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Trace element composition of scheelite in orogenic gold deposits

  • Marjorie SciubaEmail author
  • Georges BeaudoinEmail author
  • Donald Grzela
  • Sheida Makvandi
Article
  • 208 Downloads

Abstract

Scheelite from 25 representative orogenic gold deposits from various geological settings was investigated by EPMA (electron probe micro-analyzer) and LA-ICP-MS (laser ablation-inductively coupled plasma-mass spectrometer) to establish discriminant geochemical features to constrain indicator mineral surveys for gold exploration. Scheelite from orogenic gold deposits displays five REE patterns including a bell-shaped pattern with a (i) positive or (ii) negative Eu anomaly; (iii) a flat pattern with a positive Eu anomaly and, less commonly, (iv) a LREE-enriched pattern, and (v) a HREE-enriched pattern. The REE patterns are interpreted to reflect the source of the auriferous hydrothermal fluids and, perhaps, co-precipitating mineral phases. Scheelite from deposits formed in rocks metamorphosed at upper greenschist to lower amphibolite facies have low contents in REE, Y, and Sr, and high contents in Mn, Nb, Ta, and V, compared to scheelite formed in rocks metamorphosed below the middle greenschist facies. Scheelite from deposits hosted in sedimentary rocks has high Sr, Pb, U, and Th, and low Na, REE, and Y, compared to that hosted in felsic to intermediate rocks. Statistical analysis including elemental plots and multivariate statistics with PLS-DA (partial least square-discriminant analysis) reveal that the metamorphic facies of the host rocks as well as the regional host rock composition exert a strong control on scheelite composition. This is a result of fluid-rock exchange during fluid flow to gold deposition site. PLS-DA and elemental ratio plots show that scheelite from orogenic gold deposits have distinct Sr, Mo, Eu, As, and Sr/Mo, but indistinguishable REE signatures, compared to scheelite from other deposit types.

Keywords

Scheelite Orogenic gold deposits Trace elements Cathodoluminescence Principal component analysis Partial least square-discriminant analysis 

Notes

Acknowledgments

People and mining companies who collaborated are gratefully thanked: Acacia Mining, AngloGold Ashanti, D. Craw (Otago University), C. Daoust, A. Dziggel (Aachen University), Goldcorp, S. Hagemann (UWA), A. Hellmann (Aachen University), IAMgold, R. Large (University of Tasmania), L. M. Lobato (Universidade Federal de Minas Gerais), N. Maneglia (Université Laval), A. Mueller (UWA), F. Robert (Barrick), Royal Ontario Museum, N. Thébaud (UWA). M. Choquette (Université Laval), D. Savard, and M. Kudrna Prasek (UQAC) are thanked for the technical assistance with EPMA and LA-ICP-MS analyses. Roman Hanes is thanked for his help to elaborate the discussion. We thank the reviewers and Editor B. Lehmann for their insightful comments that help improve our contribution significantly.

Funding information

The research is funded by Agnico Eagle Mines Ltd., the Ministère de l’Énergie et des Ressources Naturelles du Québec and the Natural Sciences and Engineering Research Council.

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Département de Géologie et Génie GéologiqueUniversité LavalQuébecCanada
  2. 2.Centre de recherche sur la géologie et l’ingénierie des ressources minérales (E4m)QuébecCanada

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