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Prediction of Acid Rock Drainage from Automated Mineralogy

Parbhakar-Fox, A ORCID: 0000-0002-3570-1195, Lottermoser, B, Hartner, R, Berry, RF ORCID: 0000-0002-5547-3396 and Noble, TL ORCID: 0000-0002-5708-751X 2017 , 'Prediction of Acid Rock Drainage from Automated Mineralogy', in B Lottermoser (ed.), Environmental Indicators in Metal Mining , Springer International Publishing, Switzerland, pp. 139-156.

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Abstract

Automated mineralogy tools are now commonly used during mineral processing for particle characterization to help mine operators evaluate the efficiency of the selected mineral processing techniques. However, such tools have not been efficiently used to assist in acid rock drainage (ARD) prediction. To address this, the computed acid rock drainage (CARD) risk grade protocol was developed. The CARD risk grade tool involves: (1) appropriate selection of samples (i.e., following a geometallurgical sampling campaign); (2) careful preparation of a particle mount sample; (3) analysis on a mineral liberation analyser (MLA) using the X-ray modal analysis (XMOD) function; (4) processing of the XMOD data to produce a whole particle mount backscattered electron (BSE) image and a corresponding image of classified XMOD points; (5) fusion of both images to obtain particle area data; (6) calculation of the CARD risk ratio based on carbonate and sulfide particle areas, relative reactivities (pHCaCl2 − pHmineral+CaCl2) and acid forming/neutralizing values (calculated based on mineral chemistry and stoichiometric factors, kg H2SO4/t); and (7) classification of CARD risk ratios ranging from extreme risk to very-low risk. Testing of the CARD risk grade tool was performed on materials selected from several mine sites representative of both run-of-mine ore and waste. This testing proved that CARD can be effectively used to map ARD risks on a deposit scale and forecast geoenvironmental risk domains at the earliest life-of-mine phases.

Item Type: Book Section
Authors/Creators:Parbhakar-Fox, A and Lottermoser, B and Hartner, R and Berry, RF and Noble, TL
Keywords: acid mine drainage, sulfide oxidation, MLA-SEM, prediction, mineralogy, mining
Publisher: Springer International Publishing
DOI / ID Number: 10.1007/978-3-319-42731-7_8
Copyright Information:

Copyright 2017 Springer International Publishing Switzerland

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