纹理模型回归分析在地震图像增强中的应用
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摘要
高质量的地震图像在地震资料的解释过程中有其举足轻重的作用。地震图像纹理模型回归分析实际上是一个统计滤波的过程,因此可以采用该方法提高地震图像的质量。基于实际地震数据研究表明,该方法明显提高了地震图像的质量,并保持地震图像的纹理结构,且计算时间少。
引文
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[12]Gao D.Latest developmentsinseismictexture analysisfor subsurface structure,facies,andreservoir characterization:Areview[J].Geophysics,2011,76(2):1-13.
[2]Hocker C,Fehmers G.Fast structural interpretation with structure-oriented filtering[J].The Leading Edge,2002,21:238-243.
[3]Fehmers G C,Hocker C.Fast structural interpretation with structure-orientd filtering[J].Geophysics,2003,68:1286-1293.
[4]AlBinHassan N M,Luo Y.3Dedge-preserving smoothing and applications[J].Geophysics,2006,71(4):5-11.
[5]杨宁.基于倾向扩散因子的SOF地震图像增强方法[J].石油地球物理勘探,2010,45(6):833-835.
[6]杨培杰.方向性边界保持断层增强技术[J].地球物理学报,2010,53(12):2992-2997.
[7]Gao D.Texture model regressionfor effective feature discri mination:Application to seismic facies visualization andinterpretation[J].Geophsics,2004,69(4):958-967.
[8]Gao D.Theory and methodology for seismic texture analysis:i mplication for seismic facies visualization and interpretation[J].GulfCoast Association of Geological Societies Transactions,2006,56(1):217-226.
[9]Gao D.Structure-oriented texture model regressionfor seismic structure visualization andinterpretation[J].Gulf Coast Association ofGeological Societies Transactions,2006,56:207-216.
[10]Gao D.Application of seismic texture model regression to seismic facies characterization and interpretation[J].THE LEADI NGEDGE,2008:394-397.
[11]Gao D.Method for i maging seismic structures[P].United States Patent 6912466:2005-6-28.
[12]Gao D.Latest developmentsinseismictexture analysisfor subsurface structure,facies,andreservoir characterization:Areview[J].Geophysics,2011,76(2):1-13.
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