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:
Feb. 10, 2026

Filed:

Dec. 03, 2021
Applicant:

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

Inventors:

Jonas Toelke, Houston, TX (US);

Andre De Almeida Maximo, Rio de Janiero, BR;

Jacob Michael Proctor, Houston, TX (US);

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
E21B 47/002 (2012.01); E21B 47/02 (2006.01); E21B 49/02 (2006.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
E21B 47/0025 (2020.05); E21B 49/02 (2013.01); G06T 7/0004 (2013.01); E21B 2200/22 (2020.05); G06T 2207/20081 (2013.01); G06T 2207/30181 (2013.01);
Abstract

A method is provided for automatically classifying grains, pores, or both of a formation sample. The method includes receiving a digital image representation of the formation sample, and identifying a plurality of pores, grains, or both in the digital image representation. The method also includes computing a plurality of geometric features associated with the pores, grains, or both in the digital image representation, and inputting the geometric features into an unsupervised machine learning model. The unsupervised machine learning model determines a label for each identified pore and grain, the label being a pore-type or a grain-type, and the plurality of geometric features and the labels determined for each pore, grain, or both, are input into a supervised machine learning model. The supervised machine learning model determines a final classification of a pore-type for each pore and a grain-type for each grain in the digital image representation of the formation sample.


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