Metallogeny of the iron in geological time: comparison of supercontinent cycles

Abstract

Introduction: researchers of the iron ore metallogeny through geological time have always paid special attention to sedimentary deposits, primarily ferruginous quartzites, forming the core of the world's iron resource base. However, they are not the only source of this metal for the industry. Moreover, for some countries, the types of deposits with a different genesis play an important, and often key, role. The proposed study is the first to synthesize quantitative data on the through geological time metallogeny of all types of iron ore deposits of economic significance together, based on an analysis of the distribution of their explored resources.

Data and methodology: data on 398 iron ore deposits from around the world with explored resources of ≥100 million tonnes of Fe were collected and compared. The deposits and their resources were distributed over a geological time scale and compared at the level of supercontinent cycles.

Results and discussion: iron ore metallogeny underwent quite contrasting changes during the transition from one supercontinent cycle to another. These changes are expressed both in the set of deposit types formed in each of the cycles and in the intensity of their generation. More than half of all resources are associated with the most ancient Kenoran cycle. Almost all of them are concentrated in deposits of fine-banded ferruginous quartzites of the Algoma and Superior types, with the former dominating until the middle of the cycle, and the latter in its final phase, which was the most productive. The insignificant remainder falls on sedimentary deposits of continental basins and ortho-magmatic ores of basic-ultrabasic intrusions. The Columbian cycle is the second in productivity. Again, ferruginous quartzites became the leading type, but only of the Superior type with an overwhelming dominance of not fine-banded, but more coarse-banded granular ores. The ore sediments that make up these deposits were accumulated in a relatively short period of time in the middle of the cycle in a very limited number of places. The orthomagmatic type in basic-ultrabasic intrusions became the second most important in this cycle. Late- and post-magmatic deposits associated with felsic magmatism also began to form in large volumes. The first iron ore deposit in carbonatites also arose. The scale of sedimentary ores of continental basins was again very limited. The Rodinian cycle is the least productive in the historical metallogeny of iron ores with a small number of large deposits, but representing many types. For the first time in geological history, representatives of the exhalation-sedimentary and epigenetic types in sedimentary carbonate rocks appeared among them. Deposits of carbonatite, orthomagmatic and continental sedimentary types also appeared. The Pangean cycle is comparable in overall productivity with the Columbian cycle, and it is the only one represented by all types of deposits included in the analysis. The largest resources are concentrated in the giant deposits of ferruginous quartzites that appeared at the beginning of the cycle, the Rapitan type specific to this cycle, associated with post-glacial diamictites of marine basins. In the Pangean cycle, the most significant resources for their types were formed by exhalation-sedimentary, carbonatite and post-magmatic deposits. For the rest types, this cycle was ordinary. The Amasian cycle is twice as small as the Pangean cycle in terms of explored resource base. Among the types considered, only ferruginous quartzites are not represented in it. Quantitatively, the resources of continental sedimentary deposits absolutely dominate. Significant resources are also associated with late- and post-magmatic deposits. The other types appeared on a small scale.

Conclusion: all supercontinent cycles have clearly expressed features in the metallogeny of iron ore deposits. Their consideration, based on the analysis of the geological development of specific regions, should contribute to improving the quality of forecast models when conducting a forecast and exploration assessment of these regions.