谱反演在地震属性解释中的应用
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摘要
任何一个反射系数序列都可以分解成奇、偶分量,奇分量不利于检测薄层,而少量的偶分量可以提高薄层的分辨能力,谱反演的实质就是利用偶分量在厚度趋于零时的有效干涉提高地震资料的分辨率。谱反演是在谱分解的基础上,通过反演方法使频率域目标函数达到极小而反演出反射系数、薄层厚度,在没有噪声和地震子波已知的情况下,可以识别任意薄层,并精确地反演出反射系数值。其主要特点是只采用部分频谱资料就可反演稀疏反射系数或层厚。文中利用谱反演方法对大庆油田的三维地震数据体进行了反演,得到反射系数体,并用该反射系数体与给定的宽频带子波褶积,得到提高分辨率后的地震数据体,再对其进行地震属性分析。与常规资料的地震属性分析结果相比,应用谱反演方法可提高识别沉积相和小断层的能力。
Any reflection coefficient sequence can be decomposed into odd and even components.The odd components are not conducive to detect thin beds,while a few even components can improve the thin bed identification.The essential of spectral inversion improves the seismic data resolution using the effective interference of the even components when the thin-bed thickness tends to zero.Using an inverse method to acquire a minimum objective function of the frequency domain with noise free and known seismic wavelet,spectral inversion based on the spectral decomposition gets reflection coefficient and identify any thin-bed thickness.The main feature of the method is that sparse reflection coefficient or thickness could be inversed using only part of the spectrum information.The application of this spectral inversion method in a 3D seismic data volume from Daqing Oilfield obtains a reflection coefficient set.Then the resolution of the 3D seismic data volume is improved by the given broad-band wavelet convolution with the reflection coefficient set.Finally,seismic attribute interpretation is performed.Compared with the conventional seismic attribute analysis,this spectral inversion method can improve sedimentary facies and small fault identifications.
Any reflection coefficient sequence can be decomposed into odd and even components.The odd components are not conducive to detect thin beds,while a few even components can improve the thin bed identification.The essential of spectral inversion improves the seismic data resolution using the effective interference of the even components when the thin-bed thickness tends to zero.Using an inverse method to acquire a minimum objective function of the frequency domain with noise free and known seismic wavelet,spectral inversion based on the spectral decomposition gets reflection coefficient and identify any thin-bed thickness.The main feature of the method is that sparse reflection coefficient or thickness could be inversed using only part of the spectrum information.The application of this spectral inversion method in a 3D seismic data volume from Daqing Oilfield obtains a reflection coefficient set.Then the resolution of the 3D seismic data volume is improved by the given broad-band wavelet convolution with the reflection coefficient set.Finally,seismic attribute interpretation is performed.Compared with the conventional seismic attribute analysis,this spectral inversion method can improve sedimentary facies and small fault identifications.
引文
[1]李庆忠.地震高分辨率勘探中的误区与对策.石油地球物理勘探,1997,32(6):751～783Li Qingzhong.Some mistaken concepts in high-reso-lution seismic exploration and the correspondingcountermeasures.OGP,1997,32(6):751～783
[2]Portniaguine O and Castagna J P.Spectral inversion:Lessons from modeling and Boonesville case study.SEG Technical Program Expanded Abstracts,2005,24:1638～1641
[3]Chopra S,Castagna J P,Portniaguine O.Seismic reso-lution and thin-bed reflectivity inversion.CSEG Re-corder,2006,19～25
[4]Puryear C and Castagna J P.Layer-thickness determi-nation and stratigraphic interpretation using spectralinversion:Theory and application.Geophysics,2008,73(2):37～48
[5]Yuan S Y,Wang S X and Tian N.Swarm intelligenceoptimization and its application in geophysical data in-version.Applied Geophysics,2009,6(2):166～174
[6]Yuan S Y,Wang S X,Yu Y C et al.Ill-posed analy-sis for spectral inversion.SEG Technical ProgramExpanded Abstracts,2009,28:2447～2451
[7]Yuan S Y,Wang S X and Zhang W Y.Reflectivity in-version based on sparse Bayesian learning.73rd An-nual International Meeting,EAGE,Expanded Ab-stracts,2011,ID:10118
[8]Yuan S Y,Wang S X and Li G F.Random noise re-duction using Bayesian inversion.Journal of Geo-physics and Engineering,2012,9(1):60～68
[9]Chopra S,Castagna J P,Y Xu.Thin-bed reflectivityinversion and some applications.First Break,2009,27(5):17～24
[10]李阳,李占东,于亚楠等.相干体技术识别小断层.油气地球物理,2009,7(2):25～28Li Yang,Li Zhandong,Yu Yanan et al.Identifyingsmall faults by coherent body technique.PetroleumGeophysics,2009,7(2):25～28
[11]王志君,黄军斌.利用相干技术和三维可视化技术识别微小断层和砂体.石油地球物理勘探,2001,36(3):378～381Wang Zhijun and Huang Junbin.Identification of mi-cro-fault and sand body by using coherence techniqueand 3-D visualization.OGP,2001,36(3):378～381
[12]王永刚.地震资料综合解释方法.山东东营:中国石油大学出版社,2006
[2]Portniaguine O and Castagna J P.Spectral inversion:Lessons from modeling and Boonesville case study.SEG Technical Program Expanded Abstracts,2005,24:1638～1641
[3]Chopra S,Castagna J P,Portniaguine O.Seismic reso-lution and thin-bed reflectivity inversion.CSEG Re-corder,2006,19～25
[4]Puryear C and Castagna J P.Layer-thickness determi-nation and stratigraphic interpretation using spectralinversion:Theory and application.Geophysics,2008,73(2):37～48
[5]Yuan S Y,Wang S X and Tian N.Swarm intelligenceoptimization and its application in geophysical data in-version.Applied Geophysics,2009,6(2):166～174
[6]Yuan S Y,Wang S X,Yu Y C et al.Ill-posed analy-sis for spectral inversion.SEG Technical ProgramExpanded Abstracts,2009,28:2447～2451
[7]Yuan S Y,Wang S X and Zhang W Y.Reflectivity in-version based on sparse Bayesian learning.73rd An-nual International Meeting,EAGE,Expanded Ab-stracts,2011,ID:10118
[8]Yuan S Y,Wang S X and Li G F.Random noise re-duction using Bayesian inversion.Journal of Geo-physics and Engineering,2012,9(1):60～68
[9]Chopra S,Castagna J P,Y Xu.Thin-bed reflectivityinversion and some applications.First Break,2009,27(5):17～24
[10]李阳,李占东,于亚楠等.相干体技术识别小断层.油气地球物理,2009,7(2):25～28Li Yang,Li Zhandong,Yu Yanan et al.Identifyingsmall faults by coherent body technique.PetroleumGeophysics,2009,7(2):25～28
[11]王志君,黄军斌.利用相干技术和三维可视化技术识别微小断层和砂体.石油地球物理勘探,2001,36(3):378～381Wang Zhijun and Huang Junbin.Identification of mi-cro-fault and sand body by using coherence techniqueand 3-D visualization.OGP,2001,36(3):378～381
[12]王永刚.地震资料综合解释方法.山东东营:中国石油大学出版社,2006
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