基于广义S变换和JADE算法的储层识别
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摘要
广义S变换具有良好的时频聚集性,能够获得反映储层性质的时频谱,但由此生成许多单频数据体,造成地震数据的分析和解释工作变得繁琐。为此,将广义S变换和特征矩阵联合近似对角化(JADE)算法相结合,进行储层识别。在时间域内对地震信号做广义S变换,然后在时频域内提取一些相互独立的有效频率分量,最后根据已知井的储层发育情况,选取对储层识别有效的频段分量进行储层预测。仿真和实际地震数据应用结果表明了该方法的有效性。
Generalized S Transform(GST)has good time-frequency focusing, and can obtain time-frequency spectrum for reflecting the properties of reservoir.However,the procedure will produce many single-frequency data bodies,which complicates the seismic data processing and interpretation subsequently.Therefore,we combined GST with Joint Approximate Diagonalization of Eigenmatrix (JADE)to identify reservoir.GST was proceeded on seismic signals in time domain.Then,some independent effective frequency components were extracted in time-frequency domain.Finally,by using the reservoir development information of some known wells, the frequency band components effectively for reservoir identification were selected for reservoir prediction.The simulation and actual application results show the validity of the method.
Generalized S Transform(GST)has good time-frequency focusing, and can obtain time-frequency spectrum for reflecting the properties of reservoir.However,the procedure will produce many single-frequency data bodies,which complicates the seismic data processing and interpretation subsequently.Therefore,we combined GST with Joint Approximate Diagonalization of Eigenmatrix (JADE)to identify reservoir.GST was proceeded on seismic signals in time domain.Then,some independent effective frequency components were extracted in time-frequency domain.Finally,by using the reservoir development information of some known wells, the frequency band components effectively for reservoir identification were selected for reservoir prediction.The simulation and actual application results show the validity of the method.
引文
[1]张贤达.现代信号处理[M].北京:清华大学出版社, 2002:1-528
[2]Stockwell R G,Mansinha L,Lowe R P.Localization of the complex spectrum:the S transform[J].IEEE Transactions on Signal Processing,1996,44(4):998-1001
[3]Pinnegar C R,Mansinha L.The S-transform with ??windows of arbitrary and varying shape[J].Geophysics, 2003,68(1):381-385
[4]McFadden P D.Cook J G,Forster L M.Decomposition of Gear vibration signals by generalized S transform [J].Mechanical Systems and Signal Processing, 1999,13(5):691-707
[5]高静怀,陈文超,李幼铭,等.广义S变换与薄互层地震响应[J].地球物理学报,2003,46(4):526-532
[6]邹文,陈爱萍,贺振华,等.基于S变换的地震相分析技术[J].石油物探,2006,45(1):48-51
[7]Pinnegar C R,Eaton D W.Application of the S transform to prestack noise attenuation filtering [J].Journal of Geophysical Research,2003,108 (B9):1-10
[8]刘喜武,刘洪,李幼铭,等.基于广义S变换研究地震地层特征[J].地球物理学进展,2006,21(2): 440-451
[9]Comon P.Independent component analysis,a new concept[J].Signal Processing,1994,36(3):287-314
[10]Herault J,Jutten C.Space or time adaptive signal processing by Neural Network Models[C]//In: Denker J S.Nural Network for computing:AIP Conference Proceedings 151,New York:American Institute for Physics,1986,206-211
[11]Comen P.Independent component analysis,a new concept?[J].Signal Processing,1994,36(3): 287-314
[12]Lee T W,Girolami M,Sejnowski T J.Independent component analysis using an extended Infomax algorithm for mixed sub-Gaussian and super-Gaussian source[J].Neural Computation,1999,11(2): 417-441
[13]Cardoso J F,Souloumiac A.Blind beamforming for non-Gaussian signals[J].IEE Proceedings,Part F: Radar and Signal Processing,1993,140(6):362-370
[14]Cardoso J F.Higher order contrasts for independent component analysis[J].Neural Computation,1999, 11(1):157-192
[15]Li Z S.Guo X B.Predicting the distribution of thin bed reservoirs by broad frequency band seismic[J]. Applied Geophysics,2008,4(2):118-126
[2]Stockwell R G,Mansinha L,Lowe R P.Localization of the complex spectrum:the S transform[J].IEEE Transactions on Signal Processing,1996,44(4):998-1001
[3]Pinnegar C R,Mansinha L.The S-transform with ??windows of arbitrary and varying shape[J].Geophysics, 2003,68(1):381-385
[4]McFadden P D.Cook J G,Forster L M.Decomposition of Gear vibration signals by generalized S transform [J].Mechanical Systems and Signal Processing, 1999,13(5):691-707
[5]高静怀,陈文超,李幼铭,等.广义S变换与薄互层地震响应[J].地球物理学报,2003,46(4):526-532
[6]邹文,陈爱萍,贺振华,等.基于S变换的地震相分析技术[J].石油物探,2006,45(1):48-51
[7]Pinnegar C R,Eaton D W.Application of the S transform to prestack noise attenuation filtering [J].Journal of Geophysical Research,2003,108 (B9):1-10
[8]刘喜武,刘洪,李幼铭,等.基于广义S变换研究地震地层特征[J].地球物理学进展,2006,21(2): 440-451
[9]Comon P.Independent component analysis,a new concept[J].Signal Processing,1994,36(3):287-314
[10]Herault J,Jutten C.Space or time adaptive signal processing by Neural Network Models[C]//In: Denker J S.Nural Network for computing:AIP Conference Proceedings 151,New York:American Institute for Physics,1986,206-211
[11]Comen P.Independent component analysis,a new concept?[J].Signal Processing,1994,36(3): 287-314
[12]Lee T W,Girolami M,Sejnowski T J.Independent component analysis using an extended Infomax algorithm for mixed sub-Gaussian and super-Gaussian source[J].Neural Computation,1999,11(2): 417-441
[13]Cardoso J F,Souloumiac A.Blind beamforming for non-Gaussian signals[J].IEE Proceedings,Part F: Radar and Signal Processing,1993,140(6):362-370
[14]Cardoso J F.Higher order contrasts for independent component analysis[J].Neural Computation,1999, 11(1):157-192
[15]Li Z S.Guo X B.Predicting the distribution of thin bed reservoirs by broad frequency band seismic[J]. Applied Geophysics,2008,4(2):118-126
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