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The second-generation wavelet transform and its application in denoising of seismic data

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Abstract

This paper discusses the principle and procedures of the second-generation wavelet transform and its application to the denoising of seismic data. Based on lifting steps, it is a flexible wavelet construction method using linear and nonlinear spatial prediction and operators to implement the wavelet transform and to make it reversible. The lifting scheme transform -includes three steps: split, predict, and update. Deslauriers-Dubuc (4, 2) wavelet transforms are used to process both synthetic and real data in our second-generation wavelet transform. The processing results show that random noise is effectively suppressed and the signal to noise ratio improves remarkably. The lifting wavelet transform is an efficient algorithm.

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Authors and Affiliations

  1. CNPC Key Lab of Geophysical Exploration, University of Petroleum, 102249, Beijing, China

    Cao Siyuan & Chen Xiangpeng

Authors
  1. Cao Siyuan
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  2. Chen Xiangpeng
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First author

Cao Siyuan received his Ph.D. degree from the University of Petroleum in 1994. His interests are in the areas of seismic data processing, neural networks, wavelet analysis, and fractals.

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Cao, S., Chen, X. The second-generation wavelet transform and its application in denoising of seismic data. Appl. Geophys. 2, 70–74 (2005). https://doi.org/10.1007/s11770-005-0034-4

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  • DOI: https://doi.org/10.1007/s11770-005-0034-4

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