Academician Melnikov Institute of Comprehensive Exploitation of Mineral Resources—IPKON, Russian Academy of Sciences, Moscow, Russia

V. N. Zakharov, Director, Academician of the Russian Academy of Sciences
D. N. Radchenko, Head of Laboratory, Candidate of Engineering Sciences, Associate Professor, mining_expert@mail.ru
D. A. Klebanov, Head of Laboratory, Candidate of Engineering Sciences

For developing classification of digital geotechnical data on rock mass, equipment and technological environment parameters, the approaches are proposed to assess value and interrelation of generated data with a view of their using on local (mines), regional and global scales of subsoil use. A hypothesis is put forward that the use of digital data from geotechnical systems, taken individually and conjointly, with the help of the Big Data technology, can reveal most general patterns in natural and manmade alteration of the subsoil. The natural subsoil alteration patterns are understood as new knowledge on the subsoil structure and the predictive analytics on discovery of new mineral bodies, deposits and ore provinces, as well as new types of georesources, etc. In the context of manmade alteration of the subsoil, it is expected to reveal new knowledge on processes running in the subsoil during integrated exploitation, and to get ample opportunities in controlling geotechnical systems. It is also supposed that processing of digital information can provide deeper insight into interaction of the unique objects created in the subsoil—geotechnical systems, and the adjacent systems—natural environment and society. On the scale of a government, this can enable more effective management of manpower, energy and material resources, as well as can help predicting demand for minerals and finding the ways to provide mineral resources security with regard to the created subsoil use system.
The study was supported by the Russian Science Foundation, Grant No. 22-17-00142.

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