基于改进EMD的地震信号去噪
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摘要
压制随机噪声是地震数据处理过程中的一个重要环节,目前大多数去噪技术都不同程度存在去噪效果差、易损伤有效信号等问题。利用经验模态分解可将信号自适应地分解为不同特征尺度固有模态函数的优点,及小波变换模极大值滤波方法对噪声的依赖性较小且适合于低信噪比信号去噪的优势,构造了一种经验模态分解与小波变换模极大值相结合的新的去噪算法,该算法很好地实现了地震有效信号与随机噪声的分离,有效提高了地震数据信噪比。将该算法应用于仿真实验和实际地震数据处理,结果都表明该方法明显优于常规经验模态分解去噪效果。
Random noise attenuation is an important step in seismic data processing;however,most random noise attenuation methods have some problems such as poor de-noising effect and damaging effective signals to a certain degree.Empirical Mode Decomposition(EMD)can self-adaptively decompose the signal into multi-scale Intrinsic Mode Function(IFM)and wavelet transform modulus maxima de-noising method is available for low S/N signals.We construct a new random noise attenuation algorithm by combining EMD with wavelet transform modulus maxima de-noising method,which can effectively separate signals form random noise and well improve signal to noise ratio(S/N)of seismic data.The algorithm is applied on numerical simulation and field data for random noise attenuation.The results reveals that the de-noising effect of new algorithm is obviously better than that of conventional EMD.
Random noise attenuation is an important step in seismic data processing;however,most random noise attenuation methods have some problems such as poor de-noising effect and damaging effective signals to a certain degree.Empirical Mode Decomposition(EMD)can self-adaptively decompose the signal into multi-scale Intrinsic Mode Function(IFM)and wavelet transform modulus maxima de-noising method is available for low S/N signals.We construct a new random noise attenuation algorithm by combining EMD with wavelet transform modulus maxima de-noising method,which can effectively separate signals form random noise and well improve signal to noise ratio(S/N)of seismic data.The algorithm is applied on numerical simulation and field data for random noise attenuation.The results reveals that the de-noising effect of new algorithm is obviously better than that of conventional EMD.
引文
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[12]王婷.EMD算法研究及其在信号去噪中的应用[D].哈尔滨:哈尔滨工程大学出版社,2010.
[13]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 inseismicdatanoiseattenuation[J].ProgressinGeophysics,2008,23(2):493–499.
[14]张孝珍,董汉强,侯国文,等.地震勘探中的去噪技术新进展[J].勘探地球物理进展,2009,32(3):172–178.Zhang Xiaozhen,Dong Hanqiang,Hou Guowen,etal.Advances in denoising technology in seismic ex-ploration[J].Progress in Exploration Geophysics,2009,32(3):172–178.
[15]Wu Z H,Huang N E.A study of the characteristicsof white noise using the empirical mode decomposi-tion method[J].Proc.Roy.Soc.London 460A,2004:1597–1611.
[16]Mijovic B,De Vos M,Gligorijevic I,et al.Source sepa-ration from single-channel recordings by combining em-pirical mode decomposition and independent componentanalysis[J].IEEE Transaction on Biomedical Engineer-ing.2010,57(9):2188–2196.
[17]段生全,贺振华,黄德济.HHT方法及其在地震信号处理中的应用[J].成都理工大学学报:自然科学版,2005,32(4):396–400.Duan Shengquan,He Zhenhua,Huang Deji.Applicationof the Hilbert-Huang Transform to the analysis of seismicsignal[J].Journal of Chengdu University of Technology:Science&Technology Edition,2005,32(4):396–400.
[18]杨培杰,印兴耀,张广智.希尔伯特–黄变换地震信号时频分析与属性提取[J].地球物理学进展,2007,22(5):1585–1590.Yang Peijie,Yin Xingyao,Zhang Guangzhi.Seismicsignal time-frequency analysis and attributes extractionbased on HHT[J].Progress in Geophysics,2007,22(5):1585–1590.
[19]葸晓宇,刘洪.HHT方法在研究地震旋回体中的应用[J].吉林大学学报:地球科学版,2007,37(3):624–628.Xi Xiaoyu,Liu Hong.The application of HHT method instudyofseismiccycle[J].JournalofJilinUniversity:EarthScience Edition,2007,37(3):624–628.
[20]石春香,罗奇峰.时程信号的Hilbert-Huang变换与小波分析[J].地震学报,2003,25(4):398–405.Shi Chunxiang,Luo Qifeng.Hilbert-Huang Transformand wavelet analysis of time history signal[J].Acta Seis-mologica Sinica,2003,25(4):398–405.
[21]张军华,臧胜涛,周振晓,等.地震资料信噪比定量技术及方法比较[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 ratioin seismic data[J].Oil Geophysical Prospecting,2009,44(4):481–486.
[2]苏贵士,周兴元,李承楚.频率空间(三维)F–XYZ域预测去噪技术[J].石油地球物理勘探,1998,33(1):95–103.Su Guishi,Zhou Xingyun,Li Chengchu.Predictionnoise elimination in F–XYZ domain[J].Oil GeophysicalProspecting,1998,33(1):95–103.
