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:
Aug. 26, 2025

Filed:

Sep. 11, 2020
Applicant:

Schneider Electric Systems Usa, Inc., Foxborough, MA (US);

Inventors:

Bartosz Boguslawski, Grenoble, FR;

Matthieu Boujonnier, Foxborough, MA (US);

Loryne Bissuel Beauvais, Montréal, CA;

Fahd Saghir, Brisbane, AU;

Helenio Gilabert, Calgary, CA;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
E21B 47/009 (2012.01); E21B 43/12 (2006.01); F04B 49/10 (2006.01); F04B 49/20 (2006.01); G05B 23/02 (2006.01); G06F 18/2415 (2023.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01); F04B 47/02 (2006.01); F04B 49/06 (2006.01);
U.S. Cl.
CPC ...
F04B 49/20 (2013.01); E21B 43/127 (2013.01); E21B 47/009 (2020.05); F04B 49/10 (2013.01); G05B 23/0243 (2013.01); G06F 18/2415 (2023.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); E21B 2200/22 (2020.05); F04B 47/02 (2013.01); F04B 49/065 (2013.01); G05B 2219/24065 (2013.01);
Abstract

Systems and methods for real-time monitoring and control of well operations at a well site use machine learning (ML) based analytics at the well site. The systems and methods perform ML-based analytics on data from the well site via an edge device directly at the well site to detect operations that fall outside expected norms and automatically respond to such abnormal operations. The edge device can issue alerts regarding the abnormal operations and take predefined steps to reduce potential damage resulting from such abnormal operations. The edge device can also anticipate failures and a time to failure by performing ML-based analytics on operations data from the well site using normal operations data. This can help decrease downtime and minimize lost productivity and cost as well as reduce health and safety risks for field personnel.


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