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Re: AI-GEOSTATS: Block size - estimation variance - resource category.

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  • Isobel Clark
    Digby, at last a real question! ... Depends on how you use it, whether your estimates and errors have Normal distributions, how many samples you can find
    Message 1 of 2 , Mar 16, 2001
      Digby, at last a real question!

      > Is use of estimation variance for classification of
      > resource confidence e.g the AusIMM's resource
      > categories of Measured, Indicated and Inferred
      > common and is this good practice.
      Depends on how you use it, whether your estimates and
      errors have Normal distributions, how many samples you
      can find within your search radius plus a whole can of
      other worms.

      There are as many different ways of using the kriging
      variance as there are major mining houses and
      consultancy groups. If you want to classify on a
      block-by-block basis, the following seems to work
      pretty well. As professional engineers with 30 years
      of experience specialising in resource and reserve
      estimation, we have found this acceptable to most
      Western Banks:

      Measured resource: kriging variance less than ordinary
      statistical sample variance (or total sill if you have

      Indicated resource: not measured but within the range
      of influence of at least 4 samples (not sure how you
      would apply that if you have no sill!)

      Inferred resource: anything that a competent geologist
      can justify on the grounds of physical continuity.

      In plain words: measured is something that you can
      have some confidence in; indicated is within range but
      the local average is a better estimator than the
      kriging; inferred is a can of worms.

      > Also how is this
      > effected by block size in that should a reasonable
      > block size be chosen e.g. 1/4 drillhole spacing.
      The 'sample variance' referred to in the measured
      category should be reduced by the within block
      variance to be meaningful. This means the bigger the
      block the better the estimate must be to be measured.

      Drillhole spacing is not the issue in classification
      or confidence measurements -- the range of influence
      or distance scaling parameters are.

      Hope this helps
      Isobel Clark

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