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[ai-geostats] Re: More on geo-stats

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  • Isobel Clark
    Jim (cc Fran!) Thanks for the long email. I think grandmother-hood must be scrambling my brains because I am not following some of your logic. Or maybe it is
    Message 1 of 1 , Feb 13, 2006
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      Jim (cc Fran!)
       
      Thanks for the long email. I think grandmother-hood must be scrambling my brains because I am not following some of your logic. Or maybe it is the after-effects of trying to thump sense into the heads of those shareholders ;-)
       
      It is most probable that Jan Merks got involved in this field in the first place because someone tried to horn in on his sampling theory expertise. He has written some awesome stuff on the problems of the sampling/assay process. I have had the privilege of being peripherally involved with that end of the business through Norman Lotter, currently at Sudbury and finishing his PhD on just this probability plot/sampling bias/mineralogical interpretation stuff. See joint paper at 2000 SME (http://uk.geocities.com/drisobelclark/resume follow publications link).
       
      However, I am a mining engineer. It is my job to take the sample results, no matter how much they suck and give the engineers some indication of where and when they might mine in order to obtain payable ore. I have been doing this job since way before I learned any geostatistics. In fact, my first ever job was to produce 'correction factors' to allow a hydrothermal tin mine to predict their mining grades from their development grades. I only discovered later that the common sense methods I applied were identical to those produced by Sichel and Krige in the early 1950s in South African gold mines (also nothing to do with geostatistics). This job was extremely straight forward as the only issue was how to predict the average grade of 3,000 tonnes of rock from around 50 kilos of sample.
       
      The interesting parts of that work were the things I discovered in the numbers which the geologists forgot to tell me about. Like: three phases of mineralisation; a bloody great fault through the middle of the vein; grades falling off at depth and rising at shallows. Read my 1974 IMM paper to see where I got my basic training -- and all pre-geostats.
       
      YES you should be doing geology and mineralogy first -- or hydrology, climate analysis, entymology or whatever your equivalent is. YES, statistical or geostatistical or any numerical analysis should enhance and support this analysis. In my experience, the second most common phrase I encounter is "oh! we didn't think that was important!". In my courses I use examples of where geostatisticans have mucked(?) up a resource evaluation because they ignored the geology. I also use examples where the geologists did the same because their interpretation of the geology was inappropriate. I also use examples where I knew intuitively something was wrong but couldn't for the life of me explain why until I managed to browbeat the client into given me the information they "didn't think was important". You don't find this stuff in the textbooks.
       
      Geostatistical methods are not a scam. They are just another way of looking at your sample data and trying to draw inferences from the data. They may be inappropriate for your application. They may be used by unscrupulous individuals. They may be used by resource evaluators who are gullible enough to trust the data given to them by the client. The scam of BreX wasn't perpetrated by the geologists, the assay labs or the geostatistics. The scam of BreX was perpetrated by the bastard who put handfuls of alluvial gold in the samples on site and robbed the shareholders blind. It isn't the resource evaluators who are now living in the Cayman Islands on the proceeds of shares which went to $250 and crashed overnight.
      Geostatistical methods have their strengths and weaknesses, as do all interpolation methods based on real data. I don't see anyone writing emails about the "Bicubic splines scam?" or the "triangulation mapping method scam?" or the "join up the top and bottom of the ore zone with a fuzzy pencil scam?" or the "save the wavelets scam?".
       
      If you are uncertain of which approach you should apply, use your common sense. Ask these questions of any technique:
       
      -> what are the basic assumptions?
      -> are the algorithms and/or software technically adequate?
      -> do the results make sense?
       
      Apart from anything else, the above process will make it easier for you to explain to other people (like your defence committee) why you chose (or didn't choose) those methods.
       
      Think for yourself and don't dismiss a technique because someone has made it his/her life's work to attack it -- especially if they present no alternative way to do the job.
       
      Isobel
       
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