小波(包)滤波方法的GUI及其在深地震测深数据处理中的应用
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摘要
在深地震测深数据处理中,仍多用基于傅里叶变换的滤波方法和小波二阶相关去噪方法。鉴于傅里叶变换方法对非稳态的地震信号不能提供在时频上的任何局部信息,而小波和小波包方法弥补了傅里叶变换的不足,能够提供时频上的任何局部信息,且高阶相关比二阶相关对随机噪声有更好的抑制和去除作用,本文结合小波和小波包去噪方法以及高阶相关去噪方法,编写了深地震测深数据处理的小波和小波包滤波方法的人机交互软件,用于抑制和去除地震信号中的加性高斯随机噪声。该软件可以方便快捷地显示深地震测深的地震记录截面,进行小波域的自适应阈值去噪、小波域和小波包域的二阶和高阶相关去噪以及基于傅氏变换的常规滤波。实例计算结果表明,方法和程序是有效且可行的。
In a deep seismic sounding data processing, filtering methods based on the Fourier transform and second-order correlation denoising in the wavelet domain are still used. In view of the fact that the local time -frequency information can not be obtained with the Fourier transform in processing non-steady state seismic signals, which can be obtained with the wavelet (packet) transform, and also of the fact that the higher -order correlation denoising is better than a second-order correlation denoising, graphical user interface software is developed based on the wavelet and wavelet packet denoising as well as higher -order correlation denoising method, which can be used to eliminate the additive Gaussian white noise. The software can quickly and easily display seismic record sections, can do adaptive threshold denoising in the wavelet domain, can do the second-order and higher-order correlation denoising in the wavelet and wavelet packet domains, and can do also the filtering based on the Fourier transform. Examples of the deep seismic sounding data show that the methods and software are effective.
In a deep seismic sounding data processing, filtering methods based on the Fourier transform and second-order correlation denoising in the wavelet domain are still used. In view of the fact that the local time -frequency information can not be obtained with the Fourier transform in processing non-steady state seismic signals, which can be obtained with the wavelet (packet) transform, and also of the fact that the higher -order correlation denoising is better than a second-order correlation denoising, graphical user interface software is developed based on the wavelet and wavelet packet denoising as well as higher -order correlation denoising method, which can be used to eliminate the additive Gaussian white noise. The software can quickly and easily display seismic record sections, can do adaptive threshold denoising in the wavelet domain, can do the second-order and higher-order correlation denoising in the wavelet and wavelet packet domains, and can do also the filtering based on the Fourier transform. Examples of the deep seismic sounding data show that the methods and software are effective.
引文
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[17]Donoho D L,Jonstone I M.Ideal spatial adaptation via wavelet shrinkage[J].Biometrika,1994(81):425-455.
[18]刘英霞,王欣.最佳软门限去噪[J].电子学报,2006,34(1):167-169.Liu Yingxia,Wang Xin.Acta Electronica Sinica,2006,34(1):167-169.
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[2]付燕.人工地震信号去噪方法研究[D].西安:西北工业大学,2002.Fu Yan.Study on denoise for seismic signal[D].Xi'an:Northwestem Polytechnic University,2002.
[3]Donoho D L.De-noising by soft thresholding[J].IEEE Trans IT,1995,41(3):613-627.
[4]Xu Y,Weaver J B,Healy D M,et al.Wavelet transform domain filters:a spatially selective noise filtration technique[J].IEEE Trans Image Processing,1994,3(6):747-758.
[5]Mallat S,Hwang W L.Singularity detection and processing with wavelets[J].IEEE Trans Inform Theory,1992,38(2):617-643.
[6]潘泉,张磊,孟晋丽,等.小波滤波方法及应用[M].北京:清华大学出版社,2005:63-72.Pan Quan,Zhang Lei,Meng Jinli,et al.Wavelet filtering methods and its application[M].Beijing:Tsinghua University Press,2005:63-72.
[7]曹汉强,陈汝钧,李旭涛,等.杂乱背景中隐藏信号的三阶相关检测技术[J].光电工程,2005,32(9):5-11.Cao Hanqiang,Chen Rujun,Li Xutao,et al.Opto-Electronic Engineering,2005,32(9):5-11.
[8]张贤达.现代信号处理[M].北京:清华大学出版社,2002:267.Zhang Xianda.Modern signal processing[M].Beijing:Tsinghua University Press,2002:267.
[9]张三宗,徐义贤.地震记录小波域高阶相关叠加技术[J].地球物理学报,2006,49(2):554-560.Zhang Sanzong,Xu Yixian.Chinese Journal of Geophysics,2006,49(2):554-560.
[10]Bruce A G,Gao H Y.Understanding WaveShrink:Variance and Bias Estimation[J].Biometrika,1996,83(4):727-745.
[11]Gao H,Bruce A.WaveShrink with firm shrinkage[J].Statistica Sinica,1997,7:855-874.
[12]赵瑞珍.小波理论及其在图像、信号处理中的算法研究[D].西安:西安电子科技大学,2001.Zhao Ruizhen.Wavelet theory and algorithm for image and signal processing[D].Xi'an:Xidian University,2001.
[13]赵瑞珍,屈汉章,宋国乡.基于小波系数区域相关性的阈值滤波算法[J].西安电子科技大学学报,2001,28(3):324-327.Zhao Ruizhen,Qu Hanzhang,Song Guoxiang.Journal of Xidian University,2001,28(3):324-327.
[14]樊计昌,王夫运,刘明军,等.小波尺度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,2008,43(5):514-517.Fan Jichang,Wang Fuyun,Liu Mingjun,et al.Oil Geophysical Prospecting,2008,43(5):514-517.
[15]樊计昌,李松林,刘明军.利用小波包变换提取地震波高频信息[J].石油地球物理勘探,2006,41(2):144-149.Fan Jichang,Li Sonlin,Liu Mingjun.Oil Geophysical Prospecting,2006,41(2):144-149.
[16]徐长发,李国宽.实用小波方法[M].武汉:华中科技大学出版社,2001:99-100.Xu Changfa,Li Guokuan.Practical wavelet method[M].Wuhan:Huazhong University of Science and Technology Press,2001:99-100.
[17]Donoho D L,Jonstone I M.Ideal spatial adaptation via wavelet shrinkage[J].Biometrika,1994(81):425-455.
[18]刘英霞,王欣.最佳软门限去噪[J].电子学报,2006,34(1):167-169.Liu Yingxia,Wang Xin.Acta Electronica Sinica,2006,34(1):167-169.
[19]樊计昌,刘明军,王夫运,等.浅析小波最大分解层[J].科技导报,2008,26(10):40-42.Fan Jichang,Liu Mingjun,Wang Fuyun,et al.Science and Technology Review,2008,26(10):40-42.
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