Journal of Jilin University(Earth Science Edition) ›› 2015, Vol. 45 ›› Issue (1): 293-301.doi: 10.13278/j.cnki.jjuese.201501303

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Threshold Denoising Method Based on New Seislet Transform in the Condition of Low SNR

Liu Cai1, Cui Fangzi1, Liu Yang1, Wang Dian1, Liu Dianmi2, Zhang Peng1   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Research Institute of Geophysical Prospecting, Jilin Oilfield Company, CNPC, Songyuan 138000, Jilin, China
  • Received:2014-01-16 Published:2015-01-26

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Abstract:

Seislet transform is a wavelet-like transform based on wavelet base that analyzes seismic data along variable local event slopes. The calculation of the local event slopes is the key step of this method.There are many kinds of methods to calculate the local slopes. But in the condition of low SNR, these methods have some limits. We propose a method that is suitable for low SNR based on the definition of the slopes of t-x relationship in CMP traces. Comparing the slopes of t-x relationship in CMP traces with PWD method, we can see that the new method is more accurate in calculating the local slopes. Apply these slopes to Seislet frame to establish a new Seislet transform that characterize low SNR data. In seismic data processing, we introduce one method which works well for acoustic signals. We propose the new threshold method with Seislet transform. It is not only suitable for seismic signals, but also better than the traditional threshold method to improve SNR. The results show that the combination of the new Seislet transform and improved threshold method can extract signal in the condition of low SNR effectively.

Key words: Seislet transform, low SNR, local event slope, threshold, denoising

CLC Number: 

  • P631.4

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