Petrolab are proud sponsors of Process Mineralogy 2022 in Sitges, Spain this week – a picturesque town on the Mediterranean coast famed for its beaches, artistic culture and historical sites.
Petrolab technical specialists will also be presenting two papers within the main conference, one on selecting the best analytical toolkits depending on the aims of any given analysis and a second paper on the importance of sample preparation for the analysis of automated mineralogy, (see further details below).
Petrolab will be maintaining a booth within the exhibition centre adjacent to the conference room and would be delighted to chat to anyone at the conference who would like to find out more about our technical capabilities, experience and equipment.
Paper 1: Selecting the best tools for your mining project – Knowing when to use and combine techniques including optical petrography, XRD and automated mineralogy
Zajac, M ., Brough C., Garner C., Strongman J., Fletcher J.
Over the past decades, the assay was and remains the most common way to analyse samples on and off-site primarily due to its low cost, simple and translatable numerical values, and fast analysis time, producing results in a matter of hours. However, despite these cheap and convenient reasons, it appears that the assay is often delaying the inevitable consequence of obtaining more detailed mineralogical results in order to interpret the assay data in the correct context. Whilst assay data may have identified unwanted penalty elements or appreciable concentrations of target elements, it is not possible to determine where these elements are hosted or what may be responsible for factors such as poor recovery or low concentrate grades. Assay provides us only with a list of elemental values, and instead of being a definitive technique to drive processing, it should more appropriately be treated as an early warning system to guide and tailor mineralogical investigations. Providing assay information upfront can indicate potential problems or recoverable assets that a mineralogist can use to tailor further analysis using techniques including quantitative XRD, optical petrography, and/or automated mineralogy. This paper aims to compare and contrast the different techniques available to a mineralogist and how and when to combine different approaches to give a robust and efficient investigation. A combined approach can in turn be implemented at various stages during the mine cycle and although it may initially take more time, the time saved further down the line is often far greater with the knowledge applied for future use to prevent reoccurring issues. Three case studies will be used to evidence how a tailored multi-purpose approach to mineralogy has solved difficult issues related to mineral processing, complex textural relationships, and remediation/repurposing of mine waste which were unable to be identified using a single analytical method.
Paper 2: The importance of sample preparation techniques for use in automated mineralogy
Garner C., Strongman J., Staniforth B., Fletcher J., Brough C., Zajac M. (Petrolab Limited, UK)
The use of automated mineralogy has been critical in understanding all stages of a mine cycle including the identification of potential ore phases for exploration projects, routine composites for monthly mineralogy trends including liberation of target phases plus identification of penalty phases for mine closure, and the potential of reactions like carbon sequestration from mine waste in order to ensure efficient remediation. Whilst automated mineralogy is clearly a key technique, the quality of the data and how ‘automated’ the actual automated mineralogy process is, is driven by the accuracy and efficiency of sample preparation techniques. The need for on-site operational mineralogy is growing, along with the need for rapid turnaround of data to drive processing plants. This paper discusses the effects of poor sample preparation on the quality of automated mineralogy data outputs including liberation metrics, mineral abundance and grain size. Potential sources for error from preparation techniques include inefficient cleaning of all utensils and the block itself; poor screening, deagglomeration and polishing of the sample; and the desire to streamline these preparation techniques for optimisation of mine site laboratories in order to rapidly generate data to monitor daily processing plant activity. A further discussion touches on how automated is automated mineralogy, establishing that a large percentage of the process depends on the efficiency and accuracy of sample preparation and that research should be focused on optimising this stage of the process.