THE IMPORTANCE OF MINERAL DEFINITIONS USED IN GENERATING QEMSCAN DATA

The most common approach to assessing the accuracy of QEMSCAN mineralogy results is to compare the measured assay with the mineralogy-computed chemical assay. In this method we assume the measured assay results are the correct values, which means we also assume that the sub-samples used for chemical assay and QEMSCAN analysis are identical, or equally representative, and that the SEM-EDS sample preparation procedure has not introduced any bias. However, the nature of QEMSCAN data means that is quite easy to achieve an acceptable reconciliation of less than 10 or 15% (depending on the element) with very different mineralogy results.

QEMSCAN systematically scans across the sample surface collecting chemical data at each point, which is converted to mineralogy results using a Species Identification Protocol (SIP). Commercial laboratories develop their own in-house SIPs, which typically the client will not have access to. The SIP definitions and the properties used to compute QEMSCAN chemical assays are crucial for the assessment of assay reconciliation and the accuracy of mineralogy results.

To demonstrate the importance of accurate SIP definitions and correct mineral groupings we compiled two sets of QEMSCAN data based on two different sets of SIP definitions and mineral groupings. Using a sphalerite concentrate sample the number of pixels captured by the combined sphalerite definitions is the same in both cases, yet the computed mass percent is significantly different.

In the above example, the “Sphalerite” definition for SIP 1 captures the majority of pixels that contain Zn and S and only a minor amount is captured by the “Sphalerite boundary” definition. The “Sphalerite” definition for SIP 2 is set with narrower element ranges compared to SIP 1 and therefore does not capture the majority of pixels with Zn and S. Many pixels are instead captured by the “Sphalerite boundary” definition. Here, the densities of the “Sphalerite” and “Sphalerite boundary” definitions at the Primary mineral list level are very different, which has a significant impact on the final result with total sphalerite at 27% and 18% for SIPs 1 and 2 respectively. Here SIP 1 with its associated Primary mineral list produces a better assay reconciliation.

The MinAssist data validation service gives you the opportunity to review the SIP definitions and the mineral properties used to process your data. This involves a review of the raw data in order to detect obvious SIP and mineral list errors. For example, errors detected in previous projects include, but are not limited to, using the wrong density for a mineral, grouping SIP definitions into the wrong mineral group, and using SIP definitions with broad element ranges, resulting in several minerals being classified together.

The information in this article is based on QEMSCAN data, however, the principal of ensuring that the correct reference information is used for mineral computations applies to many other techniques. Contact Melissa or Pieter at MinAssist if you use QEMSCAN mineralogy results regularly and have datasets that you would like to validate.