基于迭代去噪的多源地震混合采集数据分离
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摘要
多源地震混合采集采用随机线性编码方式同时激发多个震源,检波器连续接收地震信号,获得波场混叠的炮记录.该采集技术能够显著提升采集效率和成像质量,其实现关键在于炮分离,即将相互混叠的多源波场数据彼此分离,获得传统采集的单炮记录.最小平方算法只能得到伪分离记录,不能去除混叠噪声.在高混合度的混叠数据中,混叠噪声的能量往往数倍于有效信号,炮分离难度倍增.但在伪分离记录中,该噪声在除共炮点道集以外的其它时域均为随机分布.本文研究提出了一种多时域组合迭代去噪的炮分离技术:通过运用多级中值滤波与Curvelet阈值迭代去噪算法,在不同时域根据混叠噪声特性采用相应的去噪手段,并设计迭代算法优化炮分离结果.实际资料处理结果证明:将本方法应用于高混合度的混叠数据,无论是分离质量还是计算效率,都有明显提升.
In multi-source blended seismic acquisition,different sources are shot in an overlapping fashion with certain time delays and blended records are acquired,so that both acquisition efficiency and image quality can be significantly improved.Deblending is the procedure of recovering data as if they were acquired in the conventional survey.A simple least-squares procedure is only able to get pseudodeblend results,where the blending noises cannot be removed.In high blending factor data,the blending noises are usually several times higher than the useful signals,which multiply the difficulty of source separation.Fortunately in pseudodeblend records,these noises are only coherent in the common source domain,but incoherent in other domains.For this character,multilevel median filter and Curvelet threshold iteration denoising are jointly used in this paper,and a new source separation method based on the iterative denoising in different domains is introduced.Depending on the different character of blending noises in different domains,corresponding denoising method is utilized,and an iteration method is designed for the optimization.While dealing with numerical blended real dataset,ideal results could be produced after only a few iterations,which verify that our method can largely improve the separation quality and calculation efficiency.
In multi-source blended seismic acquisition,different sources are shot in an overlapping fashion with certain time delays and blended records are acquired,so that both acquisition efficiency and image quality can be significantly improved.Deblending is the procedure of recovering data as if they were acquired in the conventional survey.A simple least-squares procedure is only able to get pseudodeblend results,where the blending noises cannot be removed.In high blending factor data,the blending noises are usually several times higher than the useful signals,which multiply the difficulty of source separation.Fortunately in pseudodeblend records,these noises are only coherent in the common source domain,but incoherent in other domains.For this character,multilevel median filter and Curvelet threshold iteration denoising are jointly used in this paper,and a new source separation method based on the iterative denoising in different domains is introduced.Depending on the different character of blending noises in different domains,corresponding denoising method is utilized,and an iteration method is designed for the optimization.While dealing with numerical blended real dataset,ideal results could be produced after only a few iterations,which verify that our method can largely improve the separation quality and calculation efficiency.
引文
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[23]Hennenfent G,Herrmann F J.Simply denoise:Wavefieldreconstruction via jittered undersampling.Geophysics,2008,73(3):V19-V28.
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[26]刘磊,刘振,张军华.曲波阈值法地震弱信号识别及去噪方法研究.地球物理学进展,2011,26(4):1415-1422.Liu L,Liu Z,Zhang J H.Denoising and detecting seismicweak signal based on curvelet thresholding method.Progressin Geophys.(in Chinese),2011,26(4):1415-1422.
[27]Berkhout A J.Seismic Migration:Imaging of AcousticEnergy by Wave Field Extrapolation.New York:ElsevierScientific Pub.Com.,1982.
[2]Beasley C J.A new look at marine simultaneous sources.TheLeading Edge,2008,27(7):914-917.
[3]Bagaini C.Overview of simultaneous vibroseis acquisitionmethods.76th Annual International Meeting,SEG,Expanded Abstracts,2006:70-74.
[4]Vaage S.Method and system for acquiring marine seismicdata using multiple sources.U.S.Patent 6906981B2,2002.
[5]Berkhout A J,Blacquière G,Verschuur D J.Changing themindset in seismic data acquisition.The Leading Edge,2008,27(7):924-938.
[6]Berkhout A J G,Blacquiere,Verschuur D J.The concept ofdouble blending:Combining incoherent shooting withincoherent sensing.Geophysics,2009,74(4):A59-A62.
[7]Blacquière G,Berkhout G,Verschuur E.Double illuminationin blended acquisition.81th Annual International Meeting,SEG,Expanded Abstracts,2011:11-15.
[8]佘德平.多震源地震正演数值模拟技术.地球物理学进展,2012,27(4):1533-1540.She D P.A numerical modeling of simultaneous sources.Progress in Geophys.(in Chinese),2012,27(4):1533-1540.
