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:
Mar. 08, 2022

Filed:

Jul. 13, 2016
Applicant:

Halliburton Energy Services, Inc., Houston, TX (US);

Inventors:

Xingyong Song, Houston, TX (US);

Jason D. Dykstra, Spring, TX (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
E21B 21/00 (2006.01); E21B 21/08 (2006.01); E21B 47/10 (2012.01); G06F 30/20 (2020.01); E21B 41/00 (2006.01); G06F 17/11 (2006.01); G06N 5/04 (2006.01); G06F 111/10 (2020.01);
U.S. Cl.
CPC ...
E21B 21/00 (2013.01); E21B 21/08 (2013.01); E21B 41/0092 (2013.01); E21B 47/10 (2013.01); G06F 17/11 (2013.01); G06F 30/20 (2020.01); G06N 5/04 (2013.01); G06F 2111/10 (2020.01);
Abstract

Methods and systems for enhancing workflow performance in the oil and gas industry may estimate the properties of drilling muds (e.g., density and/or viscosity) located downhole with methods that utilize real-time data, estimated drilling mud properties, and mathematical models. Further, the methods described herein may optionally account for the uncertainties induced by sensor readings and dynamic modeling. For example, a method may include circulating a drilling mud through a mud circulation system; performing a plurality of measurements from various sensors in a mud circulation system; modeling in real-time drilling mud flow dynamics in the drilling mud using a mathematical dynamics model; predicting physical states of the drilling mud with the mathematical dynamics model, thereby producing model physical state predictions; inputting the measurements into the mathematical dynamics model; and adjusting discrepancies between the model physical state predictions and the measurements using the mathematical dynamics model.


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