Extrapolated full-waveform inversion (EFWI) with synthesized low-frequency data

The availability of low frequency data is an important factor in the success of full waveform inversion (FWI) in the acoustic regime. The low frequencies help determine the kinematically relevant, low-wavenumber components of the velocity model, which are in turn needed to avoid convergence of FWI t...

Full description

Bibliographic Details
Main Authors: Li, Yunyue, Demanet, Laurent
Other Authors: Massachusetts Institute of Technology. Department of Mathematics
Format: Article
Published: Society of Exploration Geophysicists 2018
Online Access:http://hdl.handle.net/1721.1/116244
https://orcid.org/0000-0003-4225-2735
https://orcid.org/0000-0001-7052-5097
_version_ 1811097909016395776
author Li, Yunyue
Demanet, Laurent
author2 Massachusetts Institute of Technology. Department of Mathematics
author_facet Massachusetts Institute of Technology. Department of Mathematics
Li, Yunyue
Demanet, Laurent
author_sort Li, Yunyue
collection MIT
description The availability of low frequency data is an important factor in the success of full waveform inversion (FWI) in the acoustic regime. The low frequencies help determine the kinematically relevant, low-wavenumber components of the velocity model, which are in turn needed to avoid convergence of FWI to spurious local minima. However, acquiring data below 2 or 3 Hz from the field is a challenging and expensive task. In this paper we explore the possibility of synthesizing the low frequencies computationally from high-frequency data, and use the resulting prediction of the missing data to seed the frequency sweep of FWI. To demonstrate the reliability of bandwidth extension in the context of FWI, we first use the low frequencies in the extrapolated band as data substitute, in order to create the low-wavenumber background velocity model, and then switch to recorded data in the available band for the rest of the iterations. The resulting method, extrapolated FWI (EFWI), demonstrates surprising robustness to the inaccuracies in the extrapolated low frequency data. With a synthetic Marmousi model, we demonstrate that FWI based on an extrapolated [1,5] Hz band, itself generated from data available in the [5,15] Hz band, can produce reasonable estimations of the low wavenumber velocity models.
first_indexed 2024-09-23T17:06:53Z
format Article
id mit-1721.1/116244
institution Massachusetts Institute of Technology
last_indexed 2024-09-23T17:06:53Z
publishDate 2018
publisher Society of Exploration Geophysicists
record_format dspace
spelling mit-1721.1/1162442022-10-03T10:31:59Z Extrapolated full-waveform inversion (EFWI) with synthesized low-frequency data Li, Yunyue Demanet, Laurent Massachusetts Institute of Technology. Department of Mathematics Li, Yunyue Demanet, Laurent The availability of low frequency data is an important factor in the success of full waveform inversion (FWI) in the acoustic regime. The low frequencies help determine the kinematically relevant, low-wavenumber components of the velocity model, which are in turn needed to avoid convergence of FWI to spurious local minima. However, acquiring data below 2 or 3 Hz from the field is a challenging and expensive task. In this paper we explore the possibility of synthesizing the low frequencies computationally from high-frequency data, and use the resulting prediction of the missing data to seed the frequency sweep of FWI. To demonstrate the reliability of bandwidth extension in the context of FWI, we first use the low frequencies in the extrapolated band as data substitute, in order to create the low-wavenumber background velocity model, and then switch to recorded data in the available band for the rest of the iterations. The resulting method, extrapolated FWI (EFWI), demonstrates surprising robustness to the inaccuracies in the extrapolated low frequency data. With a synthetic Marmousi model, we demonstrate that FWI based on an extrapolated [1,5] Hz band, itself generated from data available in the [5,15] Hz band, can produce reasonable estimations of the low wavenumber velocity models. 2018-06-12T14:34:40Z 2018-06-12T14:34:40Z 2016-10 2018-05-17T17:23:06Z Article http://purl.org/eprint/type/ConferencePaper 1949-4645 http://hdl.handle.net/1721.1/116244 Li, Yunyue, and Laurent Demanet. "Extrapolated Full-Waveform Inversion (EFWI) with Synthesized Low-Frequency Data." SEG Technical Program Expanded Abstracts 2016, pp. 1352–57. https://orcid.org/0000-0003-4225-2735 https://orcid.org/0000-0001-7052-5097 http://dx.doi.org/10.1190/SEGAM2016-13844498.1 SEG Technical Program Expanded Abstracts 2016 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Society of Exploration Geophysicists MIT Web Domain
spellingShingle Li, Yunyue
Demanet, Laurent
Extrapolated full-waveform inversion (EFWI) with synthesized low-frequency data
title Extrapolated full-waveform inversion (EFWI) with synthesized low-frequency data
title_full Extrapolated full-waveform inversion (EFWI) with synthesized low-frequency data
title_fullStr Extrapolated full-waveform inversion (EFWI) with synthesized low-frequency data
title_full_unstemmed Extrapolated full-waveform inversion (EFWI) with synthesized low-frequency data
title_short Extrapolated full-waveform inversion (EFWI) with synthesized low-frequency data
title_sort extrapolated full waveform inversion efwi with synthesized low frequency data
url http://hdl.handle.net/1721.1/116244
https://orcid.org/0000-0003-4225-2735
https://orcid.org/0000-0001-7052-5097
work_keys_str_mv AT liyunyue extrapolatedfullwaveforminversionefwiwithsynthesizedlowfrequencydata
AT demanetlaurent extrapolatedfullwaveforminversionefwiwithsynthesizedlowfrequencydata