Empress Catherine II Saint Petersburg Mining University, Saint-Petersburg, Russia

A. S. Egorov, Head of Department, Doctor of Geological and Mineralogical Sciences, Professor
D. D. Sekerina, Assistant, Candidate of Geological and Mineralogical Sciences, Sekerina_DD@pers.spmi.ru
D. F. Kalinin, Doctor of Engineering Sciences, Professor
N. P. Senchina, Candidate of Geological and Mineralogical Sciences, Associate Professor

Rudny Altai is characterized by a high degree of geological and geophysical study and active industrial development of polymetallic sulphide deposits. One of the most promising objects localized in the Rudny Altai mineralogenic zone is the Zmeinogorsk ore district. The authors set the task of substantiation of non-standard criteria for the ore-bearing capacity on the basis of geotectonic interpretation of the complex of geological and geophysical data. To solve this task, a working data bank was compiled, including materials of horizontal and vertical geological, geophysical and remote sensing surveys, the calculation of transformations of gravity and magnetic fields was performed, and the reference-free zoning of the ore district area by low- and medium-frequency components of potential geophysical fields was carried out. On the basis of the lineament analysis of heterogeneous geological, geophysical and remote sensing information, we have mapped discontinuities of different morphokinematic types, separate structural and material subdivisions of the Earth’s crust (rift depressions, volcanic–plutonic belts, separate granitoid massifs). Using algorithms of gravity and magnetic field inversion, a depth section was constructed along a given cross-section. As a result of the integrated geotectonic interpretation of geological and geophysical data, the structural–tectonic and historical-evolutionary models of the Zmeinogorsk ore district were developed, which were used to substantiate ore formation mechanisms and ore substance migration paths. A set of predictive structural geological and geophysical criteria of ore-bearing capacity was formed. These areal, linear and point criteria were digitized and entered into a pattern recognition system with training. The contours of the Lazursky and Korbalikhinsky polymetallic sulphide ore occurrences were used as training standards. The constructed forecast scheme ranks the territory in terms of similarity with the given benchmarks and highlights the most promising areas for the more detailed prognostic and mineralogenic studies.

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