Isobel

While your comment "a block is not even estimated unless it is pretty
adequately known" is valid, practised on many sites, and useful eg used to
justify more drilling, it is not always practical. Some software such as
Whittle cannot cope with unestimated blocks, so we estimate a grade for them
(eg by using larger searches), but they are classified as lower confidence.
If not estimated, there is still a need to have some statement of this
resource.

Related to this, is what I term the 'salt& pepper' problem. If blocks are
assigned a classification based on individual parameters, it can result in
a mosaic of Inferred, Indicated and Measured blocks. While this may be
absolutely, mathematically, correct, it too is impractical (for us anyway).
Hence our strategy of making a judgement based on many parameters, and
applying the classification to a 'large' contiguous area.

I am very pleased to see this topic raised as some guidelines are long
overdue.

Jim
ph  08 9327 2263
fax 08 9327 2294


-----Original Message-----
From: Isobel Clark [mailto:[EMAIL PROTECTED]]
Sent: Wednesday, 27, February 2002 12:32
To: Farquhar, James (HI)
Cc: [EMAIL PROTECTED]; Bill Shaw
Subject: RE: AI-GEOSTATS: What are appropriate measures of reliability
for Mineral Resource and Ore Reserve estimates?


Jim

I totally agree with your principles. The main
difference, in operation not philosophy, is that most
(good?) practitioners include 'all of the above'
before getting to a classification stage.

For example, the selection of which blocks to estimate
in the first place is done on the basis of all
existing geological knowledge plus assumptions about
continuity etc. So, a block is not even estimated
unless it is pretty adequately known anyway. The use
of a single criterion to distinguish the line between
measured and indicated resources is almost a formality
and probably depends more on the target audience than
any other motivation.

Isobel




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