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Removing Elastic Effects in FWI Using Supervised Cycled Generative Adversarial Networks
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 81st EAGE Conference and Exhibition 2019 Workshop Programme, Jun 2019, Volume 2019, p.1 - 5
Abstract
Summary
We use a CycleGAN to map acoustic synthetic data to elastic data, and to map elastic field data to acoustic data, and use the resulting data to perform acoustic FWI on a 3D field dataset that shows strong elastic effects at top chalk. Using machine learning to change the effective physics of field data has many other potential applications.
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