Coherence based on spectral variance analysis

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. O55-O66 ◽  
Author(s):  
Yanting Duan ◽  
Chaodong Wu ◽  
Xiaodong Zheng ◽  
Yucheng Huang ◽  
Jian Ma
Keyword(s):  
Fourier Transform ◽  
Seismic Data ◽  
High Frequency ◽  
Seismic Interpretation ◽  
Variance Analysis ◽  
Frequency Spectra ◽  
Amplitude Spectra ◽  
Frequency Components ◽  
Spectral Variance ◽  
Coherence Estimation

The eigenstructure-based coherence attribute is a type of efficient and mature tool for mapping geologic edges such as faults and/or channels in the 3D seismic interpretation. However, the eigenstructure-based coherence algorithm is sensitive to low signal-to-noise ratio seismic data, and the coherence results are affected by the dipping structures. Due to the large energy gap between the low- and high-frequency components, the low-frequency components play the principal role in coherence estimation. In contrast, the spectral variance balances the difference between the low- and high-frequency components at a fixed depth. The coherence estimation based on amplitude spectra avoids the effect of the time delays resulting from the dipping structures. Combining the spectral variance with the amplitude spectra avoids the effect of dipping structures and enhances the antinoise performance of the high-frequency components. First, we apply the short-time Fourier transform to obtain the time-frequency spectra of seismic data. Next, we compute the variance values of amplitude spectra. Then, we apply the fast Fourier transform to obtain the amplitude spectra of spectral variance. Finally, we calculate the eigenstructure coherence by using the amplitude spectra of spectral variance as the input. We apply the method to the theoretical models and practical seismic data. In the Marmousi velocity model, the coherence estimation using the amplitude spectra of the spectral variance as input shows more subtle discontinuities, especially in deeper layers. The results from field-data examples demonstrate that the proposed method is helpful for mapping faults and for improving the narrow channel edges’ resolution of interest. Therefore, the coherence algorithm based on the spectral variance analysis may be conducive to the seismic interpretation.

scholarly journals On the spectrum of vertically propagating gravity waves generated by a transient heat source

2004 ◽  
Vol 4 (1) ◽  
pp. 1063-1090 ◽  
Author(s):  
M. J. Alexander ◽  
J. R. Holton
Keyword(s):  
Heat Source ◽  
Gravity Waves ◽  
High Frequency ◽  
Convective Heating ◽  
Frequency Spectra ◽  
Wide Range ◽  
Frequency Components ◽  
High Frequency Waves ◽  
Vertically Propagating ◽  
Group Velocities

Abstract. It is commonly believed that cumulus convection preferentially generates gravity waves with tropospheric vertical wavelengths approximately twice the depth of the convective heating. Individual cumulonimbus, however, act as short term transient heat sources (duration 10 to 30 min). Gravity waves generated by such sources have broad frequency spectra and a wide range of vertical scales. The high-frequency components tend to have vertical wavelengths much greater than twice the depth of the heating. Such waves have large vertical group velocities, and are only observed for a short duration and at short horizontal distances from the convective source. At longer times and longer distances from the source the dominant wave components have short vertical wavelengths and much slower group velocities, and thus are more likely to be observed even though their contribution to the momentum flux in the upper stratosphere and mesosphere may be less than that of the high frequency waves. These properties of convectively generated waves are illustrated by a linear numerical model for the wave response to a specified transient heat source. The wave characteristics are documented through Fourier and Wavelet analysis, and implications for observing systems are discussed.

scholarly journals Review and Simulation of Fixed and Adaptive Hysteresis Current Control Considering Switching Losses and High-Frequency Harmonics

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Hani Vahedi ◽  
Abdolreza Sheikholeslami ◽  
Mohammad Tavakoli Bina ◽  
Mahmood Vahedi
Keyword(s):  
Fourier Transform ◽  
High Frequency ◽  
Current Control ◽  
Switching Frequency ◽  
Hysteresis Current Control ◽  
Switching Losses ◽  
Frequency Components ◽  
Source Current ◽  
Harmonic Components ◽  
The Fourier Transform

Hysteresis Current Control (HCC) is widely used due to its simplicity in implementation, fast and accurate response. However, the main issue is its variable switching frequency which leads to extraswitching losses and injecting high-frequency harmonics into the system current. To solve this problem, adaptive hysteresis current control (AHCC) has been introduced which produces hysteresis bandwidth which instantaneously results in smoother and constant switching frequency. In this paper the instantaneous power theory is used to extract the harmonic components of system current. Then fixed-band hysteresis current control is explained. Because of fixed-band variable frequency disadvantages, the adaptive hysteresis current control is explained that leads to fixing the switching frequency and reducing the high-frequency components in source current waveform. Due to these advantages of AHCC, the switching frequency and switching losses will be diminished appropriately. Some simulations are done in MATLAB/Simulink. The Fourier Transform and THD results of source and load currents and the instantaneous switching frequency diagram are discussed to prove the efficiency of this method. The Fourier Transform and THD results of source and load currents are discussed to prove the validity of this method.

