9
during periods of low model reconciliation or mining inter-
ruptions providing option value at the end of the mine life
when the stockpile can be processed if prices are high or left
on the ground if prices are low.
Dynamic Cutoff Grades
If the operation wants every ton above a breakeven cutoff to
be milled in the same period mined, the mining rate must be
throttled back dramatically until starting to mine the outer
laybacks (Figure 11a). Each ton processed at breakeven
cutoff grade provides negligible current year profits while
consuming limited mill capacity and deferring profits from
future years to reduce NPV by 10.6%. Compared to the
base case’s dynamic cutoff grades, which change with each
time period, the fixed breakeven cutoff case shows signifi-
cantly lower mill grades (Figure 11b) and corresponding
sacrificed cash flow and NPV (Figure 11c) in each of the
first nine years. As a side note, in this breakeven cutoff case
where mining is not a bottleneck, increasing mining capac-
ity would have little to no continuous improvement value.
EVALUATING GEOSTATISTICS
IMPROVEMENT OPPORTUNITIES
Mining selectivity can have a significant impact on the grade
and tonnage of ore above cutoff and consequently on the
value of an operation. The base plan model reflects a proba-
bilistic estimate of mine selectivity, with each of the nine
simulations honoring all drilling information and identi-
fied spatial continuity trends to provide multiple equally
probable views of the distribution of grades throughout the
deposit. For grade tonnage reporting, each block of each
simulation is tested against the increment histogram bin
limits and the total accumulated tonnage in each bin is
divided by the number of simulations for purposes of this
paper, this model is called the IK (for indicator kriging)
model. To investigate the impact of lower selectivity, two
alternative models were created.
E-Type Estimate (Ok)
First, each block was assigned the grade of the average of
the nine simulations this e-type (e for expected value)
model is called the OK (for ordinary kriging) model.
Figure 12 illustrates the averaging process for a sample
bench and the resulting smoothing of grades.
Diluted Simulation (IKD)
Second, a diluted model was created for each simulation by
computing a weighted average of the block grade and the
grades of the four neighboring blocks that share a common
edge this diluted model is called IKD and uses the same
grade tonnage reporting process as the IK model. Figure 13
illustrates the process for a sample bench of a sample simu-
lation. The assigned weighting (68% for the central block
and 32% split between the four adjacent blocks) was cho-
sen to achieve an arbitrary 5% reduction in the grade distri-
bution’s standard deviation conceptually, the 32% weight
would correspond to an additional 2.35 meters of mixing
around the 80 m perimeter of a 20 m x 20 m block.
11a) Yearly tons mined comparison
11b) Yearly mill grade comparison
11c) Discounted cash flow comparison
Figure 11. Fixed cutoff comparison highlights: solid
lines=fixed breakeven cutoff grade dashed lines=base case
with dynamic cutoff grade and stockpiling
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