基于经验模态分解的地震相分析技术
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摘要
经验模态分解(EMD)方法是希尔伯特—黄变换的核心部分,可以将地震数据分解为多阶内蕴模态函数(IMF)分量,不同IMF分量具有不同的频率特性,不同的IMF分量对地震相的敏感程度不同,反映不同的地质信息。利用EMD方法结合kohonen神经网络的地震相分析可进行断层识别以及储层预测。文中将EMD方法应用于中国西部的实际地震资料分析,利用重构信号和分解得到的IMF分量进行波形地震相分析。模型试算和实际资料应用结果表明,用感兴趣的IMF分量能够重构信号,重构后的地震信号能够更加清晰地显示断层展布特征、有利储层范围等,提高了地震资料的信噪比和分辨率,对断层展布特征的认识和油气预测具有重要的参考价值。
The EMD method is the central part for Hilbert-Huang transform.With the method the seismic data can be decomposited into multi-order IMF components,different IMF component has different frequency characteristics which reflects different geological information.The seismic facies analysis which is based on the EMD method and the Kohonen neural network method can be used in fault identification and reservoir prediction.In this paper the EMD method was used in the field seismic data processing in the western of China,waveform seismic facies analysis was conducted based on the IMF components which were obtained by signal reconstruction and decomposition.The model trial calculation and application results of the field data show that using of the interested IMF component could reconstruct signal,and the reconstructed signals can better display fault distribution characteristics and favorite reservoir range,as well as raise both the signal to noise ratio and the resolution of the seismic data,they have important reference values for understanding the fault distribution characteristics and the reservoir prediction.
The EMD method is the central part for Hilbert-Huang transform.With the method the seismic data can be decomposited into multi-order IMF components,different IMF component has different frequency characteristics which reflects different geological information.The seismic facies analysis which is based on the EMD method and the Kohonen neural network method can be used in fault identification and reservoir prediction.In this paper the EMD method was used in the field seismic data processing in the western of China,waveform seismic facies analysis was conducted based on the IMF components which were obtained by signal reconstruction and decomposition.The model trial calculation and application results of the field data show that using of the interested IMF component could reconstruct signal,and the reconstructed signals can better display fault distribution characteristics and favorite reservoir range,as well as raise both the signal to noise ratio and the resolution of the seismic data,they have important reference values for understanding the fault distribution characteristics and the reservoir prediction.
引文
[1]Huang N E,Zheng Shen,Long S Ret al.The empir-ical mode decomposition and the Hilbert spectrumfor nonlinear and non-stationary ti me series analyses.Proc R Soc Lond,1998,454:903～995
[2]Huang N E,Wu M C,Long S R et al.Aconfidence li mit for the empirical mode decomposition and Hil-bert spectral analysis.Proc R Soc Lond,2003,459:2317～2345
[3]Huang N E,Man-Li Wu et al.Applications of Hil-bert-Huang transformto non-stationary financial ti me series analysis.Applied Stochastic Models In Busi-ness And Industry,2003,19:245～268
[4]Denis Donnelly.The Fast Fourier and Hilbert-Huang Transforms:A Comparison.International Journal of Computers,Communications&Control,2006,1(4):45～52
