Geology is the cornerstone of any accurate resource model.   In my opinion, geology contributes 90% of the accuracy of a resource estimate.  The time spent on the geology rarely reflects this importance.

However, the better the geological model, the simpler the resource estimation (and the simpler the mathematics required to generate a representative resource model!)

What is so important about geology?

In resource estimation, we create blocks of grade based on the nearest sample data.  If the block grade is to be relevant, then the samples it is based on must be relevant.  In other words, we need to identify the populations of interest that are relevant to the block we want to estimate.  This means we need to understand the boundaries of the populations to constrain the relevant samples.  But what makes a sample relevant? And how can we know we have sub-divided the data into groups of relevant samples? Building domains is about:

·   Using our understanding of the geological controls on mineralisation to create the limits of each mineralisation population

·   Using  statistical  tools  to  validate  our  interpretation  of  the  mineralisation populations

·   Understanding  and  defining  domains  before  creating  three  dimensional envelopes of the populations

Let us look at some examples of geological interpretations and the effect on the mining.

(a) lithological model
(b) structural model

Either interpretation of the geology is plausible given the available data.  However, the lithologically interpreted model results in a pit optimisation that is shallow with a low strip ratio.  The optimum pit on the structural model extends deeper and has a higher strip ratio.  The structural model also results in a significantly higher Net Present Value (NPV). So, the geological interpretation and its role in constraining the mineralisation affects the economic expectation of a project.

Example 2

Consider the situation of a high-grade supergene zone.  If this zone is not recognised nor interpreted as a separate high-grade zone, then the high grades will be smeared either into the oxide or into the fresh material, thereby over-estimating both grade and tonnes in these zones.

(a) Constrained estimation of high grades within supergene
(b) Unconstrained high grade smeared into oxide profile

Example 3

Another situation to consider is whether mineralisation pre- or post-dates the structural events.   In the first instance, mineralisation is interpreted to occur only within the lithological layers, whilst the interpretation of mineralisation post-dating the faulting allows additional ribbons of mineralisation to be interpreted.

(a) Mineralisation pre-dates faulting

(b) Mineralisation post-dates faulting