Modelling the reactivity of multi-mineral systems – Application to prediction of copper heap leach drain-down chemistry

Author(s): 
David Bird, Rob Bowell, Julien Declercq
Date: 
Tuesday, August 15, 2017
First presented: 
Goldschmidt 2017
Type: 
Presentation
Category: 
Geochemistry
 
 
Geochemical models are used in the mining industry for a range of applications in the forecasting of long term environmental impacts, including predictions of tailings and waste rock seepage chemistry, post-closure pit lake chemistry, heap drain-down chemistry, fate-transport of mining related impacts, and others. The less complex versions of these applications may rely on simple mixing models or assumptions that the primary controls on solution chemistry are equilibrium-based. However, the knowledge and understanding of mineral reaction kinetics has advanced significantly in recent years. Consequently modelers are able to integrate a more realistic array of geochemical reactions into predictive models to provide a more representative approximation of complex environments.
 
The findings reported here were part of a project to predict long-term drain-down seepage chemistry from a decommissioned copper heap leach pad associated with a porphyry copper mine. The geochemical model incorporated mineral reaction rate parameters available at the time from published literature. The model has since been updated to assess a comparison of those findings with a predictive model based on newly defined kinetic rate parameters.
 
This study is another in the series of demonstration applications that SRK has developed based on the initial work on the Carbfix Project [1], and applies its equations to the definition of a kinetic model of a mine waste rock facility. Through comparison of results and methodology of a kinetic and equilibrium approach to the same system, the use of kinetic models has been shown as equally valid as a prediction tool, and forms the basis for further developments: e.g. to inform the laboratory testwork that can best represent real world conditions within a numerical model.
 
[1] Declercq & Oelkers, 2014. CarbFix WP5 Project no. 281348
SRK North America