一种改进的全变分地震图像去噪技术
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摘要
消除地震记录中的噪声是地震资料处理的重要环节,它对地震资料的后续处理和解释都有重要意义。在对传统全变分图像去噪模型原理分析的基础上,提出了一种加入扩散张量的改进全变分图像去噪方法。这种方法能够加强全变分模型中扩散项沿地层纹理方向的滤波作用,使得地层沿层理方向的连续性得到一致性增强;同时控制垂直于地层层理方向上的扩散以保护边缘信息。对川西某实际地震资料的处理结果表明,该方法能够有效地消除地震图像中的噪声,增强同相轴的连续性,提高地震资料的信噪比。
Noise muffling of seismic records is a significant step in seismic data processing and it is of great importance in processing and interpreting seismic data subsequently.Based on the analysis of principles of a traditional total variation image denoising model,an improved total variation approach to image denoising with diffusion tensor appended was proposed.Through enhancing the anisotropic filtering of diffusion terms along the orientation of stratigraphic textures in the total variation model,this approach could consistently strengthen the formation continuity along the orientation and control the diffusion state perpendicular to stratigraphic bedding so as to preserve the edge structure information.The actual result of this approach in application to some seismic data from western Sichuan showed that it could effectively remove the noise in seismic images,enhance the continuity of seismic events and increase the signal to noise ratio of seismic data.
Noise muffling of seismic records is a significant step in seismic data processing and it is of great importance in processing and interpreting seismic data subsequently.Based on the analysis of principles of a traditional total variation image denoising model,an improved total variation approach to image denoising with diffusion tensor appended was proposed.Through enhancing the anisotropic filtering of diffusion terms along the orientation of stratigraphic textures in the total variation model,this approach could consistently strengthen the formation continuity along the orientation and control the diffusion state perpendicular to stratigraphic bedding so as to preserve the edge structure information.The actual result of this approach in application to some seismic data from western Sichuan showed that it could effectively remove the noise in seismic images,enhance the continuity of seismic events and increase the signal to noise ratio of seismic data.
引文
[1]刘振武,撒利明,张昕,等.中国石油开发地震技术应用现状和未来发展建议[J].石油学报,2009,30(5):711-717.Liu Zhenwu,Sa Liming,Zhang Xin,et al.Current application andfuture development of production seismology in PetroChina[J].Acta Petrolei Sinica,2009,30(5):711-717.
[2]孟庆武,李成斌,李强,等.分形理论在高分辨处理中的应用[J].石油学报,2000,21(2):31-35.Meng Qingwu,Li Chengbin,Li Qiang,et al.Application of fractaltheory in high resolution processing of seismic data[J].Acta Pe-trolei Sinica,2000,21(2):31-35.
[3]Rudin L I,Osher S,Fatemi E.Nonlinear total variation based noiseremoval algorithms[J].Physica D:Nonlinear Phenomena,1992,60(1/2/3/4):259-268.
[4]Chambolle A,Lions P L.Image recovery via total variation mini-mization and related problems[J].Numerische Mathematik,1997,76(2):167-188.
[5]Chen Q,Montesinos P,Sun Q S,et al.Adaptive total variationdenoising based on difference curvature[J].Image and VisionComputing,2010,28(3):298-306.
[6]Chan T,Marquina A,Mulet P.High-order total variation-basedimage restoration[J].SIAM Journal on Scientific Computing,2000,22(2):503-516.
[7]李敏,冯象初.基于全变差和小波方法的图像去噪模型[J].西安电子科技大学学报:自然科学版,2006,33(6):980-984.Li Min,Feng Xiangchu.A denoising model using the total varia-tion and wavelet method[J].Journal of Xidian University,2006,33(6):980-984.
[8]余丽红,冯衍秋,陈武凡.基于自适应正则化的全变分去噪算法[J].中国图象图形学报,2009,14(10):1950-1954.Yu Lihong,Feng Yanqiu,Chen Wufan.Adaptive regularizationmethod based total variational de-noising algorithm[J].Journalof Image and Graphics,2009,14(10):1950-1954.
[9]Perona P,Malik J.Scale-space and edge detection using aniso-tropic diffusion[J].IEEE Transactions on Pattern Analysis andMachine Intelligence,1990,12(7):629-639.
[10]Weickert J.Coherence-enhancing,diffusion filtering[J].Interna-tional Journal of Computer Vision,1999,31(2/3):111-127.
[11]陈凤,李金宗,李冬冬,等.提高地震图像信噪比的非线性各向异性扩散算法模型[J].石油勘探与开发,2004,31(2):77-80.Chen Feng,Li Jinzong,Li Dongdong,et al.A model of nonlinearanisotropic diffusion for increasing signal to noise ratio of seismicimage[J].Petroleum Exploration and Development,2004,31(2):77-80.
