Current low prices for many metals mean that deposits have to be
mined at high cut-offs (relative to their mean grade), which
means that only a small percentage of mining blocks are above
cut-off. Worse, at such high cut-offs, the blocks above cut-off are
usually not grouped into convenient clumps for mining; they tend
to be split into small isolated patches that are difficult to reach
and hence expensive to extract. Companies wishing to acquire
mineral properties have to be able to work out quickly what
percentage of blocks are above cut-off and what can effectively
be mined given the mining method envisaged. Moreover they
need this information within a relatively short-time. The work
presented here relates to typical South African gold mines (ie
tabular orebodies) but the long-term objective is to develop tools
for quantifying the impact of reserve breakup at high cut-offs for
a wide range of underground mines including those that are not
tabular. The mining method and the sampling procedure determine
whether ore blocks can effectively be located and extracted
economically. This project studied the impact of these two
factors on the recoverable reserves for Witwatersrand gold mines.
In order to be repeatable, the tests were done on numerical
models of the deposit obtained by geostatistical simulations. To
ensure realism, the orebody model and the mining scenarios were
based on a specific mine. The recoverable reserves (ore tonnage above cut-off, the
corresponding metal quantity and the average grade) were
calculated for a wide range of cut-offs for four mining scenarios,
as well as for the base case of free selection: Scenario 1: Blocks are taken if their true grade is above
cut-off and if they are accessible from a raiseline (no
information effect, no marginal blocks). Scenario 2: In addition to the accessible pay blocks, adjoining
marginal blocks are taken (no information effect, + marginal
blocks). Scenario 3: Blocks are taken if their estimated grade is above
cut-off and if they are accessible from a raiseline. Here the
estimator is the average of the face samples (information
effect, no marginal blocks): Scenario 4: Accessible pay blocks are taken if their estimated
grade is above cut-off. Adjoining marginal blocksare also
taken (information effect, + marginal blocks). Free selection: All blocks whose true grade is above cut-off
are taken irrespective of their accessibility. The results can be presented in different ways, for example by
plotting ore tonnage above cut-off versus cut-off grade, or metal
tonnage above cut-off versus cut-off grade etc. As expected, this
shows the hierarchy between the five scenarios from the free
selection base case to scenario No 2 (true accumulations, pay +