High-frequency wavefield extrapolation using the Fourier neural operator
File(s)
Published version
Author(s)
Song, Chao
Wang, Yanghua
Type
Journal Article
Abstract
In seismic wave simulation, solving the wave equation in the frequency domain requires calculating the inverse of the impedance matrix. The total cost strictly depends on the number of frequency components that are considered, if using a finite-difference method. For the applications such as seismic imaging and inversion, high-frequency information is always required and thus the wave simulation is always a challenging task as it demands tremendous computational cost for obtaining dispersion-free high-frequency wavefields for large subsurface models. This paper demonstrates that a data-driven machine learning method, called the Fourier neural operator (FNO), is capable of predicting high-frequency wavefields, based on a limited number of low-frequency components. As the FNO method is for the first time applied to seismic wavefield extrapolation, the experiment reveals three attractive features with FNO: high efficiency, high accuracy and, importantly, the predicted high-frequency wavefields are dispersion free.
Date Issued
2022-04-30
Date Acceptance
2022-03-12
Citation
Journal of Geophysics and Engineering, 2022, 19 (2), pp.269-282
ISSN
1742-2132
Publisher
Oxford University Press
Start Page
269
End Page
282
Journal / Book Title
Journal of Geophysics and Engineering
Volume
19
Issue
2
Copyright Statement
© The Author(s) 2022. Published by Oxford University Press on behalf of the Sinopec Geophysical Research Institute.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
License URL
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000789030400004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Physical Sciences
Geochemistry & Geophysics
dispersion free
Fourier neural operator
high-frequency wavefield
machine learning
wavefield extrapolation
FINITE-DIFFERENCE
FORM INVERSION
FRAMEWORK
Publication Status
Published