MAPPING THE MINERAL ZONATION AT THE ERNEST HENRY IRON OXIDE COPPER-GOLD DEPOSIT: VECTORING TO Cu-Au MINERALIZATION USING MODAL MINERALOGY

Iron oxide copper-gold (IOCG) deposits form in spatial and genetic relation to hydrothermal iron oxide-alkali-calcic-hydrolytic alteration and thus show a mappable zonation of mineral assemblages toward the orebody. The mineral zonation of a breccia matrix-hosted orebody is efficiently mapped by regularly spaced samples analyzed by the scanning electron microscopy-integrated mineral analyzer technique. The method results in quantitative estimates of the mineralogy and allows the reliable recognition of characteristic alteration as well as mineralization-related mineral assemblages from detailed mineral maps. The Ernest Henry deposit is located in the Cloncurry district of Queensland and is one of Australia’s significant IOCG deposits. It is known for its association of K-feldspar altered clasts with iron oxides and chalcopyrite in the breccia matrix. Our mineral mapping approach shows that the hydrothermal alteration resulted in a characteristic zonation of minerals radiating outward from the pipe-shaped orebody. The mineral zonation is the result of a sequence of sodic alteration followed by potassic alteration, brecciation, and, finally, by hydrolytic (acid) alteration. The hydrolytic alteration primarily affected the breccia matrix and was related to economic mineralization. Alteration halos of individual minerals such as pyrite and apatite extend dozens to hundreds of meters beyond the limits of the orebody into the host rocks. Likewise, the Fe-Mg ratio in hydrothermal chlorites changes systematically with respect to their distance from the orebody. Geochemical data obtained from portable X-ray fluorescence (p-XRF) and petrophysical data acquired from a magnetic susceptibility meter and a gamma-ray spectrometer support the mineralogical data and help to accurately identify mineral halos in rocks surrounding the ore zone. Specifically, the combination of mineralogical data with multielement data such as P, Mn, As, P, and U obtained from p-XRF and positive U anomalies from radiometric measurements has potential to direct an exploration program toward higher Cu-Au grades.

Resolution Enhancement for Drill-Core Hyperspectral Mineral Mapping

Drill-core samples are a key component in mineral exploration campaigns, and their rapid and objective analysis is becoming increasingly important. Hyperspectral imaging of drill-cores is a non-destructive technique that allows for non-invasive and fast mapping of mineral phases and alteration patterns. The use of adapted machine learning techniques such as supervised learning algorithms allows for a robust and accurate analysis of drill-core hyperspectral data. One of the remaining challenge is the spatial sampling of hyperspectral sensors in operational conditions, which does not allow us to render the textural and mineral diversity that is required to map minerals with low abundances and fine structures such as veins and faults. In this work, we propose a methodology in which we implement a resolution enhancement technique, a coupled non-negative matrix factorization, using hyperspectral, RGB images and high-resolution mineralogical data to produce mineral maps at higher spatial resolutions and to improve the mapping of minerals. The results demonstrate that the enhanced maps not only provide better details in the alteration patterns such as veins but also allow for mapping minerals that were previously hidden in the hyperspectral data due to its low spatial sampling.

The Rocklea Dome 3D Mineral Mapping Test Data Set

The integration of surface and subsurface geoscience data is critical for efficient and effective mineral exploration and mining. Publicly accessible data sets to evaluate the various geoscience analytical tools and their effectiveness for characterisation of mineral assemblages and lithologies or discrimination of ore from waste are however scarce. The open-access Rocklea Dome 3D Mineral Mapping Test Data Set (Laukamp, 2020; https://doi.org/10.25919/5ed83bf55be6a) provides an opportunity for evaluating proximal and remote sensing data, validated and calibrated by independent geochemical and mineralogical analyses, for exploration of channel iron deposits (CIDs) through cover. We present hyperspectral airborne, surface, and drill core reflectance spectra collected in the visible–near-infrared and shortwave infrared wavelength ranges (VNIR–SWIR; 350 to 2500 nm), as well as whole-rock geochemistry obtained by means of X-ray fluorescence analysis and loss-on-ignition measurements of drill core samples. The integration of surface with subsurface hyperspectral data collected in the frame of previously published Rocklea Dome 3D Mineral Mapping case studies demonstrated that about 30 % of exploration drill holes were sunk into barren ground and could have been of better use, located elsewhere, if airborne hyperspectral imagery had been consulted for drill hole planning. The remote mapping of transported Tertiary detritals (i.e. potential hosts of channel iron ore resources) versus weathered in situ Archaean bedrock (i.e. barren ground) has significant implications for other areas where “cover” (i.e. regolith and/or sediments covering bedrock hosting mineral deposits) hinders mineral exploration. Hyperspectral remote sensing represents a cost-effective method for regolith landform mapping required for planning drilling programmes. In the Rocklea Dome area, vegetation unmixing methods applied to airborne hyperspectral data, integrated with subsurface data, resulted in seamless mapping of ore zones from the weathered surface to the base of the CID – a concept that can be applied to other mineral exploration and mineral deposit studies. Furthermore, the associated, independent calibration data allowed the quantification of iron oxide phases and associated mineralogy from hyperspectral data. Using the Rocklea Dome data set, novel geostatistical clustering methods were applied to the drill core data sets for ore body domaining that introduced scientific rigour to a traditionally subjective procedure, resulting in reproducible objective domains that are critical for the mining process. Beyond the previously published case studies, the Rocklea Dome 3D Mineral Mapping Test Data Set has the potential to develop new methods for advanced resource characterisation and develop new applications that aid exploration for mineral deposits through cover. The white mica and chlorite abundance maps derived from airborne hyperspectral, presented here for the first time, highlight the additional applications of remote sensing for geological mapping and could help to evaluate newly launched hyper- and multispectral spaceborne systems for geoscience and mineral exploration.