Rock-Forming (Biotite and Plagioclase) and Accessory (Zircon) Minerals Geochemistry as an Indicator of the Metal Fertility of Magmas by the Example of Au-Cu-Fe-Skarn Deposits in Eastern Transbaikalia

Many gold and gold-bearing complex deposits related to the Late Jurassic and Early Cretaceous magmatism are known in Eastern Transbaikalia. The largest deposits are the Lugokan, the Kultuma and the Bystrinsky. These deposits are in a paragenetic relationship with the Late Jurassic magmatic rocks of the Shakhtama complex. According to the available data, the total resources of gold in these three deposits are estimated to be approximately 443 tons: the Lugokan, Au~53 tons, Cu~302 thousand tons; the Kultuma, Au~121 tons, Cu~587 thousand tons, Fe~33 mln t; the Bystrinsky, Au~269 tons, Cu~2070 thousand tons, Fe~67 mln t. One of the main aims of this work was to reveal the criteria of fertility for the classical porphyry type, based on the specific geochemical features of rock-forming and accessory minerals. A comparison of the obtained results with other data on the large porphyry and skarn deposits of the world showed that the magmatic rocks of the Bystrinsky massif, specifically porphyry species dated 159.6–158.6 Ma, are potentially ore-bearing for the porphyry type mineralization. The magmatic rocks that widely occur at the Lugokan and Kultuma deposits are most close to the Fe-skarn deposits. The best indicators of the magma fertility for the porphyry rocks are Ce/Ce*, Eu/Eu*, Yb/Dy, (Ce/Nd)/Y in zircons. Thus, magmatic rocks characterized by Ce/Ce* > 100, Eu/Eu* > 0.4, Yb/Dy > 5.0 and (Ce/Nd)/Y > 0.01 may be classified as high fertile for the classical porphyry mineralization in Eastern Transbaikalia. The plagioclase and biotite chemistry data also showed that the magmatic rocks that occurred at the Bystrinsky deposit are the most fertile for the porphyry type mineralization. The magmatic rocks classified as ore-bearing porphyry type have Al* > 1 in plagioclase, high values of IV(F) and IV(F/Cl) and low ratios of X(F)/X(OH) in biotites. The assessment of the metal fertility of magmatic rocks is most effective in combination with data on both the composition of rock-forming and accessory minerals. The obtained data may be used to develop the methods of prediction and search for gold, copper and iron mineralization.

Mineral inclusions in the late bronze age metal objects оf Southern Transurals

The paper is devoted to the determination of copper raw material types based on the analysis of mineral inclusions and the composition of metal objects from the Late Bronze Age settlements of the Southern Transurals (XIX–XIII centuries BC). The composition of alloys, inclusions of sulfdes, oxides and metals of objects was established by scanning electron microscopy. The composition of objects is dominated by copper and tin bronze, with a subordinate role of arsenic bronze. The presence of chalcocite and bornite inclusions in most objects indicates the use of rich ores from secondary sulfde enrichment zone. In comparison with analogs, the low total amount of sulfdes in the Southern Transuralian metal objects may indicate the use of mixed oxide and sulfde concentrates. The high Se and Te concentrations of sulfdes are indicative of using of ores of volcanic-hosted massive sulfde or skarn deposits. Keywords: metal objects, copper, bronze, sulfdes, Late Bronze Age, Southern Transurals

Texture and Geochemistry of Scheelites in the Tongshankou Deposit in Daye, Hubei, China: Implication for REE Substitution Mechanism and Multistage W Mineralization Processes

The Tongshankou skarn deposit in the Edong ore district is a typical metasomatic deposit associated with adjacent granodiorite porphyry and carbonate rocks. Using comprehensive microscopic observations, mineralogical and geochemical analysis, scheelite grains in the skarns can be classified into three major types, showing multi-stage mineralization characteristics. In the redox fluid environment, scheelites that occur with garnets usually have affinity to garnets, while in later skarn phases others exist with oxides and sulfides. They can be subdivided by trace elements, such as Nb and Eu, to discuss the detailed ore-forming process. Scheelites have three typical substitution mechanisms including: 2Ca2 + ⇌ REE3 + +Na+ (1); Ca2 + + W6 + ⇌ REE3 + +Nb5+(2); and 3Ca2 + ⇌ 2REE3++ □Ca (□Ca = Ca site vacancy) (3). Plagioclase or various hydrothermal stages can cause Eu anomalies to fluctuate from positive to negative, and these processes can cause particular zonation in W and Mo contents in scheelites. This study highlights the use of texture and geochemistry of scheelites in skarn deposits, depicting the W mineralization processes.