[9]陈生昌,马在田.广义地震数据合成及其偏移成像.地球物理学报,2006,49(4):1144-1149.Chen S C,Ma Z T.Generalized synthesis of seismic data andits migration.Chinese J.Geophys.(in Chinese),2006,49(4):1144-1149.
[10]陈生昌,王汉闯,陈林.三维VSP数据高效偏移成像的超道集方法.地球物理学报,2012,55(1):232-237.Chen S C,Wang H C,Chen L.A high efficient super-gathermigration method for 3DVSP data.Chinese J.Geophys.(inChinese),2012,55(1):232-237.
[11]Moore I,Dragoset W,Ommundsen T,et al.Simultaneoussource separation using dithered sources.78th AnnualInternational Meeting,SEG,Expanded Abstracts,2008:2806-2809.
[12]Akerberg P,Hampson G,Richett H,et al.Simultaneoussource separation by sparse radon transform.78th AnnualInternational Meeting,SEG,Expanded Abstracts,2008:2801-2804.
[13]Huo S D,Luo Y,Kelamis P,et al.Simultaneous sourcesseparation via multi-directional vector-median filter.79thAnnual International Meeting,SEG,Expanded Abstracts,2009:31-35.
[14]Doulgeris P,Mahdad A,Blacquiere G.Separation of blendedimpulsive sources using an iterative approach.72nd AnnualInternational Meeting,EAGE,Extended Abstracts,2010:B004.
[15]Mahdad A,Doulgeris P,Blacquiere G.Separation of blendeddata by iterative estimation and subtraction of blendinginterference noise.Geophysics,2011,76(3):Q9-Q17.
[16]Doulgeris P,Mahdad A,Blacquière G.Iterative separation ofblended marine data:discussion on the coherence-pass filter.81th Annual International Meeting,SEG,ExpandedAbstracts,2011:26-31.
[17]Tan C Q,Han L G,Zhang Y H,et al.Separation of blendeddata by iterative denoising.74nd Annual InternationalMeeting,EAGE,Extended Abstracts,2012:A045.
[18]Tan C,Han Q,LüY,et al.Separation of blended data bysparse inversion based on reciprocity theorem.Journal ofSeismic Exploration,2013,(in press).
[19]刘财,李红星,陶春辉等.模糊嵌套多级中值滤波方法及其在地震数据处理中的应用.地球物理学报,2007,50(5):1534-1542.Liu C,Li H X,Tao C H,et al.A new fuzzy nestingmultilevel median filter and its application to seismic dataprocessing.Chinese J.Geophys.(in Chinese),2007,50(5):1534-1542.
[20]刘洋,王典,刘财等.局部相关加权中值滤波技术及其在叠后随机噪声衰减中的应用.地球物理学报,2011,54(2):358-367.Liu Y,Wang D,Liu C,et al.Weighted median filter basedon local correlation and its application to poststack randomnoise attenuation.Chinese J.Geophys.(in Chinese),2011,54(2):358-367.
[21]王旭松,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.地球物理学进展,2006,21(2):452-457.Wang X S,Yang C C.An edge-preserving smoothingalgorithm of seismic image using nonlinear anisotropicdiffusion equation.Progress in Geophys.(in Chinese),2006,21(2):452-457.
[22]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.地球物理学进展,2010,25(3):866-870.Zhang E H,Wang W,Gao J H,et al.Non-linear anisotropicdiffusion filtering for 3Dseismic noise removal and structureenhancement.Progress in Geophys.(in Chinese),2010,25(3):866-870.
[23]Hennenfent G,Herrmann F J.Simply denoise:Wavefieldreconstruction via jittered undersampling.Geophysics,2008,73(3):V19-V28.
[24]Herrmann F J,Hennenfent G.Non-parametric seismic datarecovery with curvelet frames.Geophysical Journal International,2008,173(1):233-248.
[25]周怀来,李枚,郑文锋等.基于Curvelet变换的地震资料信噪分离技术.地球物理学进展,2009,24(2):620-625.Zhou H L,Li M,Zheng W F,et al.An approach to signalnoise separation of seismic data based on Curvelet transform.Progress in Geophys.(in Chinese),2009,24(2):620-625.
[26]刘磊,刘振,张军华.曲波阈值法地震弱信号识别及去噪方法研究.地球物理学进展,2011,26(4):1415-1422.Liu L,Liu Z,Zhang J H.Denoising and detecting seismicweak signal based on curvelet thresholding method.Progressin Geophys.(in Chinese),2011,26(4):1415-1422.
[27]Berkhout A J.Seismic Migration:Imaging of AcousticEnergy by Wave Field Extrapolation.New York:ElsevierScientific Pub.Com.,1982.
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