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:
May. 07, 2019

Filed:

Jun. 02, 2015
Applicants:

Oladele Bello, Katy, TX (US);

Stanley T. Denney, The Woodlands, TX (US);

Inventors:

Oladele Bello, Katy, TX (US);

Stanley T. Denney, The Woodlands, TX (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
E21B 43/14 (2006.01); G06Q 10/04 (2012.01); G06Q 10/06 (2012.01); G06Q 50/02 (2012.01);
U.S. Cl.
CPC ...
E21B 43/14 (2013.01); G06Q 10/04 (2013.01); G06Q 10/067 (2013.01); G06Q 10/06313 (2013.01); G06Q 50/02 (2013.01); Y04S 10/54 (2013.01);
Abstract

A method of online real-time estimation of production performance properties includes receiving real-time field data taken by downhole sensors, and estimating formation properties and production performance properties by applying the field data to a two or three-dimensional numerical transient thermal multiphase reservoir flow model, and automatically calibrating the model. Calibrating includes: selecting calibration parameters corresponding to values of selected model parameters, and applying the calibration parameters to the model to generate predicted properties that correlate with the selected model parameters, the predicted properties including flow rates and/or formation properties; automatically calculating a difference between the predicted properties and measured properties that correlate with the selected model parameters, and calculating an objective function value; performing an inversion that includes iteratively adjusting the selected model parameters until the objective function reaches a selected minimum value; and automatically updating the model by applying the selected model parameters associated with the minimum value.


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