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:
Sep. 16, 2025

Filed:

Sep. 08, 2020
Applicant:

Landmark Graphics Corporation, Houston, TX (US);

Inventors:

Yevgeniy Zagayevskiy, Houston, TX (US);

Shohreh Amini, Houston, TX (US);

Srinath Madasu, Houston, TX (US);

Zhi Chai, Houston, TX (US);

Azor Nwachukwu, Houston, TX (US);

Assignee:

Landmark Graphics Corporation, Houston, TX (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
E21B 43/00 (2006.01); E21B 21/08 (2006.01); E21B 47/003 (2012.01); G01V 20/00 (2024.01); G06F 18/20 (2023.01); G06F 30/27 (2020.01); G06F 113/08 (2020.01);
U.S. Cl.
CPC ...
E21B 43/00 (2013.01); E21B 21/08 (2013.01); E21B 47/003 (2020.05); G01V 20/00 (2024.01); G06F 18/29 (2023.01); G06F 30/27 (2020.01); E21B 2200/20 (2020.05); G01V 2210/665 (2013.01); G06F 2113/08 (2020.01);
Abstract

An apparatus for generating forecasts from a high-dimensional parameter data space comprising a reservoir model, a model order reduction module, and an assisted history matching module. The reservoir model having input variables, output variables, and an algorithmic model. The input variables, output variables, and the algorithmic model are generated by a flow simulator module and from a formation and reservoir properties database and a field production database. The model order reduction module generates a subset of the original or transformed input variables. The assisted history matching module adjust values of the output variables based on a difference between the at least one of the output variables and dynamic field production data to improve model accuracy.


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