Imperial College London
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ProfessorMikeWarner

Faculty of Engineering, Department of Earth Science & Engineering

Professor
 
 
 
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Contact

 

+44 (0)20 7594 6535m.warner

 
 
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Assistant

 

Ms Daphne Salazar +44 (0)20 7594 7401

 
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Location

 

RSM 1.46CRoyal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Yao:2019:10.3997/2214-4609.201901969,
author = {Yao, J and Guasch, L and Warner, M and Davies, D and Wild, A},
doi = {10.3997/2214-4609.201901969},
title = {Removing elastic effects in FWI using supervised cycled generative adversarial networks},
url = {http://dx.doi.org/10.3997/2214-4609.201901969},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - © 81st EAGE Conference and Exhibition 2019 Workshop Programme. All rights reserved. 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.
AU  - Yao,J
AU  - Guasch,L
AU  - Warner,M
AU  - Davies,D
AU  - Wild,A
DO  - 10.3997/2214-4609.201901969
PY  - 2019///
TI  - Removing elastic effects in FWI using supervised cycled generative adversarial networks
UR  - http://dx.doi.org/10.3997/2214-4609.201901969
ER  -
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