The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 19, 2013

Filed:

May. 06, 2010
Applicants:

Krishnan Kumaran, Raritan, NJ (US);

Jingbo Wang, New York, NY (US);

Stefan Hussenoeder, Sugarland, TX (US);

Dominique G. Gillard, Houston, TX (US);

Guy F. Medema, Magnolia, TX (US);

Fred W. Schroeder, Tomball, TX (US);

Robert L. Brovey, League City, TX (US);

Pavel Dimitrov, Houston, TX (US);

Matthew S. Casey, Houston, TX (US);

Inventors:

Krishnan Kumaran, Raritan, NJ (US);

Jingbo Wang, New York, NY (US);

Stefan Hussenoeder, Sugarland, TX (US);

Dominique G. Gillard, Houston, TX (US);

Guy F. Medema, Magnolia, TX (US);

Fred W. Schroeder, Tomball, TX (US);

Robert L. Brovey, League City, TX (US);

Pavel Dimitrov, Houston, TX (US);

Matthew S. Casey, Houston, TX (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01V 3/00 (2006.01); G05B 19/42 (2006.01); G06G 7/36 (2006.01); E21B 49/00 (2006.01);
U.S. Cl.
CPC ...
Abstract

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


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