Synthesis and Simplification of Fractal Profile

2011 ◽  
Vol 279 ◽  
pp. 262-265
Author(s):  
Chao Zhou ◽  
Cheng Hui Gao ◽  
Jie Chen ◽  
Lian Feng Lai
Keyword(s):  
Finite Element ◽  
Fourier Transform ◽  
Frequency Domain ◽  
Discrete Fourier Transform ◽  
High Frequency ◽  
Space Domain ◽  
Finite Element Software ◽  
Redundant Data ◽  
Frequency Components

In order to import a synthesized fractal profile into finite element software, the profile synthesized by discrete Fourier transform was studied. The synthesized profile was filtered in frequency domain in order to filter its high frequency components and to make it smooth, and then the chord deviation algorithm was used to reduce its redundant data in space domain. It was found that: after filtering, the profile is smooth but with lots of redundant data; the chord deviation algorithm can simplify the profile which is redundant in space domain; the time needed in the process of importing a profile into finite element software can be reduced greatly after profile simplification.

Interpretive advantages of 90°-phase wavelets: Part 1 — Modeling

Geophysics ◽  
2005 ◽  
Vol 70 (3) ◽  
pp. C7-C15 ◽  
Author(s):  
Hongliu Zeng ◽  
Milo M. Backus
Keyword(s):  
Seismic Data ◽  
High Frequency ◽  
Thick Layer ◽  
Amplitude Data ◽  
Frequency Components ◽  
Wireline Logs ◽  
Phase Data ◽  
Dual Polarity ◽  
Seismic Models ◽  
Zero Phase

We discuss, in a two-part article, the benefits of 90°-phase wavelets in stratigraphic and lithologic interpretation of seismically thin beds. In Part 1, seismic models of Ricker wavelets with selected phases are constructed to assess interpretability of composite waveforms in increasingly complex geologic settings. Although superior for single surface and thick-layer interpretation, zero-phase seismic data are not optimal for interpreting beds thinner than a wavelength because their antisymmetric thin-bed responses tie to the reflectivity series rather than to impedance logs. Nonsymmetrical wavelets (e.g., minimum-phase wavelets) are generally not recommended for interpretation because their asymmetric composite waveforms have large side lobes. Integrated zero-phase traces are also less desirable because they lose high-frequency components in the integration process. However, the application of 90°-phase data consistently improves seismic interpretability. The unique symmetry of 90°-phase thin-bed response eliminates the dual polarity of thin-bed responses, resulting in better imagery of thin-bed geometry, impedance profiles, lithology, and stratigraphy. Less amplitude distortion and less stratigraphy-independent, thin-bed interference lead to more accurate acoustic impedance estimation from amplitude data and a better tie of seismic traces to lithology-indicative wireline logs. Field data applications are presented in part 2 of this article.

scholarly journals On the spectrum of vertically propagating gravity waves generated by a transient heat source

2004 ◽  
Vol 4 (4) ◽  
pp. 923-932 ◽  
Author(s):  
M. J. Alexander ◽  
J. R. Holton
Keyword(s):  
Heat Source ◽  
Gravity Waves ◽  
High Frequency ◽  
Convective Heating ◽  
Frequency Spectra ◽  
Wide Range ◽  
Frequency Components ◽  
High Frequency Waves ◽  
Vertically Propagating ◽  
Group Velocities

Abstract. It is commonly believed that cumulus convection preferentially generates gravity waves with tropospheric vertical wavelengths approximately twice the depth of the convective heating. Individual cumulonimbus, however, act as short term transient heat sources (duration 10 to 30min). Gravity waves generated by such sources have broad frequency spectra and a wide range of vertical scales. The high-frequency components tend to have vertical wavelengths much greater than twice the depth of the heating. Such waves have large vertical group velocities, and are only observed for a short duration and at short horizontal distances from the convective source. At longer times and longer distances from the source the dominant wave components have short vertical wavelengths and much slower group velocities, and thus are more likely to be observed even though their contribution to the momentum flux in the upper stratosphere and mesosphere may be less than that of the high frequency waves. These properties of convectively generated waves are illustrated by a linear numerical model for the wave response to a specified transient heat source. The wave characteristics are documented through Fourier and Wavelet analysis, and implications for observing systems are discussed.