Origin of Palaeoproterozoic, sub-seafloor Zn-Pb-Ag skarn deposits, Sala area, Bergslagen, Sweden

Unravelling the genesis of metamorphosed mineral deposits can be complicated due to difficulties in separating between primary features and features that formed during the metamorphic overprint. Such uncertainty exists for stratabound and dolomite- and skarn-hosted Zn-Pb-Ag sulfide deposits in 1.89 Ga rocks in the Bergslagen lithotectonic unit (BLU) of Sweden, where a metasomatic vs. regional metamorphic origin for skarns has long been discussed. By integrating geological mapping with new lithogeochemical, mineralogical, and stable isotope data (C, O, S), we show that complexly zoned garnet and clinopyroxene skarns in the Sala area of the central BLU predate mineralization. Sphalerite-galena mineralization formed after the deposition of a younger, more Mn-rich ferroan diopside and andradite-grossular garnet, and is associated with phlogopite, tremolite-actinolite, chlorite, serpentine, and calcite. Mineralization in conjunction with a transition from high-T metasomatism to hydrolytic alteration is inferred. An average δ34SV-CDT of 1.6 ± 1.9‰ in sulfides is consistent with a primordial sulfur source. Trends defined by negative shifts in δ18OV-SMOW and δ13CV-PDB in dolomite and calcite are consistent with fluid infiltration at 300–500 °C. The alteration system is sharply truncated by unaltered, c. 1.89 Ga calc-alkaline granite and porphyritic intrusions, which along with F1 folding of the alteration zones and mineralization suggest that mineralization predate regional metamorphism. The Sala deposits are interpreted as Zn skarn deposits formed in conjunction with the emplacement of intrusions into penecontemporaneous marine volcanic and dolomitized limestone strata. The unusually Mg-rich mineralogy in relation to Zn skarns worldwide most likely reflects the dolomitic precursor.

Genesis of the Heiyanshan Tungsten Skarn Deposit in the East Tianshan, NW China: Insights From Geology, Fluid Inclusion, Isotopic Geochemistry and Geochronology

The eastern Tianshan Terrane is a highly prospective zone that contains several porphyry Cu–Mo, VMS Cu–Zn, magmatic Cu–Ni, epithermal and orogenic Au deposits. However, few attention has been paid to tungsten deposits. Of these, the source and evolution of the mineralising fluids related to the skarn W deposits are poorly understood. The Heiyanshan W deposit is hosted by metamorphosed clastic and carbonate beds in the Mesoproterozoic Jianshanzi Formation deposited on a continental margin tectonic setting. The Jianshanzi Formation is intruded by biotite monzogranite that yield weighted 206Pb/238U age of 326.9 ± 1.6 Ma, which suggest that the Heiyanshan W deposit was formed in the Carboniferous. The mineralisation is hosted by a prograde hydrothermal altered zone represented by a garnet (–pyroxene) skarn, and retrograde skarn characterised by fine-grained scheelite. The paragenesis of the Heiyanshan mineralisation can be subdivided into prograde skarn stage, retrograde skarn stage, quartz-sulphide stage and quartz-calcite vein stage. The types of fluid inclusions recognised in the various minerals in the deposits are liquid-rich aqueous, vapour-rich aqueous, and daughter mineral-bearing. The homogenisation temperatures of fluid inclusions from the Heiyanshan deposit decrease from 290 ± 28°C in garnet, through 232 ± 31°C in scheelite, to 232 ± 36°C in quartz and 158 ± 15°C in non-mineralised calcite, which is typical of W-bearing skarn deposits worldwide. The δ18Owater values from the Heiyanshan deposit range from +4.7 to +6.6‰ in garnet, +1.3 to +1.9‰ in quartz and −6.1 to −4.4‰ in calcite. We have measured δD in fluid inclusions from different minerals, although these bulk analyses are just a mixture of the different FIA’s present in the sample. The δD values of fluid inclusions in garnet, quartz, and calcite are from −121 to −71‰, −84 to −75‰ and −101 to −82‰, respectively, also indicative of deep-sourced magmatic fluids mixed with meteoric water. The decrease in the homogenisation temperatures for the fluid inclusions at the Heiyanshan deposit is accompanied by a drop in salinity indicating that tungsten-bearing minerals precipitated during fluid mixing between magmatic fluids and meteoric water. We conclude that eastern Tianshan Terrane contains two pulse of tungsten metallogenic events of Late Carboniferous and Early Triassic.

