High-Order Synchroextracting Time-Frequency Analysis and Its Application in Seismic Hydrocarbon Reservoir Identification

Time-frequency (TF) analysis (TFA) plays an important role in seismic hydrocarbon reservoir identification, which is attributed to its ability to effectively identify the oil and gas seismic response characteristics of geological bodies in different frequency bands. In this letter, we introduce a no...

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Bibliographic Details
Published in:IEEE geoscience and remote sensing letters Vol. 18; no. 11; pp. 2011 - 2015
Main Authors: Chen, Xuping, Chen, Hui, Fang, Yuxia, Hu, Ying
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Fourier analysis
Fourier transforms
Frequencies
Frequency analysis
Frequency dependence
Geology
High-order synchroextracting
Hydrocarbon reservoirs
Hydrocarbons
Identification
Mathematical model
Oil reservoirs
Oils
Reservoirs
Seismic activity
Seismic data
seismic hydrocarbon reservoir identification
Seismic response
Seismological data
synchroextracting operator (SEO)
Time-frequency analysis
time–frequency analysis (TFA)
Transforms
ISSN:1545-598X, 1558-0571
Online Access:Get full text
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Summary:Time-frequency (TF) analysis (TFA) plays an important role in seismic hydrocarbon reservoir identification, which is attributed to its ability to effectively identify the oil and gas seismic response characteristics of geological bodies in different frequency bands. In this letter, we introduce a novel TFA method termed high-order synchroextracting transform (SET) and apply it to the high-precision identification of gas-bearing reservoirs. Under the premise of short-time Fourier transform (STFT), this method defines a new synchroextracting operator (SEO) based on high-order approximations of signal amplitude and phase. Furthermore, only the TF information highly correlated with the TF characteristics of the signal is extracted from the STFT spectrum by using the SEO. Therefore, for a wider variety of the nonstationary signal, a highly energy-concentrated TF representation can be effectively obtained. The application of STFT and different-order SET on 1-D synthetic signal and field seismic data verifies the effectiveness of the proposed method.
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ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2020.3009259