基于曲波变换和各向异性扩散滤波的联合去噪技术

doi:10.7623/syxb201604008

石油学报 ›› 2016, Vol. 37 ›› Issue (4): 490-498,507.DOI: 10.7623/syxb201604008

基于曲波变换和各向异性扩散滤波的联合去噪技术

姚振岸¹, 孙成禹¹, 石小磊², 刘牧天¹

1. 中国石油大学地球科学与技术学院山东青岛 266580;
2. 新疆金戈壁油砂矿开发有限责任公司新疆克拉玛依 834000

收稿日期:2015-11-02 修回日期:2016-03-01 出版日期:2016-04-25 发布日期:2016-05-06
通讯作者: 姚振岸,男,1990年10月生,2013年获中国石油大学(华东)学士学位,现为中国石油大学(华东)博士研究生,主要从事地震波传播理论、地震资料处理和储层岩石物理等方面的研究。Email:an6428060@163.com
作者简介:姚振岸,男,1990年10月生,2013年获中国石油大学(华东)学士学位,现为中国石油大学(华东)博士研究生,主要从事地震波传播理论、地震资料处理和储层岩石物理等方面的研究。Email:an6428060@163.com
基金资助:
国家自然科学基金项目(No.41374123,No.41504097)和山东省自然科学基金项目(ZR2013DQ020)资助。

A combined denoising method based on Curvelet transform and anisotropic diffusion filtering

Sun Chengyu¹, Sun Chengyu¹, Shi Xiaolei², Liu Mutian¹

1. School of Geoscience, China University of Petroleum, Shandong Qingdao 266580, China;
2. Xinjiang Golden Gobi Oil Sands Development Company Limited, Xinjiang Karamay 834000, China

Received:2015-11-02 Revised:2016-03-01 Online:2016-04-25 Published:2016-05-06

摘要/Abstract

摘要：

曲波变换阈值去噪方法是一种有效的随机噪音压制方法,其去噪效果取决于阈值的选取,且存在过度平滑和环绕效应2种固有缺陷。各向异性扩散滤波方法是一种基于热扩散偏微分方程的边界保持的滤波方法,适用于信噪比较高的地震纹理图像,往往用于图像增强。基于对曲波变换阈值的分析,充分结合2种去噪方法的优点,提出了一种有效的联合去噪算法,避开了曲波阈值选取的困难,实现了边界和振幅的保持,改善了曲波变换阈值方法的缺陷。通过对叠前、叠后模拟地震数据以及实际地震数据测试,证明了该方法在去除随机噪音的同时能有效保持地震同相轴的振幅和形态特征。通过6种定量化指标,分析了该方法相对于多种曲波阈值去噪方法在提高信噪比和保持边界特征方面的优势。

关键词: 曲波变换, 各向异性扩散, 随机噪音去除, 边界和振幅保持, 滤波

Abstract:

Curvelet transform threshold denoising method is an effective way for random noise suppression, of which the denoising effect depends on threshold selection, and two inherent defects exist, i.e., excessive smoothing and surrounding effect. Anisotropic diffusion filtering method is able to preserve the border structures based on thermal diffusion partial differential equation, applicable to process the seismic texture images with high signal to noise ratio for image enhancing. Based on the analysis of Curvelet transform threshold, a new effective combined denoising algorithm is presented to fully integrate the advantages of both denoising methods. On the one hand, it avoids the difficult in Curvelet threshold selection. On the other hand, the border and amplitude are preserved to improve the defect of Curvelet transform threshold method. Through pre-stack and post-stack simulations on seismic data and actual seismic dada tests, it has been proven that such method can not only remove random noises, but also preserve the amplitude and morphological characteristics of seismic events effectively. Six quantitative evaluation indices are used to analyze the advantages of such method in improving signal to noise ratio and preserving border characteristics compared with multiple Curvelet threshold desnoising method.

Key words: Curvelet transform, anisotropic diffusion, random denoising, border and amplitude preserving, wave filtering

中图分类号:

TE631.4

姚振岸, 孙成禹, 石小磊, 刘牧天. 基于曲波变换和各向异性扩散滤波的联合去噪技术[J]. 石油学报, 2016, 37(4): 490-498,507.

Sun Chengyu, Sun Chengyu, Shi Xiaolei, Liu Mutian. A combined denoising method based on Curvelet transform and anisotropic diffusion filtering[J]. Acta Petrolei Sinica, 2016, 37(4): 490-498,507.

