Applications of the synchrosqueezing transform in seismic time-frequency analysis

Herrera, Roberto; Han, Jianxun; Baan, Mirko van der

doi:10.1190/geo2013-0204.1

Cited by 155 publications

(65 citation statements)

References 24 publications

(49 reference statements)

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“…Different reassigned time-frequency distributions exist, such as for the Wigner-Ville distribution (Auger and Flandrin, 1995), the STFT (Auger et al, 2013), the CWT (Daubechies et al, 2011;Thakur et al, 2013), or the wave-packet transform (Yang, 2015). Here, we use the SST based on the CWT (Thakur et al, 2013;Herrera et al, 2014).…”

Section: The Sstmentioning

confidence: 98%

“…The high spectral localization of the SST results mainly from this reassignment step. The hard threshold on the CWT representation controls the number of time-frequency coefficients to reassign and hence the separation between signal and noise (Thakur et al, 2013;Herrera et al, 2014). We first define this threshold by dividing the maximum value of the CWT distribution W s ða; bÞ by a given value between 1.25 and 10, disregarding time-frequency coefficients with amplitudes lower than this value.…”

Section: The Sstmentioning

confidence: 99%

“…As a consequence, these compressed time-frequency representations drastically change the frequency bandwidth of a signal (for examples of such representations, see Herrera et al, 2014;Tary et al, 2014a). This would lead to unstable or biased measures of attenuation by the SR or the FS method.…”

Section: Introductionmentioning

confidence: 98%

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Applications of high-resolution time-frequency transforms to attenuation estimation

2017

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Attenuation estimates quantify the loss of energy of propagating seismic waves due to anelastic processes. It is often carried out in the frequency domain. The most well-known methods for attenuation estimation, such as the spectral ratio and frequencyshift methods, compare spectral shapes of waveforms along a given raypath. They require broad spectra such as those obtained with the Fourier transform and the continuous wavelet transform. These methods are incompatible with high-resolution time-frequency transforms, which drastically localize timefrequency information. On the other hand, these transforms indicate stronger resistance to noise and can be used in combination with the peak frequency method to estimate attenuation. We have applied high-resolution transforms, namely the synchrosqueezing transform, basis pursuit, and complete ensemble empirical-mode decomposition, to a synthetic wedge example and two seismic data set examples, a seismic reflection profile, and a vertical seismic profile (VSP). Results for the synthetic example find that most high-resolution transforms are able to reliably estimate quality factors. Using centroid frequencies, the seismic reflection profile exhibits local increases in centroid frequencies, which likely indicates imprints from apparent attenuation over intrinsic attenuation. Centroid frequencies and effective quality factors for the VSP are consistent for the different spectral estimation techniques. These three examples illustrate the value of high-resolution transforms for frequency and quality factor measurements.

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Section: The Sstmentioning

confidence: 98%

Section: The Sstmentioning

confidence: 99%

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Applications of high-resolution time-frequency transforms to attenuation estimation

2017

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“…Subsequently, many efforts have been made to use this method for seismic data processing and interpretation. In 2014, Herrera et al [25] identified channels from seismic data using SST successfully and highlighted the advantages of this method over EMD and EEMD. In 2015, they also used SST to separate the P and S waves of microseismic data [26].…”

Section: Introductionmentioning

confidence: 99%

The Synchrosqueezing Algorithm Based on Generalized S-transform for High-Precision Time-Frequency Analysis

Chen

et al. 2017

Applied Sciences

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Abstract:In this paper, a new time-frequency analysis method-Synchrosqueezing Generalized S-transform (SSGST)-is proposed to meet the needs of high-resolution seismic signal processing and interpretation. The basic wavelet of the generalized S-transform (GST) in the paper is a modulated harmonic wave with four undetermined parameters that can be constructed by adjusting the four parameters to make the GST more suitable for seismic signals processing. The SSGST method squeezes and reconstructs the complex coefficient spectra of GST results along the frequency direction so that the energy distributions on the time-frequency spectra are concentrated around the real instantaneous frequency of the signal; thus, the time-frequency resolution can be improved. Based on mathematical theory, the basic principle of the new transformation method is given, and the mathematical expressions of the positive transformation and lossless inverse transformation of the method are strictly deduced. The experimental results of numerical signals illustrate that the proposed method can correctly decompose signals with different spectral characteristics into a high time-frequency resolution spectrum and can recovery the original signal from the time-frequency spectrum with satisfying reconstructing accuracy. Application on field seismic data shows the superiority of the new method in seismic time-frequency analysis for hydrocarbon detection.

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“…More recently, some methods have been proposed to improve time-frequency resolution. These methods can be mainly classified as: (1) methods based on signal decomposition techniques, such as empirical mode decomposition (EMD) in combination with instantaneous frequency [18][19][20][21]; or (2) methods based on the combination of time-frequency methods followed by a reassignment step, such as synchrosqueezed wavelet transforms (SST) [22][23][24].…”

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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Applications of the synchrosqueezing transform in seismic time-frequency analysis

Cited by 155 publications

References 24 publications

Applications of high-resolution time-frequency transforms to attenuation estimation

Applications of high-resolution time-frequency transforms to attenuation estimation

The Synchrosqueezing Algorithm Based on Generalized S-transform for High-Precision Time-Frequency Analysis

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

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