Araya-Polo
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Sensors
Subjects:
field data
deep learning
synthetic training data
seismic propagation velocity
inverse problems
Online Access:https://www.mdpi.com/1424-8220/23/19/8277

Internet

https://www.mdpi.com/1424-8220/23/19/8277

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