[12]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 aniso-tropic diffusion filtering technique[J].Oil Geophysical Prospec-ting,2004,39(6):651-655.
[13]项明,吴小培,汤婷,等.小波域中的PDE指纹图像增强[J].计算机工程与应用,2010,46(27):188-190.Xiang Ming,Wu Xiaopei,Tang Ting,et al.Fingerprint image en-hancement by directional diffusion PDE in wavelet domain[J].Computer Engineering and Applications,2010,46(27):188-190.
[14]钟勇,孙东,陈磊.图像增强技术在地震资料处理中的应用[J].物探与化探,2010,34(3):392-395.Zhong Yong,Sun Dong,Chen Lei.The application of the imageenhancement technology to seismic data processing[J].Geophys-ical&Geochemical Exploration,2010,34(3):392-395.
[15]王绪松,杨长春.对地震图像进行保边滤波的非线性各向异性扩散算法[J].地球物理学进展,2006,21(2):452-457.Wang Xusong,Yang Changchun.An edge-preserving smoothingalgorithm of seismic image using nonlinear anisotropic diffusionequation[J].Progress in Geophysics,2006,21(2):452-457.
[2]孟庆武,李成斌,李强,等.分形理论在高分辨处理中的应用[J].石油学报,2000,21(2):31-35.Meng Qingwu,Li Chengbin,Li Qiang,et al.Application of fractaltheory in high resolution processing of seismic data[J].Acta Pe-trolei Sinica,2000,21(2):31-35.
[3]Rudin L I,Osher S,Fatemi E.Nonlinear total variation based noiseremoval algorithms[J].Physica D:Nonlinear Phenomena,1992,60(1/2/3/4):259-268.
[4]Chambolle A,Lions P L.Image recovery via total variation mini-mization and related problems[J].Numerische Mathematik,1997,76(2):167-188.
[5]Chen Q,Montesinos P,Sun Q S,et al.Adaptive total variationdenoising based on difference curvature[J].Image and VisionComputing,2010,28(3):298-306.
[6]Chan T,Marquina A,Mulet P.High-order total variation-basedimage restoration[J].SIAM Journal on Scientific Computing,2000,22(2):503-516.
[7]李敏,冯象初.基于全变差和小波方法的图像去噪模型[J].西安电子科技大学学报:自然科学版,2006,33(6):980-984.Li Min,Feng Xiangchu.A denoising model using the total varia-tion and wavelet method[J].Journal of Xidian University,2006,33(6):980-984.
[8]余丽红,冯衍秋,陈武凡.基于自适应正则化的全变分去噪算法[J].中国图象图形学报,2009,14(10):1950-1954.Yu Lihong,Feng Yanqiu,Chen Wufan.Adaptive regularizationmethod based total variational de-noising algorithm[J].Journalof Image and Graphics,2009,14(10):1950-1954.
[9]Perona P,Malik J.Scale-space and edge detection using aniso-tropic diffusion[J].IEEE Transactions on Pattern Analysis andMachine Intelligence,1990,12(7):629-639.
[10]Weickert J.Coherence-enhancing,diffusion filtering[J].Interna-tional Journal of Computer Vision,1999,31(2/3):111-127.
[11]陈凤,李金宗,李冬冬,等.提高地震图像信噪比的非线性各向异性扩散算法模型[J].石油勘探与开发,2004,31(2):77-80.Chen Feng,Li Jinzong,Li Dongdong,et al.A model of nonlinearanisotropic diffusion for increasing signal to noise ratio of seismicimage[J].Petroleum Exploration and Development,2004,31(2):77-80.
[12]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 aniso-tropic diffusion filtering technique[J].Oil Geophysical Prospec-ting,2004,39(6):651-655.
[13]项明,吴小培,汤婷,等.小波域中的PDE指纹图像增强[J].计算机工程与应用,2010,46(27):188-190.Xiang Ming,Wu Xiaopei,Tang Ting,et al.Fingerprint image en-hancement by directional diffusion PDE in wavelet domain[J].Computer Engineering and Applications,2010,46(27):188-190.
[14]钟勇,孙东,陈磊.图像增强技术在地震资料处理中的应用[J].物探与化探,2010,34(3):392-395.Zhong Yong,Sun Dong,Chen Lei.The application of the imageenhancement technology to seismic data processing[J].Geophys-ical&Geochemical Exploration,2010,34(3):392-395.
[15]王绪松,杨长春.对地震图像进行保边滤波的非线性各向异性扩散算法[J].地球物理学进展,2006,21(2):452-457.Wang Xusong,Yang Changchun.An edge-preserving smoothingalgorithm of seismic image using nonlinear anisotropic diffusionequation[J].Progress in Geophysics,2006,21(2):452-457.
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