基于非因果滤波器的多次波匹配相减方法(英文)
|
摘要
在常规多道匹配滤波方法中的滤波器是物理可实现的因果滤波器,只能实现地震信号序列延迟的滤波。本文提出了最小二乘意义下的非因果多道输入多道输出维纳滤波方法,通过比较多道匹配相减中因果和非因果滤波方法之间的差别,验证了方法的有效性,解决了模型数据滞后于实际数据的情况。而且,通过定义长度随偏移距和层速度变化的滑动时窗,解决了匹配时窗内同相轴数量随偏移距增大而增加的问题。并将上述方法应用到改进的扩展多道匹配相减去除多次波的方法中,利用Pluto1.5理论模拟数据,对非因果滤波器和变长度时窗的匹配相减方法进行测试,取得了很好的去除多次波后的地震数据。
The filter operator used in normal multichannel matching filter is physically realizable. This filter operator only delays seismic data in the filtering process. A non- causal multichannel matching filter based on a least squares criterion is proposed to resolve the problem in which predicted multiple model data is later than real data. The differences between causal and non-causal multichannel matching filters are compared using a synthetic shot gather, which demonstrates the validity of the non-causal matching filter. In addition, a variable length sliding window which changes with offset and layer velocity is proposed to solve the count of events increasing with increasing offset in a fixed length sliding window. This variable length sliding window is also introduced into the modified and expanded multichannel matching filter. This method is applied to the Pluto1.5 synthetic data set. The benefits of the non-causal filter operator and variable length sliding window are demonstrated by the good multiple attenuation result.
The filter operator used in normal multichannel matching filter is physically realizable. This filter operator only delays seismic data in the filtering process. A non- causal multichannel matching filter based on a least squares criterion is proposed to resolve the problem in which predicted multiple model data is later than real data. The differences between causal and non-causal multichannel matching filters are compared using a synthetic shot gather, which demonstrates the validity of the non-causal matching filter. In addition, a variable length sliding window which changes with offset and layer velocity is proposed to solve the count of events increasing with increasing offset in a fixed length sliding window. This variable length sliding window is also introduced into the modified and expanded multichannel matching filter. This method is applied to the Pluto1.5 synthetic data set. The benefits of the non-causal filter operator and variable length sliding window are demonstrated by the good multiple attenuation result.
引文
Donno, D., Rocca, F., and Loinger, E., 2009, ICAseparation for improving multiple subtraction: 71stEAGE Conference and Exhibition, Expanded Abstracts,P157.
Fomel, S., 2009, Adaptive multiple subtraction usingregularized nonstationary regression: Geophysics, 74(1),V25 – V33.
Guitton, A., and Verchuur, D. J., 2004, The adaptivesubtraction of multiples using L1-norm: GeophysicalProspecting, 52, 27 – 38.
Huo, S. D., and Wang, Y., 2009, Improving adaptivesubtraction in seismic multiple attenuation: Geophysics,74(4), V59 – V67.
Liu, H. F., and Wang, Y. H., 2009, Modified multichannelmatching filters for seismic multiple attenuation: 71stEAGE Conference and Exhibition, Expanded Abstracts,P153.
Li, X., and Hu, T. Y., 2009, Surface-related multiple removal with inverse scattering series method: Chinese J.Geophys. (in Chinese), 52(6), 1633 – 1640.
Li, X. C., Liu, Y. K., Chang, X., and Li, P., 2010, Theadaptive subtraction of multiple using the equipoisemultichannel L1-norm matching: Chinese J. Geophys. (inChinese), 53 (4), 963-973.
Lu, W. K., 2006, Adaptive multiple subtraction usingindependent component analysis: Geophysics, 71(5),S179 – S184.
Monk, D. J., 1993, Wave-equation multiple suppressionusing constrained cross-equalization: GeophysicalProspecting, 41, 725 – 736.
Treitel, S., 1970, Principles of digital multichannel filtering:Geophysics, 35(5), 785 – 811.
Verschuur, D. J., Berkhout, A. J., and Wapenaar, C. P.,1992, Adaptive surface-related multiple elimination:Geophysics, 57(9), 1166 – 1177.
Wang, Y., 2003, Multiple subtraction using an expandedmultichannel matching filter: Geophysics, 68(1), 346 –354.
Weglein, A. B., Gasparotto, F. A., Carvalho, P. M., et al.,1997, An inverse-scattering series method for attenuatingmultiples in seismic reflection data: Geophysics, 62,1975 – 1989.
Fomel, S., 2009, Adaptive multiple subtraction usingregularized nonstationary regression: Geophysics, 74(1),V25 – V33.
Guitton, A., and Verchuur, D. J., 2004, The adaptivesubtraction of multiples using L1-norm: GeophysicalProspecting, 52, 27 – 38.
Huo, S. D., and Wang, Y., 2009, Improving adaptivesubtraction in seismic multiple attenuation: Geophysics,74(4), V59 – V67.
Liu, H. F., and Wang, Y. H., 2009, Modified multichannelmatching filters for seismic multiple attenuation: 71stEAGE Conference and Exhibition, Expanded Abstracts,P153.
Li, X., and Hu, T. Y., 2009, Surface-related multiple removal with inverse scattering series method: Chinese J.Geophys. (in Chinese), 52(6), 1633 – 1640.
Li, X. C., Liu, Y. K., Chang, X., and Li, P., 2010, Theadaptive subtraction of multiple using the equipoisemultichannel L1-norm matching: Chinese J. Geophys. (inChinese), 53 (4), 963-973.
Lu, W. K., 2006, Adaptive multiple subtraction usingindependent component analysis: Geophysics, 71(5),S179 – S184.
Monk, D. J., 1993, Wave-equation multiple suppressionusing constrained cross-equalization: GeophysicalProspecting, 41, 725 – 736.
Treitel, S., 1970, Principles of digital multichannel filtering:Geophysics, 35(5), 785 – 811.
Verschuur, D. J., Berkhout, A. J., and Wapenaar, C. P.,1992, Adaptive surface-related multiple elimination:Geophysics, 57(9), 1166 – 1177.
Wang, Y., 2003, Multiple subtraction using an expandedmultichannel matching filter: Geophysics, 68(1), 346 –354.
Weglein, A. B., Gasparotto, F. A., Carvalho, P. M., et al.,1997, An inverse-scattering series method for attenuatingmultiples in seismic reflection data: Geophysics, 62,1975 – 1989.
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心