The inherent uncertainty in mineral resource evaluation is perceived as negative. However, similar to skilled sailors negotiating contrary winds to advance their sailboats, we can harness this uncertainty to improve our decision making. Two examples of how SRK applies geostatistical analysis of geological and grade uncertainty are drill hole spacing studies and validation of mineral resources estimates.
1. Drill hole spacing studies
Drill hole spacing studies aim to maximise the confidence on grades and tonnages while minimising drilling costs. These are two divergent objectives, as mineral resources confidence can only be increased by acquiring new costly information. To be effective, these studies must consider practical constraints such as new access road costs, topographical relief, and inaccessible areas, while prioritising areas of the deposit where increased confidence may be most beneficial. Different drilling meshes at increasingly closer spacings are designed with the aid of an optimisation algorithm that harnessing the power of uncertainty incorporates these constraints and targets. The resulting drilling meshes are used to ‘interrogate’ reference mineralisation models that reproduce the spatial variability and other geological and statistical properties informed by the currently available data. These simulated data are amalgamated to the real data to generate multiple possible scenarios that are used to assess the grade and tonnage confidence of production volumes (see Figure 1). The retained drilling plan is the one that achieves the grade and tonnage confidence target within an acceptable drilling budget.
2. Mineral resources uncertainty and validation
Mineral resource estimates provide a single, or deterministic, forecast of the
tonnage and grades above cut-off. By generating multiple simulated scenarios
that respect the informing data and their spatial properties, we can access the full range of possible outcomes of our mineral resource estimates. The metal content at various cut-offs is, therefore, expressed as ranges of possible outcomes. While mineral resources uncertainty has geological, or tonnage, and grade uncertainty components, geological uncertainty can be the primary source of uncertainty, particularly at lower cut-off grades.
Geostatistical simulation techniques are also applied by SRK to assess the amount
of internal and external dilution at different block sizes, and as a validation tool for
estimated mineral resource models. The capability of simulation techniques
to reproduce complex multivariate relationships is key when dealing with multiple metals and contaminants to produce comprehensive assessments.
Drill hole spacing and uncertainty assessment studies require huge amounts of computational effort. To reduce the computer processing time from days to hours, SRK takes advantage of parallel computing algorithms that run on powerful virtual machines in the cloud.
