If truth be told I didn’t really miss the 2000 Millennium celebrations of the Canadian Institute of Mining, Metallurgy, and Petroleum (CIM) and the Prospectors & Developers Association of Canada (PDAC). For the masters of ceremonies didn’t pine for my paper on Applied Statistics and the Bre-X fraud. Most CIM and PDAC members play the kriging game and talk about confidence without limits. Most scientists on this planet work with real statistics and real confidence limits. I work mostly with 95% confidence intervals (95% CI) and 95% confidence ranges (95% CR) for metal contents and grades of mined ores, mineral concentrates, mineral reserves and mineral resources. The world’s mining industry blathers about confidence without limits for mineral reserves and mineral resources. Yet it did accept confidence intervals and ranges limits for mined ores and mineral concentrates. So what’s all that talk about confidence? It should be about risk! The risks between trading partners seem to matter a lot more than the risks mining investors run. That’s the real story behind Bre-X!

What keeps the world’s mining industry going is mineral exploration. To find and define mineral reserves and mineral resources is not just the name of the game but is itself a bit of a game. The trouble is statistically challenged qualified persons infer ore between holes before verifying spatial dependence either within holes or between holes. To infer ore between holes worked miracles when Bre-X drilled holes at a spacing of 50 m up to 200 m. When this geostatistical practice was applied at Bre-X’s Busang property, it didn’t spook the Ontario Securities Commission (OSC) until a few barren holes were twinned. But it really fooled Bre-X’s stakeholders, didn’t it?

I am happy to submit a guest blog for Joe Dos Santos. This is to lighten things up from the technical stuff engineers like so well and frankly…I just don’t understand. Until now!

Spending most of my college life in public relations and marketing classes, engineers and engineering seemed a world away…even though I could walk to the engineering building on my campus in under five minutes. That’s actually strolling. Still, the dynamics of what they did, the math, the figures, the equations! It was way over my head. After all, it was all I could do to get through my remedial math courses much less pursue a higher level of math. Now don’t think I didn’t feel the pressure. My father, a Cornell graduate said he learned to love the thing that really challenged him. Yep….math! And of course, we can’t forget my brother the MIT graduate. Of course I felt the pressure. After all…they are both…you guessed it, Engineers!!!

CIM eNews of March 2008 announced a seminar on Applied risk assessment for ore reserves and mining planning: Conditional simulation for the mining industry. This 2008 CIM, SME, AusIMM, and McGill Professional Development Seminar Series is based on a spurious variant of applied statistics. Conditional simulation with pseudo kriging variances makes no sense in applied statistics. What would make sense is to get rid of surreal geostatistics at each and every institution of higher learning on the face of this planet. I’m working hard to make that happen! The more so because I’ve heard some “geometallurgy” babble that may well set the stage for McGill’s geosciences to gobble up mineral process engineering.

Dr F P Agterberg, President, International Association for Mathematical Geology, has a few problems. The least of his problems is to change IAMG’s current name to International Association for Mathematical Geosciences. To bring the distance-weighted average and its central limit theorem back together again is just as pressing a problem as it is to count the degrees of freedom for a set and for the ordered set. So, I’ll try to put in a chronological context the cases of the missing variances and of the unwelcome degrees of freedom.

Agterberg talked about Autocorrelation Functions in Geology at the 1970 geostatistics colloquium in the USA. He had found some kind of “geologic prediction problem”, and drew a picture of it in Figure 1 of his paper. The same figure was reborn as “a typical kriging problem” in Figure 64 of his 1974 Geomathematics. As such, the same figure is published in the 1970 Colloquium Proceedings and in his 1974 Geomathematics. Why was a “geologic prediction problem” reborn as a “typical kriging problem”? I’ve studied the tortuous nomenclature of geostatistics and tried to figure out who lost what and when.

When my son and I were working on Precision Estimates for Ore Reserves in the late 1980s, we had copies of David’s 1977 Geostatistical Ore Reserve Estimation and Clark’s 1979 Practical Geostatistics. We wanted to know how geostatisticians derive confidence limits for metal contents of ore reserves. The problem is they don’t! By contrast, ISO/TC183 did approve in 1993 a homologue of the same method to derive confidence limits for copper, lead and zinc contents of concentrate shipments.

Dr Frederik P Agterberg, President, International Association for Mathematical Geology, called Professor Dr Georges Matheron (1930-2000) the Founder of Spatial Statistics. He ranked him on a par with Sir Ronald A Fisher (1890-1962) and Professor Dr J W Tukey (1915-2000). Agterberg was wrong! Matheron was a self-made wizard of odd statistics. Here’s why!

Most of my life I have worked with William Volk’s Applied Statistics for Engineers. At present I work with his 1980 Reprint Edition. I lost the 1969 Second Edition while I was preaching sound sampling practices and applied statistics around the world. I’m hanging on to my tattered 1958 Original Edition. Volk’s name translates into the Dutch word for “nation” or “people”. That led me to believe William Volk and Jan Visman may share the same roots. Volk holds a 1959 masters degree in mathematical statistics from Rutgers University and an undergraduate degree in chemical engineering from New York University. So he must have written much of his Original Edition before graduating from Rutgers. I took a real liking to Chapter 7 Analysis of Variance. What I like most of all is Section 7.1.4 Variance of a general function. For it was in this section that Volk proved that each function ought to have its own variance.

Geoscientists do not count degrees of freedom quite as well as do statisticians. Way too many have been taught some sort of new of science where spatial dependence need not be verified but may be assumed. Many geoscientists do not grasp why the properties of variances and the concept of degrees of freedom cannot be ignored with impunity. All the same, the world’s mining industry accepted this substitute for applied statistics because it does work miracles with a few boreholes drilled some distance apart.

Dear Bulkaholics,
I am a new member of your community. My business is Coal to Liquids plants. Is there anyone with experience in feeder technology for coal gasifiers? The problem is to feed dried coal (especially in the case of lignite) into the pressurized (Siemens or Shell) gasifiers. The train: Coal Crushing, Coal Pulverizing, Coal Drying, Coal Bunkering, Coal Feeding has to be optimized and a save handling is required (preventing coal dust explosion). I am interested to hear from someone.