Windowed statistical analysis for anomaly detection in geophysical datasets

US8380435B2 · kind B2 · utility

Assignee

• EXXONMOBIL UPSTREAM RESEARCH COMPANY · US

Inventors

• Krishnan Kumaran · Raritan, US
• Jingbo Wang · Kasai, JP
• Stefan Hussenoeder · Saginaw, US
• Dominique G. Gillard · Houston, US
• Guy F. Medema · Magnolia, US
• Fred W. Schroeder · Tomball, US
• Robert L. Brovey · League City, US
• Pavel Dimitrov · Houston, US
• Matthew S. Casey · Houston, US

Key dates

• Filing date: May 6, 2010
• Grant date: Feb 19, 2013
• Expiry date: May 24, 2031

Classification

• Technology area (CPC G): Physics
• CPC primary: G01V2210/64
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

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.