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Published as Geophysical Prospecting, 61, 516-525 (2013)

Seismic data analysis using local time-frequency decomposition

Yang Liu% latex2html id marker 1728
\setcounter{footnote}{1}\fnsymbol{footnote}% latex2html id marker 1729
\setcounter{footnote}{2}\fnsymbol{footnote}, Sergey Fomel% latex2html id marker 1730
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\setcounter{footnote}{1}\fnsymbol{footnote}College of Geo-exploration Science and Technology,
Jilin University
No.6 Xi minzhu street,
Changchun, China, 130026
% latex2html id marker 1727
\setcounter{footnote}{2}\fnsymbol{footnote}Bureau of Economic Geology,
John A. and Katherine G. Jackson School of Geosciences
The University of Texas at Austin
University Station, Box X
Austin, TX, USA, 78713-8924


Abstract:

Many natural phenomena, including geologic events and geophysical data, are fundamentally nonstationary - exhibiting statistical variation that changes in space and time. Time-frequency characterization is useful for analyzing such data, seismic traces in particular.

We present a novel time-frequency decomposition, which aims at depicting the nonstationary character of seismic data. The proposed decomposition uses a Fourier basis to match the target signal using regularized least-squares inversion. The decomposition is invertible, which makes it suitable for analyzing nonstationary data. The proposed method can provide more flexible time-frequency representation than the classical S transform. Results of applying the method to both synthetic and field data examples demonstrate that the local time-frequency decomposition can characterize nonstationary variation of seismic data and be used in practical applications, such as seismic ground-roll noise attenuation and multicomponent data registration.




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2013-07-26