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

[1] 张波, 印兴耀, 吴国忱, 等.用小波分析和反演方法联合去除随机噪声的研究[J].石油地球物理勘探, 1999, 34(6):635-641. Zhang Bo, Yin Xingyao, Wu Guochen, et al. Random Noise Elimination Using Wavelet Analysis and Inversion[J]. Oil Geophysical Prospecting, 1999, 34(6):635-641.

[2] 王典, 刘财, 刘洋, 等.基于提升算法和百分位数软阈值的小波去噪技术[J]. 地球物理学进展, 2008, 23(4):1124-1130. Wang Dian, Liu Cai, Liu Yang, et al. Application of Wavelet Transform Based on Lifting Scheme and Percentiles Soft Threshold to Elimination of Seismic Random Noise[J]. Progress in Geophysics, 2008, 23(4):1124-1130.

[3] 樊计昌, 刘明军, 王夫运, 等.小波包节点域和空间域倾角扫描高阶相关去噪技术[J]. 石油地球物理勘探, 2009, 44(6):695-699. Fan Jichang, Liu Mingjun, Wang Fuyun, et al. Dip Scanning High Order Correlation Denoise Technique in Wavelet Packet Node Field and Space Domain[J]. Oil Geophysical Prospecting, 2009, 44(6):695-699.

[4] Zhang Yi, Cheng Lizhi. A New Wavelet Denoising Method of Seismic Signals Based on a Recursive Optimal Thresholding[J]. Acta Scientiarum Naturalium Universitatis Nankaiensis, 2011, 4:14.

[5] 王志强, 韩立国, 巩向博, 等. 起伏地表检波器组合响应[J]. 吉林大学学报:地球科学版, 2014, 44(2):694-703. WangZhiqiang, HanLiguo, GongXiangbo, etal.GeophoneArrayResponseonUndulatingSurface[J].JournalofJilinUniversity:EarthScienceEdition, 2014, 44(2):694-703.

[6] Chauris H, Nguyen T. Seismic Demigration/Migration in the Curvelet Domain[J]. Geophysics, 2008, 73(2):35-46.

[7] Herrmann F J, Wang D, Hennenlent G, et al. Curvelet-Based Seismic Data Processing:A Multiscale and Nonlinear Approach[J]. Geophysics, 2008, 73(1):1-5.

[8] Pennec E L, Mallat S. Sparse Geometric Image Representation with Bandelets[J]. IEEE Trans Image Process, 2005, 14(4):423-438.

[9] Do M N, Vetterli M. The Contourlet Transform:An Efficient Directional Multiresolution Image Representation[J]. IEEE Trans Process, 2005, 14(12):2091-2106.

[10] Starck J L, Candes E J, Donoho D L. The Curvelet Transform for Image Denoising[J]. IEEE Trans Image Process, 2002, 11(6):670-684.

[11] Velisavljevic V. Directionlets:Anisotropic Multi-Directional Representation with Separable Filtering. Lausanne:Ecole Polytechnique Federale de Lausanne, 2005.

[12] Fomel S. Towards the Seislet Transform[J]. SEG Extended Abstracts, 2006, 25(1):2847-2851.

[13] Fomel S, Liu Y. Seislet Transform and Seislet Frame[J]. Geophysics, 2010, 75(3):25-38.

[14] 刘洋, Fomel S, 刘财, 等.高阶Seislet变换及其在随机噪声消除中的应用[J].地球物理学报, 2009, 52(8):2142-2151. Liu Yang, Fomel S, Liu Cai, et al. High-Order Seislet Transform and Its Application of Random Noise Attenuation[J]. Chinese Journal of Geophysics, 2009, 52(8):2142-2151.

[15] 张鹏, 陆文凯. 利用局部倾角的地震成像研究[C]//中国地球物理学会第二十六届年会、中国地震学会第十三次学术大会论文集. 宁波:中国地球物理学会, 中国地震学会, 2010. Zhang Peng, Lu Wenkai. Study of Seismic Imaging by Using Local Event Slopes[C]//Papers of the Twenty-Sixth Annual Meeting of Chinese Geophysical Society and the Thirteenth Academic Conference of Seismological Society of China. Ningbo:Chinese Geophysical Society, Seismological Society of China, 2010.

[16] Fomel S. Applications of Plane-Wave Destruction Filter[J]. Geophysics, 2002, 67(6):1946-1960.

[17] Bona A. Velocity-Less Migration Using Horizontal Slownesses[J]. EGU General Assembly, 2009, 11:EGU2009-3883.

[18] Douma H. Leading-Order Seismic Imaging Using Curvelets[J]. Geophysics, 2007, 72(6):231-248.

[19] Donoho D L, Johnstone J M. Ideal Spatial Adaptation by Wavelet Shrinkage[J]. Biometrika, 1994, 81(3):425-455.

[20] Gao H Y, Bruce A G. WaveShrink with Firm Shrinkage[J]. Statistica Sinica, 1997, 7(4):855-874.

[21] 李冲泥, 胡光锐.一种改进的子波域语音增强方法[J].通信学报, 1999, 20(4):88-91. Li Chongni, Hu Guangrui. A Modified Wavelet Domain Speech Enhancement Method[J]. Journal of China Institute of Communications, 1999, 20(4):88-91.

[22] 许丽群.小波阈值去噪改进算法研究[J].电子测量技术, 2010, 33(8):43-45. Xu Liqun.Research of Improved Algorithm of De-Noising in Wavelet Threshold[J].Electronic Measurement Technology, 2010, 33(8):43-45.

[23] 张新超. Seislet变换去除叠前线性干扰[D]. 成都:成都理工大学, 2009. Zhang Xinchao. Removal of Prestack Linear Noise by Seislet Transform[D]. Chengdu:Chengdu University of Technology, 2009.

[24] Fomel S. Velocity-Independent Time-Domain Seismic Imaging Using Local Event Slopes[J]. Geophysics, 2007, 72(3):139-147.

[25] Fomel S, Grechka V. Nonhyperbolic Reflection Moveout of P Waves:An Overview and Comparison of Reasons[M]. Golden:Center for Wave Phenomena Colorado School of Mines, 2001.

[26] 邓玉娟.基于小波变换的语音阈值去噪算法研究[D].重庆:重庆大学, 2009. Deng Yujuan. Study of Threshold De-Noising Algorithm of Speech Signal Based on Wavelet Transformation[D]. Chongqing:Chongqing University, 2009.

[27] 余晃晶.小波降噪阈值选取的研究[J].绍兴文理学院学报:自然科学版, 2004, 24(9):34-38. Yu Huangjing. Slection of a Wavelet Noise-Reduction Threshold[J]. Journal of Shaoxing University:Natural Science Edition, 2004, 24(9):34-38.

[28] Claerbout, J F. Basic Earth Imaging:Stanford Exploration Project[EB/OL].[2012-10-10]. http://www. stanford. edu/sep/prof/.
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