• Corpus ID: 230437497

Deep learning for low frequency extrapolation of multicomponent data in elastic full waveform inversion

@inproceedings{Sun2020DeepLF,
  title={Deep learning for low frequency extrapolation of multicomponent data in elastic full waveform inversion},
  author={Hongyu Sun and Laurent Demanet},
  year={2020}
}
Full waveform inversion (FWI) strongly depends on an accurate starting model to succeed. This is particularly true in the elastic regime: The cycle-skipping phenomenon is more severe in elastic FWI compared to acoustic FWI, due to the short S-wave wave-length. In this paper, we extend our work on extrapolated FWI (EFWI) by proposing to synthesize the low frequencies of multi-component elastic seismic records, and use those “artificial” low frequencies to seed the frequency sweep of elastic FWI… 

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