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:
Oct. 10, 2023

Filed:

Oct. 16, 2019
Applicant:

Saudi Arabian Oil Company, Dhahran, SA;

Inventors:

Andrey Bakulin, Dhahran, SA;

Robert Smith, Dhahran, SA;

Stanislav Glubokovskikh, Maylands, AU;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
E21B 44/00 (2006.01); E21B 49/00 (2006.01); G06N 20/00 (2019.01); G01V 1/46 (2006.01); G01V 1/50 (2006.01); G06F 18/24 (2023.01); G06F 18/213 (2023.01);
U.S. Cl.
CPC ...
E21B 44/00 (2013.01); E21B 49/003 (2013.01); G01V 1/46 (2013.01); G01V 1/50 (2013.01); G06F 18/213 (2023.01); G06F 18/24 (2023.01); G06N 20/00 (2019.01);
Abstract

Methods for determination of elastic properties of geological formations using machine learning include extracting a first feature vector from data acquired during drilling. The data includes at least drilling parameters. The first feature vector is indicative of a drilling environment classification. A machine learning classification algorithm determines the drilling environment classification based on the first feature vector. A machine learning regression algorithm is selected from multiple machine learning regression algorithms based on the drilling classification. A second feature vector is extracted from the data acquired during drilling based on the drilling classification and the selected machine learning regression algorithm. The second feature vector is indicative of elastic properties of a geological formation. The selected machine learning regression algorithm determines the elastic properties of the geological formation based on the second feature vector.


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