Using radiometric data to generate automated alteration maps based on residual values

The radiometric spectrometry method is a geophysical tool used to estimate concentrations of potassium, uranium, and thorium by measuring gamma rays emitted by radioactive isotopes of these elements during radioactive decay. All rocks and soils contain radioactive isotopes, and almost all gamma rays detected close to the Earth’s surface are the result of natural radioactive decay of potassium, uranium, and thorium. Gamma rays have fairly high penetrating power and can travel about 35 centimetres through rock and several hundred metres through air. The gamma-ray spectrometry method has many applications but is mainly used as a geological mapping tool. Changes in lithology or soil type are often accompanied by changes in radioelement concentrations. Some alteration profiles, such as potassic alteration, which is often associated with hydrothermal deposits, can be detected using gamma ray spectrometry.

In outcropping or low-coverage environments, it is thus possible to map the different lithologies and potentially estimate changes in potassium and uranium concentrations caused by alteration processes. For this case study, we used automated clustering algorithms to establish the different lithological groups according to the radiometric and magnetic signatures, coupled with geological calibration. Once the dictionary of lithology is created for the study area, it is possible to estimate changes in mass for potassium and uranium, which are characteristic of the various alteration processes. Indeed, the immobile nature of thorium allows us to estimate thorium-potassium and thorium-uranium regression and also actually calculate the residual values for the more mobile elements, potassium and uranium, which can be affected by hydrothermal fluid circulation. This mapping method makes it possible to highlight zones of leaching and deposition of these radiometric elements.

This approach permits rapid generation of much more accurate alteration maps than the ternary maps traditionally used for exploration of mineral systems associated with IOCG, uranium, porphyry, and other systems that have a large footprint and affect potassium and uranium compositions.

Case study: Labrador Trough Alteration Map, Canada

In order to test the workflow proposed above, we chose the Labrador Trough at the Québec-Labrador border because of its low level of Quaternary cover and potential for IOCG mineral deposits. These types of deposits come with a substantial alteration footprint that might be mappable using the automated approach proposed here. The data was downloaded from the Quebec public repository (Fig.1) and regridded at a 500m x 500m resolution for fast processing.

Figure 1: High resolution Thorium concentration (ppm). CC BY 4.0 - SIGÉOM, Gouvernment of Québec 2019

First, lake and swamp-environment signatures were taken out of the survey using a first round of clustering and domaining. This allowed us to concentrate on the signatures associated with the rock units. Following this first step, the magnetics data was also processed using a high pass filter to focus on the short-wavelength signature associated with near-surface changes in the magnetics. The data set consisting of the potassium, thorium, uranium, and magnetics was run through a hierarchical clustering algorithm. This algorithm enabled us to group the datapoints (grid cells) into domains of similar signatures in the 4 input dimensions. The advantage of using this type of algorithm lies in its interpretability and customizability in terms of resulting clusters. Given the model’s performance and entropy (Fig. 2), it was established that 8 clusters existed in the data set, representing probable geological domains.

Figure 2: Clusters representing probable geological domains.

Using those 8 geological domains, 3D regressions were estimated for potassium from uranium and thorium, for uranium from potassium and thorium and for thorium from potassium and uranium. A regression for each domain was estimated and the residual values for each element were then calculated (Fig. 3).

A regression for each domain was estimated and the residual values for each element were then calculated.

Lastly, the 3 residual maps are combined to generate an alteration map for potassium and uranium mass balances potentially associated with IOCG alteration (Fig. 4). When comparing the alteration map to the known deposits, certain trends become visible (Fig. 4). It especially appreciable around the Romanet Horst region (Fig. 5).

Alteration map for potassium and uranium mass balances potentially associated with IOCG alteration with visible trends.

Alteration map of the Romanet Horst region, Canada.

Jean-Philippe is our Director of Global Consulting. He brings 10 years of mineral exploration experience including expertise in geostatistics, structural, geological, and geochemical modelling and interpretation. He is skilled in the application of machine learning to overcome geological challenges and with new methods to reduce interpretational risks with geological data. He has a wide range of experience in mineral resource estimation for precious metals, base metals and industrial minerals across diverse geological environments around the world. He obtained an MSc from Laval University. Jean-Philippe is based in Quebec-City.

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