Parameters influencing the microbial oxidation activity in the industrial bioleaching heap at Escondida mine, Chile

The industrial run of mine (ROM) bioleaching heap of Escondida mine is monitored monthly from Pregnant Leach Solution (PLS) to assess concentration of microorganisms, microbial activity and physicochemical parameters generating a huge amount of information. To obtain a better description of the iron microbial activity and the dissolution rate of sulfide ores occurring in the leaching cycle, iterative process based on “Knowledge Discovery in Databases” (KDD) was used. A data mining technique, called “hierarchical clustering”, was employed with mineralogical characteristics of the ores loaded in the heap as input. Three different groups of strips were distinguished by this model. Chalcocite and chalcopyrite contents were the most relevant parameters selected by “decision tree” technique. The results showed that there was a good coincidence between the three groups defined and the metallurgical performance in terms of copper recovery. er, another decision tree analysis was performed including the three mineralogical groups, the gathered data about physicochemical parameters and the microbial community composition and function from the PLS. The PLS temperature and the MPN were the most relevant factors selected to explain the differences between the operation of the defined groups of strips. The group with the lowest chalcocite and highest chalcopyrite content, reached the highest PLS temperature and the highest MPN of ferrous iron oxidizing microorganisms and also the fastest kinetics of copper recovery. timated temperature inside the heap following conservatively the available models for heaps loaded with agglomerated material, together with the sustainable occurrence of a moderate thermophile population and the confirmation of some chalcopyrite dissolution by analysis of tail allowed us to account the chalcopyrite as a microbial substrate in that industrial scale operation. results confirmed the relationship between the microbial community function and the copper release and the hypothesis that the substrate availability is an important parameter to describe the microbial activity. Nevertheless, the model is not yet able to explain the low bacterial growth in the group with the highest chalcocite content that is considered a good microbial substrate. Then it is needed to perform another cycle of the KDD process to complete the model. This kind of information should be considered in defining models to describe and to predict copper recovery in ROM industrial bioleaching processes.