TTE293

ABSTRACT

The Encuentro deposit is situated in the Centinela Mining District (DMC), 30 km southeast

of Sierra Gorda, in the Antofagasta region, near the trace of the Centinela fault, one of the

main branches of the Domeyko Fault System. Within this NNE-trending and 40 km long

strip, it exhibits associations of intrusive, volcanic, and sedimentary rocks from the Triassic

Jurassic, along with Upper Cretaceous and Paleogene volcanic and intrusive rocks. This fault

system controls the placement of mineralized porphyries with ages ranging from 41 to 45

Ma, linked to the Eocene-Oligocene metallogenic belt.

In previous studies, Geometallurgical Units (UGMs) for sulfuric acid consumption were

defined and modeled based on carbonate content distribution, without considering the

geology of the Encuentro deposit. Carbonate content greater than 0,5% was deemed relevant

for operations. However, sulfuric acid consumption (CAN) was not accurately estimated for

areas of the deposit where carbonate is less than 0,5%.

Reanalyzing information from metallurgical tests on ISO-pH bottles, it is proposed to define

three Geometallurgical Units based on the deposit's geology for areas with carbonate content

less than 0,5%. UGM1, with an average net acid consumption of 4,3 kg/t, represents potassic

feldspar alteration (KF). UGM2 is defined for those with an average net acid consumption of

8,9 kg/t in response to potassic biotitic alteration (KBT) and sericite (SER). For UGM3, the

average net acid consumption is 11,4 kg/t in response to the influence of chlorite-sericite

alteration (CS). UGM4 and UGM5 are primarily defined by the PORDAC (22 kg/t) and

TUFAN (29 kg/t) lithologies, respectively, for sectors of the Encuentro deposit where

carbonate is greater than 0,5%, identifying ankerite as the main carbonate mineral directly

affecting sulfuric acid consumption.

Using Machine Learning methodology, prediction models were generated from 101 ISO-pH

bottles with QEMSCAN mineralogy, successfully predicting sulfuric acid consumption for

850 QEMSCAN samples using the predictive model obtained from Stepwise Regression (SR), with a coefficient of determination ( 2 ) of 0,87 and Mean Squared Error (MSE) of 3,4

kg/t, ensuring an optimal model for prediction.

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