Work

Monazite chemistry for iron sulfide-copper-gold exploration in the Mount Isa Province, Queensland, Australia

Year: 2026

Type: article

Abstract: The chemistry of hydrothermal monazite can be used as an indicator of iron sulfide-copper-gold (ISCG) mineralisation based on a case study of the Kulthor deposit in the Cloncurry District. Monazite associated with mineralisation has elevated La, Nd and S, and a moderately negative chondrite-normalised Eu anomaly, and is typically polycrystalline and intimately associated with pyrite, pyrrhotite and chalcopyrite. Monazite from mineralised and unmineralised rocks can be separated on a plot of Ce versus La + Nd using a line with the equation y = 0.95x. Monazite that is found within unmineralised rocks is enriched in Y, Dy, Th and U relative to mineralised samples and have a strong negative chondrite-normalised Eu anomaly. A plot of Y versus Dy shows two distinct gradients for the monazite analyses, whereby monazite analyses in unmineralised rocks follow the gradient of 0.24 (r 2 = 0.946), in contrast to mineralisation-associated and proximal monazite analyses which follow a gradient of 0.47 (r 2 = 0.889). Monazite grains from unmineralised rocks have well defined, jagged grain boundaries and commonly contain inclusions of zircon, apatite, rutile and xenotime. Integration of monazite data from Kulthor with a previous study on the nearby Jericho ISCG deposit allowed development of geochemical discrimination diagrams for ISCG deposits whereby Ca/Th ratios >5 and S/Th ratios >0.1 are indicative of monazite associated with ISCG mineralisation. • New monazite ISCG exploration criteria are proposed. • Monazite from mineralisation has high S/Th, Ca/Th, La and Nd. • Y versus Dy provides insight into temperatures of mineralisation. • Criteria based on S/Th and Ca/Th in monazite from ISCG deposits in Cloncurry.

Source: Applied Geochemistry

DOI: 10.1016/j.apgeochem.2025.106674

Authors: Travis Batch, Caroline Tiddy, Adrienne Brotodewo, David Giles, Courteney Dhnaram, Vladimir Lisitsin

Institutions: University of South Australia, Queensland Department of Natural Resources, Mines and Energy, Queensland Government

Language: English

Topic: Geochemistry and Geologic Mapping

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,490

Funders: University of South Australia, Mineral Exploration Cooperative Research Centre