[5]Morlet J et al.Wave propagation and sampling theory-partz.Sampling Theory and Complex Waves,1982,47(2):222～236
[6]Yih Jeng,Ming-Juin Lin et al.Noise reduction and da-ta recovery for a VLF-EMsurvey using a nonlineardecomposition method.Geophysics,2007,72(5):F223～F235
[7]Maza Bekara,PGS,and Mirko van der Baan.Ran-domand coherent noise attenuation by empirical mode decomposition.SEG Technical Program Expanded Abstracts,2008,27:2591～2595
[8]Bradley Matthew Battista,Camelia Knapp et al.Ap-plication of the empirical mode decomposition and Hilbert-Huang transform to seismic reflection data.Geophysics,2001,66(1):294～307
[9]Paul A Hwang,Huang N E,Wang David W.Anote on analyzing nonlinear and nonstationary ocean wave data.Applied Ocean Research,2003,(25):187～193
[10]段生全,贺振华等.HHT方法及其在地震信号处理中的应用.成都理工大学学报(自然科学版),2005,32(4):396～400
[11]文晓涛,贺振华,黄德济.基于EMD与波形复杂性的储层识别.SEG论文详细摘要,2009:1213～1216
[12]Ivan Magrin-Chagnolleau and Richar d G.Empirical mode decomposition based ti me-frequency attributes.SEG Technical Program Expanded Abstracts,1999,18:73～91
[13]邹文,陈爱萍等.基于S变换的地震相分析技术.石油物探,2006,45(1):48～51
[14]于红枫,王英民等.Strati magic波形地震相分析在层序地层岩性生分析中的应用.煤田地质与勘探,2006,34(1):64～67
[15]吕景英.用波形分析法预测塔河油田碳酸盐岩储层.勘探地球物理进展,2004,27(2):112～116
[16]邓传伟,李莉华等.波形分类技术在储层沉积微相预测中的应用.石油物探,2008,47(3):262～266
[17]杨智春,谭光辉.一种基于样条插值的经验模态分解改进算法.西北工业大学报,2007,25(5):737～741
[2]Huang N E,Wu M C,Long S R et al.Aconfidence li mit for the empirical mode decomposition and Hil-bert spectral analysis.Proc R Soc Lond,2003,459:2317～2345
[3]Huang N E,Man-Li Wu et al.Applications of Hil-bert-Huang transformto non-stationary financial ti me series analysis.Applied Stochastic Models In Busi-ness And Industry,2003,19:245～268
[4]Denis Donnelly.The Fast Fourier and Hilbert-Huang Transforms:A Comparison.International Journal of Computers,Communications&Control,2006,1(4):45～52
[5]Morlet J et al.Wave propagation and sampling theory-partz.Sampling Theory and Complex Waves,1982,47(2):222～236
[6]Yih Jeng,Ming-Juin Lin et al.Noise reduction and da-ta recovery for a VLF-EMsurvey using a nonlineardecomposition method.Geophysics,2007,72(5):F223～F235
[7]Maza Bekara,PGS,and Mirko van der Baan.Ran-domand coherent noise attenuation by empirical mode decomposition.SEG Technical Program Expanded Abstracts,2008,27:2591～2595
[8]Bradley Matthew Battista,Camelia Knapp et al.Ap-plication of the empirical mode decomposition and Hilbert-Huang transform to seismic reflection data.Geophysics,2001,66(1):294～307
[9]Paul A Hwang,Huang N E,Wang David W.Anote on analyzing nonlinear and nonstationary ocean wave data.Applied Ocean Research,2003,(25):187～193
[10]段生全,贺振华等.HHT方法及其在地震信号处理中的应用.成都理工大学学报(自然科学版),2005,32(4):396～400
[11]文晓涛,贺振华,黄德济.基于EMD与波形复杂性的储层识别.SEG论文详细摘要,2009:1213～1216
[12]Ivan Magrin-Chagnolleau and Richar d G.Empirical mode decomposition based ti me-frequency attributes.SEG Technical Program Expanded Abstracts,1999,18:73～91
[13]邹文,陈爱萍等.基于S变换的地震相分析技术.石油物探,2006,45(1):48～51
[14]于红枫,王英民等.Strati magic波形地震相分析在层序地层岩性生分析中的应用.煤田地质与勘探,2006,34(1):64～67
[15]吕景英.用波形分析法预测塔河油田碳酸盐岩储层.勘探地球物理进展,2004,27(2):112～116
[16]邓传伟,李莉华等.波形分类技术在储层沉积微相预测中的应用.石油物探,2008,47(3):262～266
[17]杨智春,谭光辉.一种基于样条插值的经验模态分解改进算法.西北工业大学报,2007,25(5):737～741
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