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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 1729
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ootnote}{2}</SUP></A>, Sergey Fomel<A NAME=
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 WIDTH=College of Geo-exploration Science and Technology,
Jilin University
No.6 Xi minzhu street,
Changchun, China, 130026
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\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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Next: Introduction Up: Reproducible Documents

2013-04-13