Gold deportment and ore characterisation studies are key tools in gaining an appropriate understanding of complex gold ores for process development and optimisation. These studies have historically involved imprecise chemical methods with slow and costly optical microscopy for gold identification. The traditional approach requires highly skilled petrographers, is prone to human error, and is not scalable, reducing the usefulness in practical analysis._x000D_
The proposed methodology utilises a decision tree and knowledge base in a staged approach to gold ore characterisation, building up progressively more detailed information about the sample mineralogy, gold deportment and key mineral properties, as the process is followed. Whilst the automated QEMSCAN system is used for mineral and gold identification, interactive and focused data analyses are used to give more efficient and accurate results. This is complemented by smart sample preparation and chemical methods to enhance and validate the data, making the staged approach methodology reliable, scalable and therefore practical and economical.