Spatial zoning of mineral deposits

Delineation of ore-bearing intervals, construction of ore bodies and lithological modeling of mineral deposits yet remain the uncomputerized processes which need direct participation of geologists. Industrial digitalization dictates minimization of operations which require high-level human control. One of the processes automation of which can help minimize manual work in delineation is detection of lithological varieties, geological bodies and geotechnical elements. The method proposed to delineate lithological varieties is based on neural network technologies for three-dimensional modeling of ore bodies (coal seams) and enclosing rocks in order to improve the quality of geological supervision, planning and design of mines. This method can refine and greatly accelerate processing of geological data from rock mass assaying at all stages of integrated subsoil use. The developed method of three-dimensional modeling of rock mass lithology using functional capabilities of neural networks enables modeling at shorter notice at the required accuracy and reliability of the results.

Keywords: mineral mining, geological supervision of subsoil use, statistics, data processing, operational exploration, drilling, data standartization, ore body, neural networks, 3D modeling, digital deposit.
For citation:

Melnichenko I. A., Kirichenko Yu. V. Spatial zoning of mineral deposits. MIAB. Mining Inf. Anal. Bull. 2021;(4):46-56. [In Russ]. DOI: 10.25018/0236_1493_2021_4_0_46.

Issue number: 4
Year: 2021
Page number: 46-56
ISBN: 0236-1493
UDK: 550.8.053
DOI: 10.25018/0236_1493_2021_4_0_46
Article receipt date: 03.12.2020
Date of review receipt: 15.01.2021
Date of the editorial board′s decision on the article′s publishing: 10.03.2021
About authors:

I.A. Melnichenko1, Graduate Student, e-mail:,
Yu.V. Kirichenko1, Dr. Sci. (Eng.), Professor,
1 National University of Science and Technology «MISiS», 119049, Moscow, Russia.


For contacts:

I.A. Melnichenko, e-mail:


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