公开(公告)号：EP2356488A1

公开(公告)日：2011-08-17

申请号：EP09826491.4

申请日：2009-09-30

申请人： Exxonmobil Upstream Research Company

发明人： KUMARAN, Krishnan ,  WANG, Jingbo ,  HUSSENOEDER, Stefan ,  GILLARD, Dominique ,  MEDEMA, Guy, F. ,  SCHROEDER, Fred, W. ,  BROVEY, Robert, L. ,  DIMITROV, Pavel

IPC分类号： G01V1/00

CPC分类号： G01V1/288 ,  G01V1/301 ,  G01V2210/63 ,  G01V2210/64 ,  G01V2210/665

摘要： Method for identifying geologic features from geophysical or attribute data using windowed principal component (or independent component) analysis. Subtle features are made identifiable in partial or residual data volumes. The residual data volumes (24) are created by (36) eliminating data not captured by the most prominent principal components (14). The partial data volumes are created by (35) projecting the data on to selected principal components. The method is suitable for identifying physical features indicative of hydrocarbon potential.

摘要翻译： 使用窗口主成分（或独立分量）分析从地球物理或属性数据中识别地质特征的方法。 部分或残留数据量可以识别细微的特征。 剩余数据量（24）由（36）创建，消除未被最突出的主要组件（14）捕获的数据。 部分数据量由（35）将数据投影到选定的主要组件上创建。 该方法适用于识别指示烃潜力的物理特征。

公开(公告)号：EP2567261A1

公开(公告)日：2013-03-13

申请号：EP11777741.7

申请日：2011-03-17

申请人： ExxonMobil Upstream Research Company

发明人： KUMARAN, Krishnan ,  WANG, Jingbo ,  HUSSENOEDER, Stefan ,  GILLARD, Dominique, G. ,  MEDEMA, Guy, F. ,  SCHROEDER, Fred, W. ,  BROVEY, Robert, L. ,  DIMITROV, Pavel ,  CASEY, Matthew, S.

IPC分类号： G01V1/40

CPC分类号： G01V1/301 ,  G01V1/288 ,  G01V2210/64

摘要： Method for identifying geologic features from geophysical or attribute data using windowed principal component (22), or independent component, or diffusion mapping (61) analysis. Subtle features are made identifiable in partial or residual data volumes. The residual data volumes (24) are created by (36) eliminating data not captured by the most prominent principal components (14). The partial data volumes are created by (35) projecting the data (21) on to selected principal components (22, 61). Geologic features may also be identified from pattern analysis (77) or anomaly volumes (62, 79) generated with a variable-scale data similarity matrix (73). The method is suitable for identifying physical features indicative of hydrocarbon potential.