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Time-frequency analysis of seismic data for the characterization of geologic structures via synchro-extracting transform

ZHEN LI1,2 ,  JINGHUAI GAO1,2 ,  ZHIGUO WANG2,3 ,  NAIHAO LIU1,2 ,  FENGYUAN SUN1,2
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1 School of Information and Communications Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, P.R. China.,
2 National Engineering Laboratory for Offshore Oil Exploration, Xi’an, Shaanxi 710049, P.R. China.,
3 School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, P.R. China.,
JSE 2021, 30(2), 101–120;
Submitted: 3 December 2018 | Accepted: 20 March 2020 | Published: 1 April 2021
© 2021 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Li, Z., Gao, J.H., Wang, Z.G., Liu, N.H. and Sun, F.Y., 2020. Time-frequency analysis of seismic data for the characterization of geologic structures via synchroextracting transform. Journal of Seismic Exploration, 30: 101-120. Time-frequency (TF) analysis based method is one of the most powerful tools in seismic data processing and interpretation. To delineate the subsurface geological structures clearly, the energy concentration of the seismic TF representation (TFR) is as high as possible. The traditional TF methods, such as the short-time Fourier transform (STFT) and wavelet transform (WT), have been widely applied for seismic TF analysis. However, they suffer from the diffused TFR because of the Heisenberg uncertainty principle. To achieve a higher energy-concentrated TF result, the synchrosqueezing transform (SST) was proposed. The SST method has been successfully used for seismic processing. In this paper, we introduce a novel approach for seismic spectrum analysis based on the synchroextracting transform (SET), which is an extension of the Fourier-based SST (FSST). The SET extracts the TF information only located at the instantaneous frequency (IF) trajectory of the analyzed signal and removes the most smeared TF energy, which leads to a highly sharpened TFR. We also put forward a theorem to prove that the SET can get the exact IF of a linear chirp signal. All the results of the synthetic signal and real seismic data demonstrate the validity and effectiveness of the proposed method.

Keywords
time-frequency analysis
seismic data processing
high energy-concentrated
synchroextracting transform
Fourier-based synchrosqueezing transform.
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Journal of Seismic Exploration, Print ISSN: 0963-0651, Published by AccScience Publishing
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