MACHINE LEARNING APPROACH FOR IDENTIFYING MUD AND FORMATION PARAMETERS BASED ON MEASUREMENTS MADE BY AN ELECTROMAGNETIC IMAGER TOOL

Patent №

US 11,199,643

Granted

2021-12-14

Filed 2019

Owner

HALLIBURTON ENERGY SERVICES, INC.

Lab

AI components

4

ml · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

16579513

Aspects of the subject technology relate to systems and methods for identifying values of mud and formation parameters based on measurements gathered by an electromagnetic imager tool through machine learning. One or more regression functions that model mud and formation parameters capable of being identified through an electromagnetic imager tool as a function of possible tool measurements of the electromagnetic imager tool can be generated using a known dataset associated with the electromagnetic imager tool. One or more tool measurements obtained by the electromagnetic imager tool operating to log a wellbore can be gathered. As follows, one or more values of the mud and formation parameters can be identified by applying the one or more regression functions to the one or more tool measurements.

Machine learningKnowledge representationPlanningAI hardwareG01V 3/20E21B 49/005G01V 1/306G01V 3/088G01V 3/28G06F 18/2411G06N 3/0499G06N 3/08+4 more

AI classification

Planning1.00
Machine learning0.98
AI hardware0.87
Knowledge representation0.58
Evolutionary computation0.01
Natural language0.00
Vision0.00
Speech0.00

Ownership

HALLIBURTON ENERGY SERVICES, INC.

assignment · 524910921

Assignors

SAMSON, ETIENNE M., GUNER, BARIS, FOUDA, AHMED E.

On an employer assignment, the assignors are typically the inventors.

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