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A novel high-precision spectral decomposition method based on second-order synchrosqueezing transform and its application

ZHIWEI GUO,  SIYUAN CAO
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State Key Laboratory of Petroleum Resources and Engineering, CNPC Key Laboratory of Geophysical Exploration, China University of Petroleum (Beijing), 18 Fuxue Road, Changping, Beijing 102249, P.R. China,
JSE 2020, 29(2), 159–172;
Submitted: 13 December 2018 | Accepted: 20 December 2019 | Published: 1 April 2020
© 2020 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

Guo, Z.W. and Cao, S.Y., 2020. A novel high-precision spectral decomposition method based on second-order synchrosqueezing transform and its application. Journal of Seismic Exploration: 29, 159-172. Spectral decomposition plays a central role in characterizing multicomponent signals, as for instance seismic signal, because it can reveals lots of valuable information hidden in the broadband seismic response. This paper presents a new methodology for seismic spectral decomposition via second-order synchrosqueezing transform. Second-order synchrosqueezing transform, which relies on a second-order local estimate of the instantaneous frequency, can provide a sharpened time-frequency representation while allowing for the separation and the reconstruction of the modes. We validate our method by means of a synthetic model and compare with the conventional spectral decomposition algorithms. Two field examples are employed to illustrate that the seismic attributes delineation using the second-order synchrosqueezing transform based method gives a better reflection of hydrocarbon-saturated reservoirs and stratigraphic characteristics.

Keywords
spectral decomposition
second-order synchrosqueezing transform
seismic signal
hydrocarbon detection
stratigraphic characteristics
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Journal of Seismic Exploration, Electronic ISSN: 0963-0651 Print ISSN: 0963-0651, Published by AccScience Publishing
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