[3]康治,于承业,贾卧,等.f x域去噪方法研究[J].石油地球物理勘探,2003,38(2):136–138.Kang Zhi,Yu Chengye,Jia Wo,et al.A study on noisesuppression method in f x domain[J].Oil GeophysicalProspecting,2003,38(2):136–138.
[4]Canales L L.Random noise reduction.SEG 1984:54th SEG Annual Meeting Expanded Abstracts[C/OL].http://dx.doi.org/10.1190/1.1894168.
[5]巩向博,韩立国,王恩利,等.压制噪声的高分辨率Radon变换法[J].吉林大学学报:地球科学版,2009,39(1):152–157.Gong Xiangbo,Han Liguo,Wang Enli,et al.Denoisingvia high resolution Radon transform[J].Journal of Jilin U-niversity:Earth Science Edition,2009,39(1):152–157.
[6]Yu S,Cai X,Su Y.Seismic signal enhancement by poly-nomial fitting[J].Applied Geophysics,1989,1:57–65.
[7]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.GaoJinghuai,MaoJian,ManWeishi,etal.Onthedenois-ing method of prestack seismic data in wavelet domain[J].Chinese J.Geophysics,2006,49(4):1155–1163.
[8]张军华,吕宁,田连玉,等.地震资料去噪方法综合评述[J].石油地球物理勘探,2005,40(S1):121–127.Zhang Junhua,LüNing,Tian Lianyu,et al.An overviewofthemethodsandtechniquesforseismicdatanoiseatten-uation[J].Oil Geophysical Prospecting,2005,40(S1):121–127.
[9]Battistal B M,Knapp C,McGee T,et al.Applicationof the empirical mode decomposition and Hilbert-Huangtransformtoseismicreflectiondata[J].Geophysics,2007,72(2):29–37.
[10]Huang N E,Zheng S.The empirical mode decompositionand the hilbert spectrum for nonlinear and non-stationarytime series analysis[J].Proc.R.Soc.Lond.A,1998,454:903–995.
[11]Wu Z,Huang N E.Ensemble empirical mode decomposi-tion:a noise–assisted data analysis method[J].Advancesin Adaptive Data Analysis,2009,1(1):1–41.
[12]王婷.EMD算法研究及其在信号去噪中的应用[D].哈尔滨:哈尔滨工程大学出版社,2010.
[13]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 inseismicdatanoiseattenuation[J].ProgressinGeophysics,2008,23(2):493–499.
[14]张孝珍,董汉强,侯国文,等.地震勘探中的去噪技术新进展[J].勘探地球物理进展,2009,32(3):172–178.Zhang Xiaozhen,Dong Hanqiang,Hou Guowen,etal.Advances in denoising technology in seismic ex-ploration[J].Progress in Exploration Geophysics,2009,32(3):172–178.
[15]Wu Z H,Huang N E.A study of the characteristicsof white noise using the empirical mode decomposi-tion method[J].Proc.Roy.Soc.London 460A,2004:1597–1611.
[16]Mijovic B,De Vos M,Gligorijevic I,et al.Source sepa-ration from single-channel recordings by combining em-pirical mode decomposition and independent componentanalysis[J].IEEE Transaction on Biomedical Engineer-ing.2010,57(9):2188–2196.
[17]段生全,贺振华,黄德济.HHT方法及其在地震信号处理中的应用[J].成都理工大学学报:自然科学版,2005,32(4):396–400.Duan Shengquan,He Zhenhua,Huang Deji.Applicationof the Hilbert-Huang Transform to the analysis of seismicsignal[J].Journal of Chengdu University of Technology:Science&Technology Edition,2005,32(4):396–400.
[18]杨培杰,印兴耀,张广智.希尔伯特–黄变换地震信号时频分析与属性提取[J].地球物理学进展,2007,22(5):1585–1590.Yang Peijie,Yin Xingyao,Zhang Guangzhi.Seismicsignal time-frequency analysis and attributes extractionbased on HHT[J].Progress in Geophysics,2007,22(5):1585–1590.
[19]葸晓宇,刘洪.HHT方法在研究地震旋回体中的应用[J].吉林大学学报:地球科学版,2007,37(3):624–628.Xi Xiaoyu,Liu Hong.The application of HHT method instudyofseismiccycle[J].JournalofJilinUniversity:EarthScience Edition,2007,37(3):624–628.
[20]石春香,罗奇峰.时程信号的Hilbert-Huang变换与小波分析[J].地震学报,2003,25(4):398–405.Shi Chunxiang,Luo Qifeng.Hilbert-Huang Transformand wavelet analysis of time history signal[J].Acta Seis-mologica Sinica,2003,25(4):398–405.
[21]张军华,臧胜涛,周振晓,等.地震资料信噪比定量技术及方法比较[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 ratioin seismic data[J].Oil Geophysical Prospecting,2009,44(4):481–486.
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