Vol 70, No 7 (2025)

Iron ores are mostly typical exogenous deposits formed under the influence of various tectonic, paleogeographic and biochemical factors. Mineralogical and petrographic analysis of iron ores showed that the main ones in terms of distribution and volume in the Precambrian and Phanerozoic are the banded ferruginous-siliceous formation or BIF, oolitic hydrogoethite-chamosite-siderite (Lorraine type), as well as hematite, goethite-hydrogoethite weathering crusts (WC). The remaining types of ores do not play any significant role in the reserves, and their quantity is at the level of statistical error. It is shown that the evolution of iron accumulation is clearly expressed in the Earth history. It has a pulsating-directed trend with several stages of ore formation. In the Archean, iron ores accumulations are confined to greenstone belts, in the Paleoproterozoic – to protoplatforms, in the Neoproterozoic – to rift basins, and in the Phanerozoic – to platforms. The Archean and Paleoproterozoic ores are represented by the BIF, the Neoproterozoic by the granular iron formation, and the Phanerozoic by the WC and oolitic formations. Over time, the mineral-petrographic types of ores also evolved. If hematite-magnetite ores are typical for the Archean and Paleoproterozoic, hematite ores are typical for the Neoproterozoic, then hematite, hydrohematite, goethite WC and oolitic hematite-chamosite-siderite ores are typical for the Phanerozoic. The change in ore types was determined by changes in the facies conditions, as well as by metamorphic processes in the Precambrian. The change in ore types was determined by the facies conditions evolution, as well as by the processes of metamorphism in the Precambrian.

A quartz geothermometer (QG) allows you to determine the temperature of a geothermal reservoir (GR) located at depth by the concentration of SiO₂ (m) in a solution that ascends from this reservoir to the surface. An error was made in the initial modeling of QG, which underestimated the quartz deposition rate and thus expanded the scope of application of QG. Another disadvantage of early modeling was that it ignored the possibility of precipitation of metastable modifications of silica. To eliminate these shortcomings, a new mathematical modeling using the finite difference method was performed using new kinetic data. The reliability of the data was assessed by using them in modeling the slow cooling of the quartz–water system and comparing the simulation results with the experimental results of this process. The best agreement between experiments and calculations was obtained when two-stage SiO₂ deposition was used in calculations, when different kinetic constants were used above and below the solubility of amorphous silica (AS), which described the deposition of AS and other metastable modifications of silica, respectively. The results of the new QG simulation using new kinetic data were the same with the same ratio of the two initial parameters that characterize the deposition surface area normalized to the mass of water (S/M) and the rate of solution rise (v). The real boundary values of this ratio, S/M and v, are determined, at which the model predicts the correct readings of QG for different temperatures of the solution in GR and at the surface. The kinetic equations used in the simulation do not take into account many features of the silica deposition reaction mechanism. An experimental study of these features will make it possible to perform a more realistic simulation of QG, close to real natural processes.