基于NBICA的盲反卷积方法
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摘要
在线性系统假设下,根据地震记录估计地震子波和反射系数序列是一个典型的盲反卷积过程。针对带状独立分量分析反卷积方法对噪声敏感的缺点,提出一种的基于高斯矩的噪声带状独立分量分析反卷积方法,并利用邻近道间的相关信息实施子波提取。实验结果表明,对于带噪地震数据的盲反卷积,该算法性能更优。
On the hypothesis of linear system,it is a typical process of blind deconvolution for the estimation of seismic wavelet and reflectivity sequence with the observations.As sensitivity to noise for Banded Independent Component Analysis(BICA),a method called Noisy Banded Independent Component Analysis(NBICA) based on Gaussian moment is proposed,with its robustness to noise.The information between adjacent seismic traces is used for wavelet extraction.Experimental result shows that the efficiency of the method is better.
On the hypothesis of linear system,it is a typical process of blind deconvolution for the estimation of seismic wavelet and reflectivity sequence with the observations.As sensitivity to noise for Banded Independent Component Analysis(BICA),a method called Noisy Banded Independent Component Analysis(NBICA) based on Gaussian moment is proposed,with its robustness to noise.The information between adjacent seismic traces is used for wavelet extraction.Experimental result shows that the efficiency of the method is better.
引文
[1]刘喜武,刘洪.地震盲反卷积综述[J].地球物理学进展,2003,18(2):203-209.
[2]Wiggings R A.Minimum Entropy Deconvolution[J].Geoexploration,1978,16(1):21-35.
[3]陆文凯,骆毅,赵波,等.基于独立分量分析的多次波自适应相减技术[J].地球物理学报,2004,47(5):886-891.
[4]Kaplan S T,Ulrych T J.Blind Deconvolution and ICA with a Banded Mixing Matrix[C]//Proc.of the4th International Symposium on ICA and Blind Signal Separation.Nara,Japan:[s.n.],2003:223-228.
[5]Al-Qaisi A,Woo W L,Dlay S S.Blind Seismic Deconvolution of Single Channel Using Instantaneous Independent Component Analysis[C]//Proc.of the6th International Symposium on Communication Systems,Networks and Digital Signal Processing.Graz,Austria:[s.n.],2008:142-146.
[6]刘喜武,高伟,张宁,刘婉莹.基于带状混合矩阵ICA实现地震盲反卷积[J].地球物理学进展,2007,22(4):1153-1163.
[7]Hyvarinen A.Fast ICA for Noisy Data Using Gaussian Mom-ents[C]//Proc.of IEEE International Symposium on Circuits and Systems.Seattle,Washington,USA:IEEE Press,1999:57-61.
[8]Hyvarinen A.Fast and Robust Fixed-point Algorithms for Independent Component Analysis[J].IEEE Transactions on Neural Networks,1999,10(3):626-634.
[9]Fiori S,Tanaka T.An Averaging Method for a Committee of Special-orthogonal-group Machines[C]//Proc.of IEEE International Symposium on Circuits and Systems.Seattle,Washington,USA:IEEE Press,2008:2170-2173.
[2]Wiggings R A.Minimum Entropy Deconvolution[J].Geoexploration,1978,16(1):21-35.
[3]陆文凯,骆毅,赵波,等.基于独立分量分析的多次波自适应相减技术[J].地球物理学报,2004,47(5):886-891.
[4]Kaplan S T,Ulrych T J.Blind Deconvolution and ICA with a Banded Mixing Matrix[C]//Proc.of the4th International Symposium on ICA and Blind Signal Separation.Nara,Japan:[s.n.],2003:223-228.
[5]Al-Qaisi A,Woo W L,Dlay S S.Blind Seismic Deconvolution of Single Channel Using Instantaneous Independent Component Analysis[C]//Proc.of the6th International Symposium on Communication Systems,Networks and Digital Signal Processing.Graz,Austria:[s.n.],2008:142-146.
[6]刘喜武,高伟,张宁,刘婉莹.基于带状混合矩阵ICA实现地震盲反卷积[J].地球物理学进展,2007,22(4):1153-1163.
[7]Hyvarinen A.Fast ICA for Noisy Data Using Gaussian Mom-ents[C]//Proc.of IEEE International Symposium on Circuits and Systems.Seattle,Washington,USA:IEEE Press,1999:57-61.
[8]Hyvarinen A.Fast and Robust Fixed-point Algorithms for Independent Component Analysis[J].IEEE Transactions on Neural Networks,1999,10(3):626-634.
[9]Fiori S,Tanaka T.An Averaging Method for a Committee of Special-orthogonal-group Machines[C]//Proc.of IEEE International Symposium on Circuits and Systems.Seattle,Washington,USA:IEEE Press,2008:2170-2173.
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