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. 16, 2016

Filed:

Jul. 31, 2012
Applicants:

Marko Maucec, Englewood, CO (US);

Gustavo Carvajal, Katy, TX (US);

Seyed M. Mirzadeh, Houston, TX (US);

Ajay Pratap Singh, Houston, TX (US);

Hasnain A. Khan, Houston, TX (US);

Luigi A. Saputelli, Houston, TX (US);

Inventors:

Marko Maucec, Englewood, CO (US);

Gustavo Carvajal, Katy, TX (US);

Seyed M. Mirzadeh, Houston, TX (US);

Ajay Pratap Singh, Houston, TX (US);

Hasnain A. Khan, Houston, TX (US);

Luigi A. Saputelli, Houston, TX (US);

Assignee:

LANDMARK GRAPHICS CORPORATION, Houston, TX (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06G 7/48 (2006.01); G06F 7/60 (2006.01); E21B 43/00 (2006.01); G01V 99/00 (2009.01);
U.S. Cl.
CPC ...
E21B 43/00 (2013.01); G01V 99/00 (2013.01);
Abstract

The present disclosure describes systems and methods for performing multi-level reservoir history matching. At least some illustrative embodiments include a method that includes generating a first history-matched model using at least one updated model parameter derived from one or more existing model parameters, generating a set of second history-matched models by applying a probabilistic inversion to the first history-matched model, and deriving a set of third history-matched models from the set of second history-matched models. The method further includes generating dynamic simulation realization sets using each of the set of third history-matched models, ranking each of the set of third history-matched models based at least in part on the dynamic simulation realization sets, and presenting a production forecast to a user based on the highest ranked third history-matched models.


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