¹ Federal State Budgetary Institution "Central Research Institute of Geological Prospecting for Base and Precious Metals" (FSBI "TSNIGRI"), Moscow

² Peoples' Friendship University of Russia named after Patrice Lumumba, Moscow

As part of the task of the FSBI TsNIGRI for the scientific and methodological support of geological exploration projects included into the State Order list of objects, that is provided by the State Assignment "Experimental, Methodological and Thematic Works", a compartive analysis has been performed of the expected and actually obtained results of the geological exploration at 20 projects completed in 2023. Based on the analysis, it was noted that the targets for localization and assessment of the forecasted resources of lead, zinc, and gold had been fulfilled at a level not lower than the average indicators of recent years. These targets were almost in full completed at 1 geological exploration project for base metals and at 5 geological exploration projects for gold. The main reasons were considered for the non-fulfillment/underfulfillment of the targets for localization and assessment of the forecast resources of precious and base metals for the State Order objects. It has been concluded that early phase geological exploration projects at the current level remain a high-risk production in economic terms. Reduction of the risks of the prospecting is possible by means of introduction into the practice of geological surveys of small- and medium-scale forecast-minerogenic works specialized on a certain type of solid minerals, especially within poorly studied territories, as well as by means of more efficient conducting of the geological surveys.

Key words: volcanic-plutonic belt, porphyry copper, petrochemical, isotope-geochemical, sources of mineral matter.

Federal State Budgetary Institution "All-Russian Research Geological Institute of A. P. Karpinsky", St. Petersburg

This article provides a brief overview of the theory of neural network methods of pattern recognition. It considers the features of using deep machine learning methods in interpreting complex geological and geophysical data and the possibilities of using them to solve forecasting problems. A method for neural network forecasting of ore mineralization, based on a priori physical-geological modeling by automated mapping of geological ore control factors, is proposed. The method is demonstrated on the example of identifying gold ore deposits in the Central Kolyma region.

Key words:machine learning, artificial neural networks, pattern recognition, geophysical data integration, mineralization forecast, gold deposits, Central Kolyma region.

¹Far East Geological Institute, Far Eastern Division of the Russian Academy of Sciences (FEGI FEB RAS), Vladivostok

²Institute of Geology of Ore Deposits, Petrography, Mineralogy and Geochemistry of the Russian Academy of Sciences (IGEM RAS), Moscow

Formation of anomalously antimony-silver bearing Sn-Pb-Zn ores of the Yuzhnoye deposit is related to the late Albian-Cenomanian orogeny of Sikhote-Alin. The ore-bearing structures are represented by fractured zones of strike-slip and thrust faults, subconformable to the bedding of Lower Cretaceous flyschoid siltstones and sandstones in the flank of an anticline. Based on the lead-isotope investigation, the source of lead in the Cenomanian ore-magmatic system of the Yuzhnoye deposit was represented by flyschoids of the Early Cretaceous accretionary prism of the Zhuravlevka terrane, the substrate of the granite-metamorphic layer of the newly formed Mesozoic continental crust of Sikhote-Alin. In terms of the mineralogical-geochemical and structural features, the deposit is fundamentally different from the skarn and vein Pb-Zn deposits of the Dalnegorsk type, associated with Early Paleocene magmatites of the Dalnegorsk andesite-gabbro-granodiorite-granite suite.

Key words: Albian-Cenomanian orogeny, Sn-Ag-Pb-Zn ores, S-O-Pb isotopes, Zhuravlevka terrane, Yuzhnoye, Krasnorechensk, Sikhote-Alin.

¹ Institute of the Earth's Crust, SB RAS, Irkutsk

²Limited Liability Company scientific and production company "Spirit" (OOO NPK "Spirit"), Irkutsk

The article presents information on the geology of the Verkhne-Timptonsky gold placer region, within which the Yurskoe placer deposit is located. A brief description of gold placers in the Yurski Stream basin is presented based on geological exploration results. Typomorphic features of native gold from the valley placer of the Yurski Stream were studied. Based on the studies, two types of the native gold were identified, that were related to different primary sources. The high-fineness gold of type I represents residual gold that entered the placer from Precambrian gold-bearing diaphthorites and from fissured weathering crusts in the diaphthorites. The medium- to low-fineness gold of type II of a low-temperature hydrothermal genesis entered the placer from Mesozoic volcanogenic molasse sequences. The question of whether these deposits are an intermediate collector for fragments of earlier gold mineralization, or there was a superposition of a late low-temperature mineralization, remains open. The prospects for identifying economically significant ore objects of various genetic types in the Yurski Stream basin are assessed.

Key words: Aldan-Stanovoy Shield, deep-seated fault, stratigraphic formation, rock sequence, igneous complex, ore formation, diaphthoresis, placer, bedrock, native gold, typomorphic features, fineness, primary source.

Federal State Budgetary Institution “Central Research Institute of Geological Prospecting for Base and Precious Metals” (FSBI “TSNIGRI”), Moscow

Using the examples of kyanite, sillimanite, and andalusite, the Fourier transform infrared microscopy is shown to be highly informative for studying the polymorphism of minerals. A technique has been developed for diagnosing the kyanite group minerals under the IR microscope. The data obtained confirm that the use of IR microscopy makes it possible to improve the method of analyzing minerals in heavy mineral concentrates and facilitates increasing the forecasting and prospecting efficiency.

Key words: FTIR microscope, IR spectra, wave number, kyanite, andalusite, sillimanite, hydroxyl groups.