Director
IGT Overseas
Graduate of the Geological Faculty of Lomonosov Moscow State University, candidate of geological and mineralogical sciences.
Total professional experience of 36 years. For 15 years, he held senior positions in the geological exploration services of Sibneft, Gazprom Neft, and Millhouse. Since 2015, he has been the executive director of the IGT Group, which includes several private companies engaged in geological exploration for precious and non-ferrous metals, consulting, remote sensing of the Earth, and the development of specialized software for geological exploration.
Awarded the "Deposit Pioneer" Badge.
Gives a course of lectures at the faculty of the "Higher School of Innovative Business" of Lomonosov Moscow State University.
Member of the Public Council under the Federal Agency for Subsoil Use (Rosnedra).
Member of the Eurasian Geophysical Society.
Application of artificial intelligence algorithms at the exploration stage of geological exploration – a solution to the problem or an imitation of success?
Artificial intelligence (AI) is one of the fastest growing technologies, attracting significant investments from various financial sources around the world. Undoubtedly, aggressive investment in AI is due to the possible advantages it offers: reduced costs, scalability, improved final quality of task performance, more informed decisions based on data analysis, advantages in technological developments and many other factors.
Undoubtedly, modern technological solutions are fundamentally changing approaches to obtaining and processing multi-format data obtained as a result of applying various methods of geological research. This, in turn, significantly increases the accuracy of resource forecasts and, accordingly, significantly reduces risks in geological exploration at its later stages.
It seems that the integration of deep machine learning methods into geological exploration practice should open new horizons for the interpretation of data obtained in the process of the entire complex of studies - from remote sensing methods from space to actual data obtained as a result of drilling and subsequent analytical studies. The convergence of technologies and AI in geological exploration can create a powerful synergistic effect, expanding the possibilities of identifying and evaluating new promising areas and mineral deposits, as well as increasing the degree of reliability of the forecasts obtained.
However, is this true in practice? Are our expectations too high? The cost of investment errors is too high, especially at the prospecting stage of geological exploration. Maybe the abbreviation AI does not mean artificial intelligence, but AI is just an imitation of intelligence? What are the differences in the use of AI at the geological prospecting stage and the exploration stage? Can any preferences be obtained from replacing or combining natural intelligence with artificial intelligence, and if so, what are they? Which geological specializations are most likely to disappear with the process of mass implementation of AI in geological exploration. Let's try to discuss these issues.
