Signal and noise separation method for pre-stack seismic data in wave atomic domain based on coefficient correlation threshold

Yang Ning, He Zhen-hua, Huang De-ji

Oil Geophysical Prospecting ›› 2011, Vol. 46 ›› Issue (1) : 53-57.

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PDF(5993 KB)
Oil Geophysical Prospecting ›› 2011, Vol. 46 ›› Issue (1) : 53-57.

Signal and noise separation method for pre-stack seismic data in wave atomic domain based on coefficient correlation threshold

  • Yang Ning1, He Zhen-hua2, Huang De-ji2
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Abstract

The signal-noise separation method for pre-stack seismic data in the wave atomic domain was proposed in this paper,at first the multi-scale decomposition was conducted in the wave atomic domain,then based on the energy concentration principle the coefficient correlation for the different scales were utilized to separate effective signal and the noise.The results of numerical simulation and field data processing indicate that the pre-stack seismic data signal-noise separation method which is based on the coefficient correlation threshold in the wave atomic domain could effectively suppresses the random noise,meanwhile it also could restrain some coherent noise.It can be seen that the signal to noise ratio for the processed seismic sections was greatly raised and the reflection events were more continuous,providing high signal to noise sections for the subsequent processing.

Key words

coefficient correlation / threshold / wave atom / signal-noise separation

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Yang Ning, He Zhen-hua, Huang De-ji. Signal and noise separation method for pre-stack seismic data in wave atomic domain based on coefficient correlation threshold[J]. Oil Geophysical Prospecting, 2011, 46(1): 53-57

References

[1] 贺振华,黄德济.裂缝油气藏地球物理预测.四川科技出版社,2007,136~168 [2] Landes K J. Rtdgelets:Theory and Applications[D]. Department of Statistics,Stanford University,USA,1998,1~166 [3] Landes K J,Demanet L and Donoho D L. Fase discrete curvelet transforms,applied and computational mathematics. California Institute Technology, Pasadena, L alifornia, USA, 2005,1 ~43 [4] Do M N,Vetterli M. The contourlet transform:an efficiet directional multiresolution image representation. IEEE Transactions Image on Processing,2005,14(12):2091~2106 [5] Donoho D L. Wedgelets:nearly minimax estimation of edges. Ann Static,1999,27:859~897 [6] Loifman R R,Meyer Y,Quake S,Wickerhauser M V. Signal processing and compression with wave packets// Meyer Y,Roques S eds. Progress ln Wavs-let Analyss and Application. Gif-sur-Yvette,1993,77 ~93 [7] Demanet L and Ying L X. Wave atoms and aparsity of oscillatory patterns. Applied and Computational Harmonic Analysis,2007,23 (3): 368~387 [8] Neelamani Ramesh,Baumstein Anatoly I,uillard Dominique G et al. Coherent and random noise attenuation using the curvelet transform. The Leading Ede,2008,27(2):240~248 [9] 张恒磊,张云翠,宋双,刘天佑.基于Curvelet域的叠前地震资料去噪方法.石油地球物理勘探,2008,43(5):508~513Zhang Heng-lei,zhang Yun-cui,Song Shuang,Liu Tian-you.Curvelet domain-based prestack seismic data denoise method.OGP,2008,43(5):508~513 [10] Villemoes L. Wavelet packets with uniform time-frequency localization. Comptes-Rendus Mathematique,2002,335(10):793~796
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