EVALUATING TITANITE AS AN INDICATOR OF METAL FERTILITY AND RELATIVE OXYGEN FUGACITY IN THE WHITE PINE MO-W PORPHYRY DEPOSIT, UTAH

2019 ◽  
Author(s):  
Alec J. Martin ◽  
◽  
Jeffrey D. Keith ◽  
Eric H. Christiansen ◽  
Bart J. Kowallis ◽  
...  
Keyword(s):  
Oxygen Fugacity ◽  
White Pine ◽  
Porphyry Deposit

scholarly journals Crystal mush dykes as conduits for mineralising fluids in the Yerington porphyry copper district, Nevada

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Lawrence C. Carter ◽  
Ben J. Williamson ◽  
Simon R. Tapster ◽  
Catia Costa ◽  
Geoffrey W. Grime ◽  
...  
Keyword(s):  
Low Temperature ◽  
Cross Section ◽  
Porphyry Copper ◽  
Similar Type ◽  
Interconnected Network ◽  
Crystal Mush ◽  
Porphyry Deposit ◽  
Hydrothermal Quartz ◽  
Miarolitic Cavities

AbstractPorphyry-type deposits are the world’s main source of copper and molybdenum and provide a large proportion of gold and other metals. However, the mechanism by which mineralising fluids are extracted from source magmas and transported upwards into the ore-forming environment is not clearly understood. Here we use field, micro-textural and geochemical techniques to investigate field relationships and samples from a circa 8 km deep cross-section through the archetypal Yerington porphyry district, Nevada. We identify an interconnected network of relatively low-temperature hydrothermal quartz that is connected to mineralised miarolitic cavities within aplite dykes. We propose that porphyry-deposit-forming fluids migrated from evolved, more water-rich internal regions of the underlying Luhr Hill granite via these aplite dykes which contained a permeable magmatic crystal mush of feldspar and quartz. The textures we describe provide petrographic evidence for the transport of fluids through crystal mush dykes. We suggest that this process should be considered in future models for the formation of porphyry- and similar-type deposits.

scholarly journals Mineralogy, mineral chemistry and thermobarometry of post-mineralization dykes of the Sungun Cu–Mo porphyry deposit (Northwest Iran)

2020 ◽  
Vol 12 (1) ◽  
pp. 764-790
Author(s):  
Amin Allah Kamali ◽  
Mohsen Moayyed ◽  
Nasir Amel ◽  
Fadaeian Mohammad ◽  
Marco Brenna ◽  
...  
Keyword(s):  
Active Continental Margin ◽  
Mineral Chemistry ◽  
Quartz Diorite ◽  
Alkaline Magmatism ◽  
Porphyry Deposit ◽  
Average Percentage ◽  
The North ◽  
Northwestern Iran ◽  
Subduction System ◽  
Late Stages

AbstractThe Sungun copper–molybdenum porphyry deposit is located in the north of Varzaghan, northwestern Iran. The Sungun quartz-monzonite is the oldest mineralized intrusive body in the region and was emplaced during the Early Miocene. Eight categories of the late and unmineralized dykes, which include quartz diorite, gabbrodiorite, diorite, dacite, microdiorite and lamprophyre (LAM), intrude the ore deposit. The main mineral phases in the dykes include plagioclase, amphibole and biotite, with minor quartz and apatite and secondary chlorite, epidote, muscovite and sericite. The composition of plagioclase in the quartz diorite dykes (DK1a, DK1b and DK1c) varies from albite-oligoclase to andesine and oligoclase to andesine; in the diorite, it varies from andesine to labradorite; in the LAM, from albite to oligoclase; and in the microdiorite (MDI), it occurs as albite. Amphibole compositions are consistent with classification as hornblende or calcic amphibole. Based on their AlIV value (less than 1.5), amphibole compositions are consistent with an active continental margin affinity. The average percentage of pistacite (Ps) in epidotes formed from alteration of plagioclase and ferromagnesian minerals is 27–23% and 25–30%, respectively. Thermobarometric studies based on amphibole and biotite indicate approximate dyke crystallization temperature of 850–750℃, pressure of 231–336 MPa and high fO2 (>nickel-nickel-oxide buffer). The range of mineral compositions in the postmineralization dyke suite is consistent with a genetic relationship with the subduction of the Neotethys oceanic crust beneath the continental crust of the northwest part of the Central Iranian Structural Zone. Despite the change from calc-alkaline to alkaline magmatism, the dykes are likely related to the late stages of magmatic activity in the subduction system that also generated the porphyry deposit.

