Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan-Reference-Cited by-同舟云学术

Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan

Published:2017-12-01 Issue:1 Volume:22 Page:21-27
ISSN:2255-8691
Container-title:Applied Computer Systems
language:en
Short-container-title:

Author:

Kuchin Yan¹,Grundspeņķis Jānis²

Affiliation:

1. Branch Office “Geotechnocentr” of JSC Volkovgeologija , Kazakhstan

2. Riga Technical University , Latvia

Abstract

Abstract The paper explores geophysical methods of wells survey, as well as their role in the development of Kazakhstan’s uranium deposit mining efforts. An analysis of the existing methods for solving the problem of interpreting geophysical data using machine learning in petroleum geophysics is made. The requirements and possible applications of machine learning methods in regard to uranium deposits of Kazakhstan are formulated in the paper.

Publisher

Walter de Gruyter GmbH

Reference33 articles.

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