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Proceedings Paper

Low-bit-rate efficient compression for seismic data
Author(s): Amir Z. Averbuch; Francois G. Meyer; Jan-Olov Stroemberg; Ronald Raphael Coifman; Anthony A. Vassiliou
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Paper Abstract

The main drive behind the use of data compression in seismic data is the very large size of seismic data acquired. Some of the most recent acquired marine seismic data sets exceed 10 Tbytes, and in fact there are currently seismic surveys planned with a volume of around 120 Tbytes. Nevertheless, seismic data are quite different from the typical images used in image processing and multimedia applications. Some of their major differences are the data dynamic range exceeding 100 dB in theory, very often it is data with extensive oscillatory nature, the x and y directions represent different physical meaning, and there is significant amount of coherent noise which is often present in seismic data. The objective of this paper is to achieve higher compression ratio, than achieved with the wavelet/uniform quantization/Huffman coding family of compression schemes, with a comparable level of residual noise. The goal is to achieve above 40dB in the decompressed seismic data sets. One of the conclusions is that adaptive multiscale local cosine transform with different windows sizes performs well on all the seismic data sets and outperforms the other methods from the SNR point of view. Comparison with other methods (old and new) are given in the full paper. The main conclusion is that multidimensional adaptive multiscale local cosine transform with different windows sizes perform well on all the seismic data sets and outperforms other methods from the SNR point of view. Special emphasis was given to achieve faster processing speed which is another critical issue that is examined in the paper. Some of these algorithms are also suitable for multimedia type compression.

Paper Details

Date Published: 5 December 2001
PDF: 11 pages
Proc. SPIE 4478, Wavelets: Applications in Signal and Image Processing IX, (5 December 2001); doi: 10.1117/12.449714
Show Author Affiliations
Amir Z. Averbuch, Tel Aviv Univ. (Israel)
Francois G. Meyer, Univ. of Colorado/Boulder (United States)
Jan-Olov Stroemberg, Royal Institute of Technology (Sweden)
Ronald Raphael Coifman, Yale Univ. (United States)
Anthony A. Vassiliou, GeoEnergy, Inc. (United States)


Published in SPIE Proceedings Vol. 4478:
Wavelets: Applications in Signal and Image Processing IX
Andrew F. Laine; Michael A. Unser; Akram Aldroubi, Editor(s)

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