Research Risk Factors in Monitoring Well Drilling—A Case Study Using Machine Learning Methods

Research Risk Factors in Monitoring Well Drilling—A Case Study Using Machine Learning Methods

This article takes an approach to creating a machine learning model for the oil and gas industry. This task is dedicated to the most up-to-date issues of machine learning and artificial intelligence. One of the goals of this research was to build a model to predict the possible risks arising in the...

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Bibliographic Details
Main Authors: Shamil Islamov, Alexey Grigoriev, Ilia Beloglazov, Sergey Savchenkov, Ove Tobias Gudmestad
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Symmetry
Subjects:
machine learning
drilling problems
artificial intelligence
risk factor evaluation
gradient boosting
Online Access:https://www.mdpi.com/2073-8994/13/7/1293

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