Maintaining Sample Data Quality Through Robust Quality Assurance and Quality Control Protocols

Successful evaluation and exploitation of resources and reserves relies on the collection of high quality sample data. The quality of the sample data must be maintained through the application of a robust quality assurance and quality control (QAQC) program, including documentation of sampling procedures, training of sampling personnel and the regular monitoring of control samples. However, the application of QAQC programs in the minerals industry is often poor and the purpose misunderstood. It is all too common to have good quality control data collected, but no analysis work carried out until after drilling is completed. In a lengthy drill program, this can lead to problems not being discovered and corrected as they happen. Moreover, rectifying problems afterwards will be costly in terms of time and money, if not impossible. The consequences of poor quality sample data are many and include such effects as over- or underestimation of block grades, misclassification of ore and waste, and lower confidence in the resource/reserve models. The purpose of this paper is to highlight, using case studies, the importance of good QAQC practices to monitor the quality of sampling and laboratory sample preparation and analysis.