By Jack Caldwell

The Canadian Institute of Mining’s CIM Magazine follows a delightful approach to presenting high quality technical papers: it simply does not present them.

All they give you is, generally, a one-page executive summary. I say delightful, because that is about as much as most people want to read for entertainment and/or information about any technical topic. If you need to read the rest of the paper to earn your living—go to the website and, if, like most of our readers, you do not belong to the CIM, pay for the full paper.

The December 2006 issue of the CIM Magazine includes a summary of a paper Geostatistical modeling of McMurray oil sands deposits. Here are the key concepts in the paper (I quote but indulge in much editing and shortening; and even then I suspect very few will understand a word—but it is fun to see how the authors have succeeded in generating text that sounds good. Hence skip the following if you do not delight in rap-like word-play.)

“Resource estimation for oil sands has traditionally relied on polygonal and inverse distance schemes. While simple and straightforward in practice, these resource estimation techniques do not permit reliable uncertainty assessment. The following steps are described in detail relative to the use of modern geostatistical techniques for the McMurray formation:

1. Assess the most appropriate stratigraphic transformation for optimizing the correlation structure.

2. Determine representative distributions with declustering and debiasing techniques.

3. Model spatial continuity of bitumen grade, fines grade, water saturation, and other petrophysical variable.

4. Perform estimation and cross validation as checks against simulation results.

5. Perform simulation for uncertainty quantification of bitumen and fines grade.

6. Model checking of simulation results against the input data and comparison against the kriged models.”

Do not despair, if like me, you have not understood the above; some executive does, for it occupies a full page of an 86-page national magazine. For those seeking to understand geostatistics, EduMine can put you right. First there is the entirely practical course called Practical Geostatistic, Modeling and Spatial Analysis. Then there is the empirically-based course called Empirical Methods of Resource/Reserve Estimation.

And more and better is yet to come. To be posted on Edumine within the next few weeks are courses by Isobel Clark. Here is a brief description of the courses soon to be posted.

"These courses are based on 28 years of teaching to mining engineers, geologists, hydrologists, soil scientists, climatologists, plus the occasional geographer, pattern recognition expert, meteorologist, statistician, and computer scientist. Even, on one occasion, an accountant."

No executives I am afraid. If you cannot wait for her courses to appear, here are some links to geostatistics on the web:

The introduction to Isobel Clarks new course is so fascinating, I make free to reproduce the rest of it here as an example of understandable technical writing.

Readers interested in rigorous mathematical proofs are urged to stop here and turn to the more theoretically based material (a comprehensive bibliography is included). This course is not intended to turn out fully-fledged geostatisticians. It is intended for people with problems to be solved which can be assisted by a geostatistical approach.

To benefit from this course you need to be fairly comfortable with basic algebra. That is, with the notion of using symbols as shorthand for longer statements. We have worked hard to bring you consistent notation throughout the course. Where notation is out of our control, we explain carefully what each symbol stands for and try not to use that symbol for anything else.

Calculus --- differentiation and integration --- is discussed at various points in the text. The reader is not expected to do any calculus (as such) but is expected to know that the differential of x2 is 2x. The only other complication is the frequent use of simultaneous equations. We tend not to use matrix algebra in this course but will give the matrix form after explanations have been given in simple algebra. For example, linear regression is easier to understand if developed with algebra, but very simple to implement in spreadsheets if matrices are used.

If we haven't scared you off yet, be reassured by the fact that all the analyses are illustrated with real data sets in full worked examples. Data sets and software can be downloaded from Ecosse Geostatistics. There are also exercises for you to try. Answers are available for you to check your results. Most of these exercises have been collected and used in classes or examinations at Final (Senior) Year and Master's levels.

We regret that this course cannot contain the jokes, anecdotes and sheer fun that we have when we give the course in person. We do advise you, however, to keep your sense of humor and common sense at all times while taking this course.