Practical applications of quality assurance and quality control in mineral exploration, resource estimation and mining programmes: a review of recommended international practices

Author:

Smee Barry W.1,Bloom Lynda2,Arne Dennis3ORCID,Heberlein David4

Affiliation:

1. Smee and Associates Consulting Ltd., North Vancouver, British Columbia V7R 4K3, Canada

2. Lynda Bloom, Analytical Solutions Ltd, Mulmur, Ontario L9V 0L1, Canada

3. Telemark Geosciences Pty Ltd, Yackandandah, Victoria 3749, Australia

4. Heberlein Geoconsulting, Maple Ridge, British Columbia V2X 8L9, Canada

Abstract

Independent quality assurance and quality control (QA/QC) programmes are required by reporting codes for publicly listed companies and are necessary to optimize data quality at all stages of the sampling, preparation and analytical processes involved in mineral exploration, resource estimation and mining grade control. QA/QC programmes should be adjusted over time to meet changing requirements in data quality at different stages of mineral resource development and exploitation. Certified reference materials are used to monitor accuracy and bias at the project laboratory relative to consensus values for the material from round-robin certification analyses. They are also used to monitor drift over time within an individual laboratory and to identify significant failures in QC at the analytical batch level caused by abrupt changes in concentration related to re-calibration of instruments or procedural changes at the laboratory. Duplicate analyses of sample material are generated at key stages of sampling and preparation to estimate the precision of data generated at each stage. Invariably, the largest source of uncertainty occurs during the initial sampling. Coarse blanks are used to monitor cross-contamination between samples or from sample preparation equipment. Furthermore, each of these QC sample types can be used to discover possible sample mix-ups. Supplementary material: An Excel spreadsheet for the calculation of the average coefficient of variation (CV AVE ) (Appendix C) is available at https://doi.org/10.6084/m9.figshare.c.7070137 Thematic collection: This article is part of the Reviews in Exploration Geochemistry collection available at: https://www.lyellcollection.org/topic/collections/reviews-in-exploration-geochemistry

Publisher

Geological Society of London

Reference20 articles.

1. Quality Control of Assay Data: A Review of Procedures for Measuring and Monitoring Precision and Accuracy

2. Sampling Errors and Control of Assay Data Quality in Exploration and Mining Geology

3. ASTM -178 2011. Standard practice for dealing with outlying observations. In: Book of Standards Developed by Subcommittee: E11.10 14.01 11. ICS Code: 03.120.30 https://doi.org/10.1520/E0178-21

4. Geochemical data quality: the ‘fit-for purpose’ approach;Bettany L.;Explore: Newsletter of the Association of Exploration Geochemists,2001

5. CIM Mineral Resource and Mineral Reserve Committee 2018. CIM Mineral Exploration Best Practice Guidelines. Canadian Institute of Mining Metallurgy and Petroleum Westmount Quebec https://mrmr.cim.org/media/1163/cim-mineral-exploration-best-practice-guidelines-2018.pdf

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