Noise‐adaptive filtering of seismic shot records

Geophysics ◽  
1988 ◽  
Vol 53 (5) ◽  
pp. 638-649 ◽  
Author(s):  
Richard G. Anderson ◽  
George A. McMechan
Keyword(s):  
Fourier Transform ◽  
Adaptive Filtering ◽  
Seismic Data ◽  
Adaptive Filters ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Amplitude Spectrum ◽  
Noise Rejection ◽  
Amplitude Spectra ◽  
Spectral Subtraction Method

Ambient noise can obscure reflections on deep crustal seismic data. We use a spectral subtraction method to attenuate stationary noise. Our procedure, called noise‐adaptive filtering, is to Fourier transform the noise before the first arrivals, subtract the amplitude spectrum of the noise from the amplitude spectrum of the noisy data, and inverse Fourier transform. The phase spectrum is not corrected, but the method attenuates noise if the phase shift between the signal and noise is random. The algorithm can be implemented as a frequency filter, as a frequency‐wavenumber filter, or as two separate frequency and wavenumber filters. Noise‐adaptive filtering is often superior to conventional frequency or frequency‐wavenumber filtering because it adapts to spatial variations in the noise without parameter testing. Noise‐adaptive filters can achieve noise rejection ratios of up to 45 dB; their dynamic range is about 25 dB. These filters work best when the input signal‐to‐noise ratio is on the order of 0 dB and there are significant differences between the frequency‐wavenumber amplitude spectra of the signal and noise. Application of the method to field data can enhance events that are not visible in the input data.

Progressive denoising of seismic data via robust noise estimation in dual domains

Geophysics ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. V99-V118
Author(s):  
Yi Lin ◽  
Jinhai Zhang
Keyword(s):  
Seismic Data ◽  
High Frequency ◽  
Random Noise ◽  
Denoising Method ◽  
Data Set ◽  
Edge Preserving ◽  
Space Domain ◽  
Time Space ◽  
Frequency Components ◽  
Resolution Imaging

Random noise attenuation plays an important role in seismic data processing. Most traditional methods suppress random noise either in the time-space domain or in the transformed domain, which may encounter difficulty in retaining the detailed structures. We have introduced the progressive denoising method to suppress random noise in seismic data. This method estimates random noise at each sample independently by imposing proper constraints on local windowed data in the time-space domain and then in the transformed domain, and the denoised results of the whole data set are gradually improved by many iterations. First, we apply an unnormalized bilateral kernel in time-space domain to reject large-amplitude signals; then, we apply a range kernel in the frequency-wavenumber domain to reject medium-amplitude signals; finally, we can obtain a total estimate of random noise by repeating these steps approximately 30 times. Numerical examples indicate that the progressive denoising method can achieve a better denoising result, compared with the two typical single-domain methods: the [Formula: see text]-[Formula: see text] deconvolution method and the curvelet domain thresholding method. As an edge-preserving method, the progressive denoising method can greatly reduce the random noise without harming the useful signals, especially to those high-frequency components, which would be crucial for high-resolution imaging and interpretations in the following stages.

scholarly journals High Resolution Impedance Inversion

2019 ◽  
Vol 37 (4) ◽  
Author(s):  
Carlos Cunha Filho ◽  
Leonardo Teixeira Da Silva ◽  
Nathalia Souto Muniz Da Cruz ◽  
Andrea Damasceno ◽  
Tatiana Soares De Oliveira ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
High Frequency ◽  
Frequency Bandwidth ◽  
Input Amplitude ◽  
Amplitude Data ◽  
Impedance Inversion ◽  
Frequency Components ◽  
Study Case

