A robust geological dataset and a well understood and constructed geological model are the foundation of a reliable mineral resource estimate that will guide financial and operational decisions through a project’s value chain.
Geological models should include all lithological, structural, alteration and weathering aspects that control the mineralisation in a deposit, but also aspects that could impact geotechnical stability, geometallurgical recovery and waste characterisation.
There are many projects that SRK has been asked to review where the client’s
geology team usually has a reasonable understanding of the local geology and
mineralisation controls, but time and budget constraints have resulted in geological models that only consist of simple grade shells interpreted above a cutoff with limited geological context. Without this context, the shape, size and orientation of the interpreted mineralisation may be incorrect, which then affects the mineral resource estimate and any subsequent Ore Reserve estimation. Realistically, these models should be treated as low confidence or high uncertainty models and classified accordingly.
Advances in geological modeling, notably implicit modeling, have allowed geoscientists to visualise and model geology in 3D rather than using the classical 2D sectional approach, as well as rapidly incorporate more extensive datasets into a model. While implicit modelling is a vast improvement, practitioners should still take time to first understand all the geological aspects of their deposit before modelling. It’s very easy and quick to produce ‘a model’ using implicit modelling software, but it takes time and patience to produce robust geological models that reflect all the available geological information.
Geological models are an important asset for exploration and mining companies
that should not be overlooked, or their preparation rushed. Investing time and effort in geological modelling early on reduces the geological uncertainty for a project and can lead to savings for infill and grade control drilling and reduce the time to update future geological models as more data become available.
