Academician Melnikov Research Institute of Comprehensive Exploitation of Mineral Resources – IPKON, Russian Academy of Sciences, Moscow, Russia:

V. N. Zakharov, Director, Corresponding Member of the Russian Academy of Sciences

Geophysical Center of the Russian Academy of Sciences, Moscow, Russia:

B. V. Dzeranov, Researcher, Candidate of Geological and Mineralogical Sciences, b.dzeranov@geras.ru

Geophysical Center of the Russian Academy of Sciences, Moscow, Russia¹ ; Schmidt Institute of Physics of the Earth, Russian Academy of Sciences, Moscow, Russia²:

A. D. Gvishiani^{1, 2}, Research Manager, Academician of the Russian Academy of Sciences, Doctor of Physical and Mathematical Sciences

Saint Petersburg Mining University, Saint Petersburg, Russia:
L. A. Vaisberg, Academician of the Russian Academy of Sciences, Doctor of Engineering Sciences

The authors use the theory of Big Data to discuss the stages of induced transformation in the Earth’s interior. The amount of data on the mining sector exponentially grows with its digital transformation. Mining sciences call for efficient processing and integration of data acquired from numerous digital systems. Such data reach the amount of hundreds terabytes annually at a scale of a single company. This article gives grounds for the fact that the mining sector data belong to Big Data. The current world’s mining industry uses a few hundreds of different digital technologies. The amount of incoming data is colossal as a consequence. At the same time, digital technologies are unequally distributed among the mining companies. Based on the data-flow analysis, the problem on systematization of sources and amounts of information on a geotechnical system is formulated and solved. The systematization allows demonstrating the scale of the information received and used, and discloses the principle of the data processing and storage. The trends of research in the sphere of Big Data towards sustainable functioning of geotechnical systems in correlation with the environment and society. Creation of the efficient processing methods for Big Data of a geotechnical systems can help reveal more general nature-and-technology interactions in the future. This can help studying transformation of the structure and properties of the Earth’s interior under the manmade impact. Later on, Big Data can become a tool for the analyses of hydrological behavior and gas dynamics, environment, social aspects of subsoil use, etc.
The study was carried out under state contracts between the Geophysical Center, IPKON RAS and the Ministry of Science and Higher Education of Russia.

The authors appreciate participation of Associate Professor, Candidate of Engineering Sciences D. N. Radchenko and Head of Laboratory, Candidate of Engineering Sciences D. A. Klebanov from the Academician Melnikov Research Institute of Comprehensive Exploitation of Mineral Resources – IPKON RAS in this study.

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