ABSTRACTThe identification of clay-rich layers is crucial for development of pre-salt reservoirs. They represent flow barriers and compromise the return of investment of the project if the thickness is misvalued. This issue becomes more relevant for thin clay-rich layers. The solution for the characterization of thin beds is classic: increase of the frequency bandwidth in seismic data. Here, we present a new methodology to derive high-frequency impedance volume. The approach starts with the recovery of low and high-frequency components in seismic data by the application of interactive deconvolution (iterdec). The extended bandwidth data is employed as an input amplitude data to the sparse-spike inversion. The outcome is a high-frequency acoustic impedance volume, which improves the interpretation of thin clay-rich layers. We present a study case of a presalt reservoir to demonstrate that this technique mitigated the location risk of an injection well and helped to maximize the oil swept of its vicinity. Furthermore, we discuss the required adaptations in the sparse-spike inversion workflow, and present the advantages of this approach when compared with conventional inversion results.Keywords: Inversion, resolution, broadband, pre-salt. RESUMOA identificação de camadas argilosas é crucial para o desenvolvimento de reservatórios do pre-sal. Elas atuam como barreira para o fluxo dos fluidos, comprometendo o retorno do investimento no projeto, caso sua espessura seja subavaliada. Esta questão se torna mais relevante no caso the camadas argilosas de pequena espessura. A solução para a caracterização de camadas finas é clássica: torna-se necessário aumentar a banda espectral do dado sísmico. O presente trabalho apresenta a metodologia e os primeiros resultados da incorporação de uma nova metodologia para geração de volumes de impedância de alta resolução. Nesta abordagem, os componentes de baixa e alta frequência do dado sísmico são recuperados através da aplicação de um processo de deconvolução iterativa (iterdec). Em seguida, este dado com banda espectral expandida é utilizado como entrada para uma inversão esparsa, resultando num volume de impedância acústica, que reduz as incertezas na interpretação de camadas argilosas de pouca espessura. Apresenta-se o estudo de caso de um reservatório do pre-sal para demonstrar a efetividade desta técnica na mitigação de risco associado ao posicionamento de um poço injetor, resultando na maximização da varredura de óleo em torno do poço. São apresentadas e discutidas as adaptações necessárias ao fluxo tradicional de inversão e condicionamento de dados sísmicos, bem como as vantagens da aplicação dessa metodologia sobre os resultados da inversão.Palavras-chave: Inversão, resolução, banda-larga, pre-sal.

S-transform and Fourier transform frequency spectra of broadband seismic signals

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. O71-O81 ◽  
Author(s):  
Lin Wu ◽  
John Castagna
Keyword(s):  
Fourier Transform ◽  
Frequency Analysis ◽  
Seismic Data ◽  
General Rule ◽  
Peak Frequency ◽  
Seismic Signals ◽  
Frequency Spectra ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
S Transform

The S-transform is one way to transform a 1D seismogram into a 2D time-frequency analysis. We have investigated its use to compute seismic interpretive attributes, such as peak frequency and bandwidth. The S-transform normalizes a frequency-dependent Gaussian window by a factor proportional to the absolute value of frequency. This normalization biases spectral amplitudes toward higher frequency. At a given time, the S-transform spectrum has similar characteristics to the Fourier spectrum of the derivative of the waveform. For narrowband signals, this has little impact on the peak frequency of the time-frequency analysis. However, for broadband seismic signals, such as a Ricker wavelet, the S-transform peak frequency is significantly higher than the Fourier peak frequency and can thus be misleading. Numerical comparisons of spectra from a variety of waveforms support the general rule that S-transform peak frequencies are equal to or greater than Fourier-transform peak frequencies. Comparisons on real seismic data suggest that this effect should be considered when interpreting S-transform spectral decompositions. One solution is to define the unscaled S-transform by removing the normalization factor. Tests comparing the unscaled S-transform with the S-transform and the short-windowed Fourier transform indicate that removing the scale factor improves the time-frequency analysis on reflection seismic data. This improvement is most relevant for quantitative applications.

Application of a Wavelet Extension De-Noising Method in Seismic Data Processing

2012 ◽  
Vol 622-623 ◽  
pp. 1670-1673
Author(s):  
Ye Wu ◽  
Bo Zhang ◽  
Jia Wei
Keyword(s):  
Fourier Transform ◽  
Seismic Data ◽  
High Frequency ◽  
The Other ◽  
Frequency Noise ◽  
Seismic Data Processing ◽  
High Frequency Noise ◽  
Filtering Method ◽  
Components Method ◽  
Coefficient Method

A new wavelet extension de-noising (WED) method is proposed in this paper. The basic principle is derived in detail. We have removed the high frequency noise in seismic data based on the suppressing detail components method, Fourier transform filtering method, WED method and reconstructing the 5th layer approximate coefficient method respectively, and the results show that the WED method can more effectively restrain noise than the other methods.

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