基于神经网络的多属性分析在地震图像共同区域划分中的应用
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摘要
介绍了基于神经网络的多属性分析在地震图像的共同区域划分中的应用。首先优选并计算了能刻画地震图像复杂度的4种属性:纹理能量、纹理对比度、纹理随机性和纹理分形维属性,然后采用神经网络对具有统计学特征的纹理属性进行聚类分析,从而得到地震图像共同区域划分图。
引文
[1]王永刚.地震资料综合解释方法[M].东营:中国石油大学出版社,2007.
[2]Gao D.Application of three-dimensional seismic texture analysis with special reference to deep-marine facies discrimination and interpre-tation:Offshore Angola,west Africa[J].AAPG Bulletin,2007,91(12):1665-1683.
[3]Gao D.Volume texture extraction for 3D seismic visualization and interpretation[J].Geophysics,2003,68(4):1294-1302.
[4]Gao D L.Texture model regression for effective feature discrimination:Application to seismic facies visualization and interpretation[J].Geophsics,2004,69(4):958-967.
[5]Gao D L.Theory and methodology for seismic texture analysis:implication for seismic facies visualization and interpretation[J].GulfCoast Association of Geological Societies Transactions,2006,56(1):217-226.
[6]Gao D L.Application of seismic texture model regression to seismic facies characterization and interpretation[J].THE LEADINGEDGE,2008,27(3):394-397.
[7]West B P,May S R.Eastwood J E.Interactive seismic facies classification using textural attributes and neural networks[J].TheLeading Edge,2002,21(10):1042-1049.
[8]Andreas Kohler,Matthias Ohrnberger,Frank Scherbaum.Unsupervised pattern recognition in continuous seismic wavefield recordsusing Self-Organizing Maps[J].Geophysical Journal International,2010,182(3):1619-1630.
[9]Marcilio Castro de Matos,Paulo Leo Manassi Osorio,Paulo Roberto Schroeder Johann.Unsupervised seismic facies analysis usingwavelet transform and self-organizing maps[J].Geophysics,2007,72(1):9-21.
[10]文环明.分形测井解释理论方法研究[D].成都:成都理工大学,2002.
[11]唐雪芹.基于地震属性分析的沉积相划分——以民丰地区为例[D].东营:中国石油大学,2009.
[2]Gao D.Application of three-dimensional seismic texture analysis with special reference to deep-marine facies discrimination and interpre-tation:Offshore Angola,west Africa[J].AAPG Bulletin,2007,91(12):1665-1683.
[3]Gao D.Volume texture extraction for 3D seismic visualization and interpretation[J].Geophysics,2003,68(4):1294-1302.
[4]Gao D L.Texture model regression for effective feature discrimination:Application to seismic facies visualization and interpretation[J].Geophsics,2004,69(4):958-967.
[5]Gao D L.Theory and methodology for seismic texture analysis:implication for seismic facies visualization and interpretation[J].GulfCoast Association of Geological Societies Transactions,2006,56(1):217-226.
[6]Gao D L.Application of seismic texture model regression to seismic facies characterization and interpretation[J].THE LEADINGEDGE,2008,27(3):394-397.
[7]West B P,May S R.Eastwood J E.Interactive seismic facies classification using textural attributes and neural networks[J].TheLeading Edge,2002,21(10):1042-1049.
[8]Andreas Kohler,Matthias Ohrnberger,Frank Scherbaum.Unsupervised pattern recognition in continuous seismic wavefield recordsusing Self-Organizing Maps[J].Geophysical Journal International,2010,182(3):1619-1630.
[9]Marcilio Castro de Matos,Paulo Leo Manassi Osorio,Paulo Roberto Schroeder Johann.Unsupervised seismic facies analysis usingwavelet transform and self-organizing maps[J].Geophysics,2007,72(1):9-21.
[10]文环明.分形测井解释理论方法研究[D].成都:成都理工大学,2002.
[11]唐雪芹.基于地震属性分析的沉积相划分——以民丰地区为例[D].东营:中国石油大学,2009.
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