An Improved Time-Frequency Analysis Method for Hydrocarbon Detection Based on EWT and SET

Hui Chen, Jiaxing Kang, Yuanchun Chen, Dan Xu and Ying Hu
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Hui Chen: Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China
Jiaxing Kang: Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China
Yuanchun Chen: Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China
Dan Xu: Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China
Ying Hu: Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, China

Energies, 2017, vol. 10, issue 8, 1-12

Abstract: Oil and gas reservoirs can cause increased attenuation of seismic waves, which can be revealed by time-frequency analysis for direct detection of hydrocarbons. In this paper, a new method applying the empirical wavelet transform (EWT) in association with the synchroextracting transform (SET), named EWT-SET, is proposed as an improved time-frequency analysis method for hydrocarbon detection. The SET is a novel time-frequency analysis method which can be considered as a post-processing procedure of short-time Fourier transform and can improve the energy concentration of the time-frequency representation by retaining only the time-frequency information most related to the signal time-varying features. Given the potential limitations of SET for broadband nonstationary seismic signals, using the EWT-SET method which applies SET to the signal after EWT decomposition, not only effectively extracts time-varying features of seismic signals but also improves the performance of SET in concentrating instantaneous energy. The preliminary model tests demonstrate that EWT-SET can effectively depict the location and extent of attenuation anomalies related to hydrocarbons with changing thicknesses of the gas-bearing layer. Application to field data further confirms the capacity for hydrocarbon detection of the presented method. Thus, the EWT-SET method shows significant application prospects and promotion value for hydrocarbon detection.

Keywords: hydrocarbon detection; time-frequency analysis; synchroextracting transform (SET); empirical wavelet transform (EWT) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
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