Iron Isotope Fractionation during Skarn Cu-Fe Mineralization

Fe isotopes have been applied to the petrogenesis of ore deposits. However, the behavior of iron isotopes in the mineralization of porphyry-skarn deposits is still poorly understood. In this study, we report the Fe isotopes of ore mineral separations (magnetite, pyrite, chalcopyrite and pyrrhotite) from two different skarn deposits, i.e., the Tonglvshan Cu-Fe skarn deposit developed in an oxidized hydrothermal system and the Anqing Cu skarn deposit developed in a reduced hydrothermal system. In both deposits, the Fe isotopes of calculated equilibrium fluids are lighter than those of the intrusions responsible for the skarn and porphyry mineralization, corroborating the “light-Fe fluid” hypothesis. Interestingly, chalcopyrite in the oxidized-Tonglvshan skarn deposit has lighter Fe than chalcopyrite in the reduced-Anqing skarn deposit, which is best understood as the result of the prior precipitation of magnetite (heavy Fe) from the ore fluid in the oxidized-Tonglvshan systems and the prior precipitation of pyrrhotite (light Fe) from the ore fluid in the reduced-Anqing system. The δ56Fe for pyrite shows an inverse correlation with δ56Fe of magnetite in the Tonglvshan. In both deposits, the Fe isotope fractionation between chalcopyrite and pyrite is offset from the equilibrium line at 350 °C and lies between the FeS-chalcopyrite equilibrium line and pyrite-chalcopyrite equilibrium line at 350 °C. These observations are consistent with the FeS pathway towards pyrite formation. That is, Fe isotopes fractionation during pyrite formation depends on a path from the initial FeS-fluid equilibrium towards the pyrite-fluid equilibrium due to the increasing extent of Fe isotopic exchange with fluids. This finding, together with the data from other deposits, allows us to propose that the pathway effect of pyrite formation in the Porphyry-skarn deposit mineralization is the dominant mechanism that controls Fe isotope characteristics.

Oxygen-Isotope-Based Modeling of the Hydrothermal Fluid Processes of the Taochong Skarn Iron Deposit, Anhui Province, China

The Taochong iron deposit is one of the important skarn deposits in the Middle–Lower Yangtze River metallogenic belt, Eastern China. There are two types of ores in the deposit: skarn- and quartz–calcite-type ores. The skarn-type ore, which is composed of hematite (Hm-1), garnet, pyroxene, actinolite, chlorite, quartz (Q-1), and calcite (Cal-1), is crosscut locally by a quartz–calcite-type ore vein. The quartz–calcite-type ore consists mainly of hematite (Hm-2), magnetite, quartz (Q-2 and 3), and calcite (Cal-2). The δ18Owater value (~2.67‰) of the fluids in equilibrium with Hm-1 is similar to the values of the mixtures of magmatic and meteoric fluids. However, the δ18O values of the fluids in equilibrium with Hm-2 are in the range of 7.64–8.54‰, similar to those of magmatic fluids. The δ18O values decrease systematically from the fluids in equilibrium with Hm-2 (7.64‰ to 8.54‰) to the fluids in equilibrium with magnetite, Q-3, and Cal-2 (−0.12‰ to 4.17‰) and the fluids in equilibrium with Cal-3 (−2.17‰ to 0.36‰). These features of oxygen isotopes indicate that two episodes of hydrothermal activity took place in the Taochong deposit, and both episodes began with a magmatic origin and then progressively evolved by mixing with meteoric water. The results of quantitative simulations suggest that the deposition of the skarn-type ores was most likely caused by the mixing of magmatic and meteoric fluids, whilst the deposition of the quartz–calcite-type ores was most likely caused by the boiling of magmatic fluids and the mixtures of magmatic brine and meteoric water.

Classification of different skarn deposits based on the compositional variability of associated grandite garnets: a data science and Machine Learning approach

<p>Rapid technological improvements made in in-situ analysis techniques, including LA-ICPMS, have transformed the field of analytical geochemistry. This has a far-reaching impact for different petrogenetic and ore-genetic studies where minute major and trace element compositional changes between different mineral zones within a single crystal can now be demarcated. Minerals such as garnet although robust are quite sensitive to the changing P-T and fluid conditions during their formation. These minerals have become powerful tools to characterize mineralization types. Previously, Meinert (1992) has used in-situ major element EPMA analysis results to classify different skarn deposit based on the end-member composition of hydrothermal garnets. Alternatively, Tian et al. (2019) used the garnet trace element composition for the similar purpose. However, these discrimination plots/ classification schemes show major overlap in different skarn deposits, such as Fe, Cu, Zn, and Au. The present study is an attempt to use machine learning approach on available garnet data to found a more potent classification scheme for skarn deposits, thus reaffirming garnet as a faithful indicator for hydrothermal ore deposits. We have meticulously collected major and trace element data of Ca-rich garnets, associated with different skarn deposits worldwide from 40 publications. This collected data is then used to train a model for fingerprinting the skarn deposits. Stratified random sampling method has been used on the dataset with 80% of the samples as test set and the rest 20 % as training dataset. We have used K-nearest neighbour (KNN), Support Vector Machine (SVM) and Random Forest algorithms on the data by using Python as a platform. These ML classification algorithm performs better than the earlier existing models available for classification of ore types based on garnet composition in skarn system. Factor importance is calculated that shows which elements play a pivotal role in classification of the ore type. Our results depict that multiple garnet forming elements taken together can reliably be used to discriminate between different ore formation settings.</p>