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Proceedings Paper

Application of the wavelet transform in seismic data processing for the development of new noise reduction techniques
Author(s): Fotios P. Kourouniotis; Robert F. Kubichek; Nicholas G. K. Boyd III; Arun K. Majumdar
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Paper Abstract

New techniques for developing more efficient noise reduction schemes are presented and implemented by applying the wavelet transform (WT) to a series of stationary and non- stationary signals. Their effectiveness is illustrated with specific applications to both real and synthetic seismic data, and the superiority over Fourier transform (FT) based methods is demonstrated. These methods aim at the efficient reduction of the effects that surface waves, airwaves, and direct waves can have on the interpretation of a seismic record. We first apply the WT on each trace in a common- depth-point gather and then perform stacking in the WT domain and compute both the mean and median transforms. Then, the signal-to-noise ratio of the stacked transforms is estimated and used as a criterion to improve the quality of the transformed data, and finally the total energy in the stacked WT plane is computed and redistributed in order to boost weak events. The advantage of stacking in the WT domain is that it allows for detection of weak reflections overpowered by high amplitude surface and air waves. Additionally, it is shown that by frequency modulating a mother wavelet, further attenuation of surface waves, airwaves, and first breaks may be achieved.

Paper Details

Date Published: 23 October 1996
PDF: 12 pages
Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996); doi: 10.1117/12.255273
Show Author Affiliations
Fotios P. Kourouniotis, Univ. of Wyoming (United States)
Robert F. Kubichek, Univ. of Wyoming (United States)
Nicholas G. K. Boyd III, Univ. of Wyoming (United States)
Arun K. Majumdar, Laser/electro-optics Concepts Research, Inc. (United States)

Published in SPIE Proceedings Vol. 2825:
Wavelet Applications in Signal and Image Processing IV
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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