A key consideration with the use of routinely collected geochemical data is the appropriate extrapolation of discreetly selected samples over an entire mineral deposit. At the Rochester mine in west-central Nevada, SRK used the existing deposit-wide total sulphur database to predict acid-generating waste at the mine scale.
The Rochester mine is a low sulfidation epithermal gold-silver deposit hosted in silica-rich volcanic rocks. In this deposit type, neutralizing minerals are rare and acid generation is almost entirely a function of the sulphide content of the rocks. Total sulphur data are routinely collected on site to differentiate areas of potentially acid-generating waste rock as part of the waste rock management plan. To supplement the spatial distribution of this dataset, logged sulfide data were used as a proxy for total sulphur in the absence of analytical data. These data were transformed into total sulphur values which were included in the geological model. This dataset was combined with modeled structure, lithology and grade to produce a sulphur block model, utilizing similar approaches to those used in resource estimation models (Figure 1).
The development of a sulphur block model using mineral resource estimation methodology enabled detailed scheduling of potentially acid-generating waste rock at the mine scale. This study demonstrates that utilizing available, applicable data as a site-specific analogue is beneficial for the prediction of environmental impacts across a deposit. This work has been accepted for publication in Economic Geology under the title “Sulfide Variation in the Coeur Rochester Silver Deposit: Use of Geological Block Modeling in the Prediction and Management of Mine Waste.”