参考文献

[1] 李振春,张军华.地震数据处理方法[M].东营:石油大学出版社,2004:1-4.
Li Zhenchun,Zhang Junhua.Seismic data processing technique[M].Dongying:University of Petroleum Press,2004:1-4.
[2] 刘喜武,刘洪,李幼铭.高分辨率Randon变换方法及其在地震信号处理中的应用[J].地球物理学进展,2004,19(1):8-15.
Liu Xiwu,Liu Hong,Li Youming.High resolution radon transform and its application in seismic signal processing[J].Progress in Geophysics,2004,19(1):8-15.
[3] 高静怀,毛剑,满蔚仕,等.叠前地震资料噪声衰减的小波域方法研究[J].地球物理学报,2006,49(4):1155-1163.
Gao Jinghuai,Mao Jian,Man Weishi,et al.On the denoising method of prestack seismic data in wavelet domain[J].Chinese Journal of Geophysics,2006,49(4):1155-1163.
[4] 吴招才,刘天佑.地震数据去噪中的小波方法[J].地球物理学进展,2008,23(2):493-499.
Wu Zhaocai,Liu Tianyou.Wavelet transform methods in seismic data noise attenuation[J].Progress in Geophysics,2008,23(2):493-499.
[5] 姜宇东,杨勤勇,何柯,等.基于曲波变换的地面微地震资料去噪方法研究[J].石油物探,2012,51(6):620-624.
Jiang Yudong,Yang Qinyong,He Ke,et al.Surface microseismic date denoising method based on Curvelet transform[J].Geophysical Prospecting for Petroleum,2012,51(6):620-624.
[6] 薛诗桂.基于曲波变换的循环平移地震随机噪声衰减[J].地球物理学进展,2015,30(1):372-377.
Xue Shigui.The Curvelet transform for seismic random de-noising using cycle spinning method[J].Progress in Geophysics,2015,30(1):372-377.
[7] 包乾宗,陈文超,高静怀.基于第二代Curvelet变换的地震资料随机噪声衰减[J].煤田地质与勘探,2010,38(1):66-70.
Bao Qianzong,Chen Wenchao,Gao Jinghuai.Seismic data random noise attenuation based on the second generation Curvelet transform[J].Coal Geology & Exploration,2010,38(1):66-70.
[8] Herrmann F J,Verschuur E.Curvelet-domain multiple elimination with sparseness constraints[C]//74th Annual Internet SEG Mtg,Society of Exploration Geophysicists.Expanded Abstracts,2004:1333-1336.
[9] 王德营,李振春,黄建平,等.一种分尺度的面波压制方法[J].石油学报,2014,35(2):303-309.
Wang Deying,Li Zhenchun,Huang Jianping,et al.A surface wave suppression method based on scale-partition[J].Acta Petrolei Sinica,2014,35(2):303-309.
[10] Perona P,Malik J.Scale-space and edge detection using anisotropic diffusion[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1990,12(7):629-639.
[11] 孙夕平,杜世通,汤磊.相干增强各向异性扩散滤波技术[J].石油地球物理勘探,2004,39(6):651-655.
Sun Xiping,Du Shitong,Tang Lei.Coherent-enhancing anisotropic diffusion filtering technique[J].Oil Geophysical Prospecting,2004,39(3):651-655.
[12] 张尔华,王伟,高静怀,等.非线性各向异性扩散滤波器用于三维地震资料噪声衰减与结构特征增强[J].地球物理学进展,2010,25(3):866-870.
Zhang Erhua,Wang Wei,Gao Jinghuai,et al.Non-linear anisotropic diffusion filtering for 3D seismic noise removal and structure enhancement[J].Progress in Geoph ysics,2010,25(3):866-870.
[13] 倪雪,李庆武,孟凡,等.基于Curvelet变换和全变差的图像去噪方法[J].光学学报,2009,29(9):2390-2394.
Ni Xue,Li Qingwu,Meng Fan,et al.Image denoising method based on Curvelet transform and total variation[J].Acta Optica Sinica,2009,29(9):2390-2394.
[14] Lavialle O,Pop S,Germain C,et al.Seismic fault preserving diffusion[J].Journal of Applied Geophysics,2007,61(2):132-141.
[15] Cai Hanpeng,He Zhenhua,Li Yalin,et al.An adaptive noise attenuation method for edge and amplitude preservation[J].Applied Geophysics,2014,11(3):289-300.
[16] Weickert J.Coherence-enhancing diffusion filtering[J].International Journal of Computer Vision,1999,31(2/3):111-127.
[17] 沈跃,张亨,张令坦,等.基于自适应滤波的钻井液连续压力波信号噪声抑制[J].石油学报,2014,35(2):353-358.
Shen Yue,Zhang Heng,Zhang Lingtan,et al.Eliminating noise of drilling fluid continuous pressure wave signals based on the self-adaptive filtering method[J].Acta Petrolei Sinica,2014,35(2):353-358.
[18] 张军华,藏胜涛,周振晓,等.地震资料信噪比定量计算及方法比较[J].石油地球物理勘探,2009,44(4):481-486.
Zhang Junhua,Zang Shengtao,Zhou Zhenxiao,et al.Quantitative computation and comparison of S/N ratio in seismic data[J].Oil Geophysical Prospecting,2009,44(4):481-486.
[19] 韩春明,郭华东,王长林,等.保持边缘的SAR图像滤波方法[J].高技术通讯,2003,13(7):11-15.
Han Chunming,Guo Huadong,Wang Changlin,et al.Edge preserving filter for SAR images[J].High Technology Letters,2003,13(7):11-15.
[20] Wang Zhou,Bovik A C,Lu Ligang.Why is image quality assessment so difficult?[C]//Proceedings of IEEE International Conference on Acoustics,Speech,and Signal Processing.Orlando,FL,USA:IEEE,2002,4:IV-3313- IV-3316.
[21] Wang Zhou,Bovik A C,Sheikh H R,et al.Image quality assessment:from error visibility to structural similarity[J].IEEE Transactions on Image Processing,2004,13(4):600-612.
[22] 孙成禹,张吉辉.完全纵波方程有限差分波场模拟[J].石油地球物理勘探,2005,40(3):289-294.
Sun Chengyu,Zhang Jihui.Finite-difference wavefield simulation of full P-wave equation[J].Oil Geophysical Prospecting, 2005,40(3):289-294.

基于曲波变换和各向异性扩散滤波的联合去噪技术

A combined denoising method based on Curvelet transform and anisotropic diffusion filtering

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