Mining investors are often faced with lots of technical jargon around Mineral Resource statements. The thoughts in this article, written by Snowden’s Jeremy Peters, are not exhaustive, but are a simple list of things to look for when interpreting these statements.
The average investor is often not in a position to critique that Mineral Resource estimate that has appeared in an announcement. Once you get past the “significant upgrade”, “tier one asset”, “world class” and “high grade” Managing Director’s bumf, this is what I look for at first pass and should be meaningful and simple enough to follow for a non-technical person:
Competent Person (CP) Part of the JORC Code definition requires five years relevant experience (Clause 11). This does not mean five years’ post graduate experience.
A competent Mineral Resource CP will have perhaps ten years’ hanging around mines and maybe another five years in Exploration and another five years or so estimating Resources in head office or for a reputable consultancy. Ideally a postgrad qualification in geostatistics. The Resource estimated by the 10-year experience MD with an MBA or the 30-year veteran grizzled exploration geo probably won’t stand up in court.
Significant figures A dead giveaway. There’s not 1,285,282.56t @ 1.865% Cu – it’s 1.29Mt @ 1.87% Cu. JORC obliges this (Clause 25).
Estimation technique (Table 1 Section 3). There’s a good reason why Kriging or its derivatives are industry standard techniques at the moment – they’re statistically supported, until something better comes along.
The 30-year veteran grizzled exploration geo or Hiram C Cheeseburger P Geo, of Tucson AZ, is going to use nearest neighbour or inverse distance, because that’s all they know – exploration geos are not necessarily familiar with Mineral Resource estimation and big North American porphyries usually don’t require sophisticated geostatistics (although I’d dispute this, but that’s for another article). Some foreign Mineral Resource estimates use polygonal techniques, because these are mandated by the Soviet-derived systems (there’s a whole separate topic in this).
There’s nothing wrong with these techniques, provided that the data supports their use. And I rarely see such orebodies. So, when you look at Blue Sky Mines’ Maiden Mineral Resource estimate, look for commentary on variography and geostatistics. You don’t have to know what it means, but if it’s there in Table 1 and sounds plausible, then it’s probably OK (pun intended).
Classification (Clauses 20 to 24). Measured? Really? the geo must demonstrate not only geological continuity (look, pa! I can measure this in three dimensions!) but grade continuity – which means geostatistics. I get suspicious of big Measured numbers.
Reasonable Prospects (Clause 20 and Table 1 Section 3). Second to “at the time of reporting” for Ore Reserves (Clause 29), the most abused Clause in the Code. Does a modest, narrow 0.3% copper Resource at 500m depth really have reasonable prospects for eventual extraction?
Unconstrained estimates (Table 1 Section 3). If the glossy ASX release shows lots of tennis balls of mineralisation in the sections, then run or start shorting. The geo has simply pushed the default button on the software and estimated blocks around drill intercepts. There’s no geology gone into this sort of rubbish. There’s software out there that does this and it has its place in the electronic pantheon, but is dangerous in the hands of someone who doesn’t understand Mineral Resource estimation.
A competent Mineral Resource geo will carefully construct an electronic model of the shape of the mineralisation and the faults and lithology that constrains it and then carefully model the geostatistics of the samples within this shape. Takes time. Costs money. Do it.
The database Look for commentary on the database (Table 1 Section 3). If it is described as a commercial, industry standard database, then all’s probably well. If it’s described as being a bunch of spreadsheets, then start shorting.
QAQC Look for coherent commentary on Quality Assurance and Quality Control (Table 1 Section 1). A good Mineral Resource estimate will have at least 5% of samples as blanks, certified standards or duplicates and there will be warts and all analysis and commentary on just how crap the resultant data is. If the geo is relying on the laboratory for this sort of stuff, then immediately start shorting.
Downhole survey (Table 1 Section 1). If it ain’t been surveyed, it ain’t real.
Bulk density (Table 1 Section 3). Has a default bulk density been applied of, say 2.8 t/m3 for ore and 2.3 t/m3 for waste? Then something’s amiss. Look for the term “bulk density”! If “density” or “specific gravity” is used, then chances are the estimation geologist doesn’t understand what’s going on. If there’s coherent discussion on a disciplined bulk density measurement campaign to support a Kriged bulk density model, then all’s probably well with the world.
The above is not exhaustive, but I find it to be a useful first pass in assessing Mineral Resource estimates.