Let’s get physical

Our Determined Explorer explains the discipline of geology requires a hands-on approach with little time for daydreaming.

As a student, the distinction between geology as a “physical” science rather than a “theoretical” one like physics was pretty stark. 

Sure, we had some geostatistical tools and laboratory methods like radiometric dating. Still, the emphasis was on geologists mapping the field and collecting samples that could be analysed chemically or under the microscope. 

Image processing was embryonic and required supercomputing power – something generally only available to the oil and gas industry.

Over time, that distinction has got noticeably less clear. 

The massive increase in computing power over the past few decades has meant that our ability to model data, particularly for essential tasks like resource estimation, has become increasingly sophisticated and within the routine job description of non-expert users. 

A mine I once worked at could boast an incredible annual reconciliation between the resource estimate and mined gold of about ±3%.

Considering the geological and measurement variables involved was a testament to the data collection process from drill hole to mining to mill. 

Yet another site underwent a step-change in their geological understanding with the advent of cheap, multi-element assays that allowed the geologists to model their complicated deposits in a previously impossible way.

There has also been an explosion in the amount and quality of geological, geophysical and geochemical data available to explorers. Enlightened government agencies have progressively invested in pre-competitive surveys and digitisation of all the information coming from industry. 

The concept of “data mining” from internal databases or public sources is a powerful way of evaluating missed opportunities and generating new exploration targets.

The next phase will be artificial intelligence, or AI, something I have been both enthusiastic and sceptical about in roughly equal measure. 

AI potentially has the power to mesh together different data layers in a way that we used to think was the preserve of only the expert geologist with years of experience with ore deposits and the ability to recognise patterns in the geological data.

AI systems are progressing and are starting to be something exploration companies will consider as part of their business strategies to obtain new insights or competitive advantage. 

However, I think they are mostly still frustratingly restricted to the 2D map space and understandably biased by the considerable variation in data density between known mineralised districts and greenfield or covered terrains where good geological data might be very sparse.

I am not worried about people being replaced in the project generation role. 

At best, AI will become a useful but not infallible tool of the trade. 

For the moment, we still need exploration geologists to get into the field and collect the rocks or do the drilling programs. That’s what we want to be doing anyway.

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