The Parable of the Discovery Channel—A Geological Modelling Tale
AusIMM’s Parker Challenge (running from 14 December 2022 to 24 March 2023) was set up to honour the memory of the well-respected American geostatistician, Harry Parker (Searston et al. 2020). I think it’s great the AusIMM organisers came up with this challenge and I believe it’s certainly long overdue.
The Parker Challenge is designed to document the variability in resource estimations that result when multiple resource geology specialists analyse an identical dataset. In a way it’s a strange challenge, particularly to quantitative scientists who work outside the mining industry, and I’ll be fascinated to see the results, if they are made public. I was going to participate, in collaboration with my A-Team member Stuart Masters but we’re both too busy at the moment.
I have a very specific way of approaching this problem of geological modelling for the purposes resource estimation (which applies to exploration as well). I summarised this approach in a 15-minute talk I gave at the 2014 AusIMM Mining Geology Conference (I apologise for the poor sound, which was recorded 8 years’ ago on my phone).
I’m certainly not a geostatistician—I’ve had no training in that field because I have no desire to estimate resources. Why? Because I don’t think geostatistics is the critical issue that needs to be looked at to lower the variability of results between practitioners. In my 2014 talk I address what I believe is the fundamental reason why so much variability exists in resource estimation results, and it has little to do with maths—it’s to do with geology.
In the talk I explain this in a form of a parable that anyone can understand. It’s a recasting of the central message of my paper that was part of AusIMM’s Mineral Resource and Ore Reserve Estimation: Guide to Good Practice (Cowan 2014). Despite that paper being nearly 10 years old, my approach to the problem hasn’t changed in the intervening years.
In this talk, you’ll learn about:
- The critical reason why I think there’s so much variability in resource estimation results
- The most effective modelling workflow that I use
- Why implicit modelling won’t decrease your modelling risk, but will increase it if you don’t use the most appropriate workflow
Harry Parker famously said:
“In general, an ounce of geology is worth a pound of geostatistics; this may be disappointing to geostatisticians with no geological background—tough.”
Although I fully agree with Harry, I made a small alteration to his quote in my 2014 talk, and I apologised to Harry who was sitting in the front row. Harry was a good sport and wasn’t bothered and he was nice enough to come up to me later to tell me he liked my talk.
I hope you like ‘The Parable of the Discovery Channel’, as much as Harry Parker did!
References
Cowan, E.J. 2014. ‘X-ray Plunge Projection’— Understanding Structural Geology from Grade Data, in Mineral Resource and Ore Reserve Estimation — The AusIMM Guide to Good Practice, second edition, Monograph 30, 207–220.
Searston S., Smith L.B., Verly G. 2020. Farewell to Harry M. Parker (1946–2019). Mathematical Geology, 52, 447–450.
