基于奇异值分解的倾角扫描叠加
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摘要
奇异值分解(SVD)法是地震数据处理的新手段之一,但SVD法只能增强水平同相轴而不能有效地增强非水平同相轴。为此,提出了基于SVD的倾角扫描叠加方法。该方法根据地震剖面选择一组线性时移参数(即倾角扫描参数),将地震数据进行线性时移,然后用SVD法提取信号,再作反线性时移以恢复原时间坐标,将其结果叠加作为最终输出。该方法在同时存在水平、非水平同相轴的情况下,能较好地提高信噪比。采用合成地震资料进行的试算表明,效果良好,方法是可行的。此外,还讨论了该方法用于实际资料处理时应注意的问题。图3参9
Singular value decomposition (SVL)) is one of the new approaches in seismic data processing, nevertheless. it can't enhance non-horizontal events effectively; and thus there is introduced in this paper a dip-scanning stacking method on the basis of SVD. A group of (dip-scanning) parameters for linear time shift is selected according to seismic data for each dip. Then the data are filtered using SVD method, and inverse linear time shift is applied to restore the data to their original coordinates Finally. the results from all dips are added to form the final output data. The method can enhance signal-to-noise ratio whether there are horizontal or non-horizontal events in the data. The computed result of the synthetic data demonstrates the feasibility and effectiveness of the method. A discussion is presented also on some other relative problems in actual data processing.
Singular value decomposition (SVL)) is one of the new approaches in seismic data processing, nevertheless. it can't enhance non-horizontal events effectively; and thus there is introduced in this paper a dip-scanning stacking method on the basis of SVD. A group of (dip-scanning) parameters for linear time shift is selected according to seismic data for each dip. Then the data are filtered using SVD method, and inverse linear time shift is applied to restore the data to their original coordinates Finally. the results from all dips are added to form the final output data. The method can enhance signal-to-noise ratio whether there are horizontal or non-horizontal events in the data. The computed result of the synthetic data demonstrates the feasibility and effectiveness of the method. A discussion is presented also on some other relative problems in actual data processing.
引文
1 谢凤兰.赵改善.利用SVD法重建地震剖面.石油物探,1990:29(4) :33～40
2 Freire S L, Ulrych T J. Application of singular value decomposition to vertical seismic profiling. Geophysics, 1988; 53(6) : 778～785
3 Key S C, Smithson S B. New approach to seismic-reflection event detection and velocity determination. Geophysics, 1990; 55(8) : 1057-1067
4 Uerych T J, Freire S, Siston P.地震剖面的本征图象处理.见:SEG第58届年会论文集,北京:石油工业出版社,1989:646～650
5 Jackson G M, Mason I M, Greenhalgh S A. Principle component transforms of triaxial recordings by singular value decomposition. Geophysics, 1991; 56(4) : 528～523
6 夏江海.奇异值分解在位场资料处理中的应用.物探化探计算技术,1989;11(2) :93～98
7 黄皓平.电磁法数据处理的奇异值分解法.地球物理学报,1991;34(5) :644～650
8 陈遵德.一种提取声波全渡信号的新方法--奇异值分解法.地球物理测井,1991;15(1) :29～33
9 Al-yahya K M. Application of the partial Karhunen-Loeve transform to suppress random noise in seismic sections. Geophysical Prospecting, 1991; 39: 77～93
2 Freire S L, Ulrych T J. Application of singular value decomposition to vertical seismic profiling. Geophysics, 1988; 53(6) : 778～785
3 Key S C, Smithson S B. New approach to seismic-reflection event detection and velocity determination. Geophysics, 1990; 55(8) : 1057-1067
4 Uerych T J, Freire S, Siston P.地震剖面的本征图象处理.见:SEG第58届年会论文集,北京:石油工业出版社,1989:646～650
5 Jackson G M, Mason I M, Greenhalgh S A. Principle component transforms of triaxial recordings by singular value decomposition. Geophysics, 1991; 56(4) : 528～523
6 夏江海.奇异值分解在位场资料处理中的应用.物探化探计算技术,1989;11(2) :93～98
7 黄皓平.电磁法数据处理的奇异值分解法.地球物理学报,1991;34(5) :644～650
8 陈遵德.一种提取声波全渡信号的新方法--奇异值分解法.地球物理测井,1991;15(1) :29～33
9 Al-yahya K M. Application of the partial Karhunen-Loeve transform to suppress random noise in seismic sections. Geophysical Prospecting, 1991; 39: 77～93
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