High-precision frequency attenuation analysis and its application

Xiong, Xiang; He, Xin; Pu, Yong; He, Zhenhua; Kai, Lin

doi:10.1007/s11770-011-0302-4

Cited by 18 publications

(11 citation statements)

References 6 publications

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“…The phenomenon of abnormal attenuation mainly shows the loss of high-frequency energy and the conservation of strong low-frequency energy (e.g., [33][34][35][36][37]). Spectral decomposition technology can be utilized to identify hydrocarbon reservoirs by analyzing the different frequency response characteristics among different scale geological bodies (e.g., [38]).…”

Section: Field Data Examplesmentioning

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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Section: Field Data Examplesmentioning

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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“…When seismic signals propagate through hydrocarbon reservoirs, waves induced by fluid flow are the main causation of attenuation of energy and frequency. The characteristics of the loss of high-frequency energy and the conservation of strong low-frequency energy resulting from the above mention that attenuation can be found in different frequency data, which have been successfully applied for reservoir characterization and hydrocarbon detection by many scholars [31][32][33][34]. Time-frequency analysis is an important tool for revealing the variation of signals in both the time and frequency domains.…”

Section: Ewt-set As a Hydrocarbon Detection Toolmentioning

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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“…Seismic attenuation is usually separated into attenuation connected to scattering effects and attenuation corresponding to stratigraphic absorption [7,8]. Subsurface rocks usually form a porous medium filled with fluid [9]. Waves induced by fluid flow can lead to stratum absorption, which is the main causation of attenuation of seismic waves [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…Waves induced by fluid flow can lead to stratum absorption, which is the main causation of attenuation of seismic waves [10,11]. When seismic waves propagate through reservoirs, high-frequency energy waves decay more rapidly than low-frequency waves, which may lead to high-frequency energy loss and only conserve strong low-frequency energy [9,[12][13][14]. Some theoretical and practical studies have been carried out to verify this phenomenon by many scholars [9,[15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…When seismic waves propagate through reservoirs, high-frequency energy waves decay more rapidly than low-frequency waves, which may lead to high-frequency energy loss and only conserve strong low-frequency energy [9,[12][13][14]. Some theoretical and practical studies have been carried out to verify this phenomenon by many scholars [9,[15][16][17][18]. There are two main methods for revealing seismic attenuation associated with hydrocarbons, which can be classified as: (1) methods based on low-frequency information, such as low-frequency shadow analysis [18,19] as well as the method of observing the difference between high-frequency and low-frequency energy [20,21]; and…”

Section: Introductionmentioning

confidence: 99%

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High-Precision Spectral Decomposition Method Based on VMD/CWT/FWEO for Hydrocarbon Detection in Tight Sandstone Gas Reservoirs

Chen

Zhou

et al. 2017

Energies

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Seismic time-frequency analysis methods can be used for hydrocarbon detection because of the phenomena of energy and abnormal attenuation of frequency when the seismic waves travel across reservoirs. A high-resolution method based on variational mode decomposition (VMD), continuous-wavelet transform (CWT) and frequency-weighted energy operator (FWEO) is proposed for hydrocarbon detection in tight sandstone gas reservoirs. VMD can decompose seismic signals into a set of intrinsic mode functions (IMF) in the frequency domain. In order to avoid meaningful frequency loss, the CWT method is used to obtain the time-frequency spectra of the selected IMFs. The energy separation algorithm based on FWEO can improve the resolution of time-frequency spectra and highlight abnormal energy, which is applied to track the instantaneous energy in the time-frequency spectra. The difference between the high-frequency section and low-frequency section acquired by applying the proposed method is utilized to detect hydrocarbons. Applications using the model and field data further demonstrate that the proposed method can effectively detect hydrocarbons in tight sandstone reservoirs, with good anti-noise performance. The newly-proposed method can be used as an analysis tool to detect hydrocarbons.

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High-precision frequency attenuation analysis and its application

Cited by 18 publications

References 6 publications

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

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

High-Precision Spectral Decomposition Method Based on VMD/CWT/FWEO for Hydrocarbon Detection in Tight Sandstone Gas Reservoirs

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