Multi-scale exploration of giant Qulong porphyry deposit in a collisional setting

2021 ◽  
Vol 139 ◽  
pp. 104455
Author(s):  
Zehua Han ◽  
Rui Wang ◽  
Xuesong Tong ◽  
Fei Sun ◽  
Yuyao Li ◽  
...  
Keyword(s):  
Porphyry Deposit ◽  
Multi Scale

Classifying Copper-Molybdenum-Gold Porphyry Deposit Alteration using Magnetic and Spectral data

2021 ◽  
Author(s):  
Oliver Dixon ◽  
William McCarthy ◽  
Nasser Madani ◽  
Michael Petronis ◽  
Steve McRobbie ◽  
...  
Keyword(s):  
Machine Learning ◽  
Magnetic Susceptibility ◽  
Spectral Data ◽  
Learning Algorithm ◽  
Copper Production ◽  
Magnetic Data ◽  
Machine Learning Algorithm ◽  
Porphyry Deposit ◽  
Remanent Magnetisation ◽  
Magnetic Remanence

<p>Copper is one of the most important critical metal resources needed to achieve carbon neutrality with a projected increase in demand of >300% over the next half century from electronics and renewables.  Porphyry deposits account for most of the global copper production, but the discovery of new reserves is ever more challenging. Machine learning presents an opportunity to cross reference new and traditionally under-utilised data sets with a view to developing quantitative predictive models of hydrothermal alteration zones to guide new, ambitious exploration programs.</p><p>The aim of this study is to demonstrate a new alteration classification scheme driven by quantitative magnetic and spectral data to feed a machine learning algorithm. The benefits of an alteration model based on quantitative data rather than subjective observations by geologists, are that there is no bias in the data collected, the arising model is quantifiable and therefore easy to model and the process be fully automated. Ultimately, this approach aids more detailed exploration and mine modelling, in turn, reducing the extraction process carbon footprint and more effectively identifying new deposits.</p><p>Presented here are magnetic susceptibility and shortwave infrared (SWIR) data collected from the KazMinerals plc. owned Aktogay Cu-Mo giant porphyry deposit, eastern Kazakhstan, which has a throughput of 30Mtpa of ore. These data are cross referenced using a newly developed machine learning algorithm. Generated autonomously, our results reveal twelve statistically and geologically significant clusters that define a new alteration classification for porphyry style mineralisation. Results are entirely non-subjective, reproducible, quantitative and modellable.</p><p>Importantly, magnetic susceptibility measurements improve the algorithm’s ability to identify clusters by between 29-36%; enhancing the sophistication of the included magnetic data promises to yield substantially better statistical results. Magnetic remanence data are therefore being complied on representative samples from each of the twelve identified clusters, including hysteresis, isothermal remanent magnetisation (IRM) acquisition, FORC measurements, natural remanent magnetisation (NRM) and anhysteretic remanent magnetisation (ARM). Through collaboration with industry partners, we aim to develop an automated means of collecting these magnetic remanence data to accompany the machine learning algorithm.</p>

Volatile exsolution at the Dinkidi Cu-Au porphyry deposit, Philippines: A melt-inclusion record of the initial ore-forming process

Geology ◽  
1999 ◽  
Vol 27 (8) ◽  
pp. 691 ◽  
Author(s):  
Vadim S. Kamenetsky ◽  
Rohan C. Wolfe ◽  
Stephen M. Eggins ◽  
Terrence P. Mernagh ◽  
Evgeniy Bastrakov
Keyword(s):  
Melt Inclusion ◽  
Forming Process ◽  
Porphyry Deposit ◽  
Volatile Exsolution

Application of an ordinary kriging–artificial neural network for elemental distribution in Kahang porphyry deposit, Central Iran

2020 ◽  
Vol 13 (15) ◽  
Author(s):  
Amir Bijan Yasrebi ◽  
Ardeshir Hezarkhani ◽  
Peyman Afzal ◽  
Reza Karami ◽  
Mohammad Eskandarnejad Tehrani ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Ordinary Kriging ◽  
Central Iran ◽  
Elemental Distribution ◽  
Porphyry Deposit ◽  
Artificial Neural

scholarly journals Platinum mineralization comparative characteristics of the some Far East deposits

2018 ◽  
Vol 56 ◽  
pp. 04017
Author(s):  
Natalya Lavrik ◽  
Natalya Litvinova ◽  
Tatyana Aleksandrova ◽  
Valentina Stepanova ◽  
Alexandra Lavrik
Keyword(s):  
Far East ◽  
Manganese Ore ◽  
Gold Content ◽  
Alternative Source ◽  
Porphyry Deposit ◽  
Copper Porphyry ◽  
Native Silver ◽  
Iron Manganese ◽  
Platinum Mineralization

In this article shown platinum mineralization comparative characteristics for three deposits: Kondoer-traditional unique deposit and other two probably alternative source of platinum: the Poperechnoe ironmanganese deposit and the Malmyzh copper-porphyry deposit. Platinoids of the Kondoer deposit are the chain Pt>>Ir>Os>Ru=Rh>Pd. The presences of platinum crystals are characteristic, there are over 50 rare and new platinoids minerals in different combinations. There are gold and silver. Platinoids from the iron-manganese ore of Poperechnoe are as Pt>>Rh≈Ir>Ru≈Os>Pd. A scattered dissemination of arsenide sulfate and sulfides of Rh, Ir, Ru, Os are noted in the platinum. Palladium is present as impurities in gold and platinum. The gold content is different-with admixtures Ag, Pb, Cd, Fe. At this stage the platinoids content in oxidized ores of the Malmyzh gold-copper porphyry deposit is Pt ≈ Pd. The gold is present as electrum. There is native silver cadmium.

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