Reassigned wavelet spectral decomposition and its application in hydrocarbon detection

Liu, Chuncheng; Han, Miao; Chen, Baoshu; Han, Liguo; Shang, Shuo

doi:10.1190/segam2013-0913.1

Cited by 5 publications

(1 citation statement)

References 8 publications

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“…Therefore, it is necessary to find reliable methods, which can use seismic data directly for hydrocarbon detections in unconventional reservoirs. Time-frequency analysis can reveal the distribution of signal energy or strength in both time and frequency domains, which has played a significant role in seismic data processing and interpretation, such as reservoir characterization [6][7][8][9] and hydrocarbon detection [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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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.

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