Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan

Kuchin, Yan; Grundspeņķis, Jānis

doi:10.1515/acss-2017-0014

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.

References

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Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan

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