Efficient frequency-domain reflection-based full waveform inversion using wavefield separation

Title
Efficient frequency-domain reflection-based full waveform inversion using wavefield separation
Author(s)
Jun, Hyunggu
KIOST Author(s)
Jun, Hyunggu(전형구)
Publication Year
2019-10-16
Abstract
Full waveform inversion (FWI) is a suitable algorithm to invert the subsurface velocity with high accuracy. The low frequency components and long offset seismic data are necessary for the FWI to invert the long wavelength velocity. To invert the long wavelength velocity from the reflection-dominant short offset seismic data, the reflection-based full waveform inversion (RFWI) which decomposed the gradient of the FWI into high and low wavenumber components was introduced. However, the conventional RFWI still contained the high wavenumber components which were generated between the primary wavefield and the scattered wavefield. Moreover, the true amplitude migration which needed additional computation was necessary. In this study, the new frequency-domain RFWI algorithm is introduced to overcome the drawbacks of the conventional RFWI. The new RFWI algorithm uses the up/down-going wavefield separation to remove the high wavenumber component and the two-step approach to enhance the computational efficiency. The effectiveness of the proposed algorithm is verified by the synthetic numerical test using short-offset Marmousi seismic data. © 2018 SEG.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/22250
Bibliographic Citation
88th Society of Exploration Geophysicists International Exposition and Annual Meeting, pp.1118 - 1122, 2019
Publisher
Society of Exploration Geophysicists
Type
Conference
Language
English
Publisher
Society of Exploration Geophysicists
Related Researcher
Research Interests

Seismic data processing,Exploration geophysics,Machine learning,탄성파 자료처리,물리탐사,머신러닝

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