Dear Raimon,
A few steps back may be necessary, mining geostatistics uses random
functions to model the grade of the deposit, not of the samples. The
samples, among other sources of information, are there to help you in that
modeling process. The spatial continuity of the orebody itself is not a
function of the sampling, it is derived from a series of complex natural
phenomena. Under sampling the deposit does not make the "real" underlying
continuity disappear. In light of that, if your data fail to show any
kind of continuity, you should ask yourself: is it because the grades of
the deposit are truly "random", or is it because the sampling failed to
capture that continuity for a variety of reasons.
If you decide to go with the assumption of spatial independence, you then
decide that grades are uncorrelated in space. This may not be a safe
decision, and may be very consequential for the development of your
operation. By assuming a pure nugget effect, you will be expecting
constant cash flow from your operation, (every block has the same
expectation, all would be above the cutoff) and will be designing a pretty
simple mining schedule (there is no rich or barren zone). But then, if
your orebody had a spatial continuity, you will have varying cashflow and
very un-optimal mining design, that may well end up transforming a
profitable operation into the red. I do not say that such scenario does
not exist, I just put it in context.
The assumption of spatial independence is pretty consequential and should
not be made too easily. Energy should be invested on understanding why,
from a geological and metallogenical perspective, it is spatially
uncorrelated ( e.g. folding, faulting, etc... ). Also recall that
variograms only capture continuity along a line, the continuity of
curvilinear features are not easily modeled (unfolding may be helpful
here). I would anyway suggest to perform a sensitivity analysis on the
spatial correlation and see how the economics hold based on your chosen
mining design.
Regards,
Alex Boucher
At 10:30 AM 7/22/2006, you wrote:
Dear list,
this situation posed by Mr.Merks, in which spatial dependence is not
strong enough as to be useful for geostatiscs, might be rather common. I'd
like to ask to the list, what kind of estimation of reserves should be
done in this case? In the absence of spatial dependence, classical
statistics should apply: therefore, shall we estimate the mean value of
ore content in the "deposit" by the arithmetic mean of the samples? And
attach an error to it, in the fashion of the standard error of the mean
(something like the variance of the sample divided by number of data
used)? Or did I grossly misunderstand something in the discussion, with so
much bogus-hocus-pocus and 5-line sentences?
thanks for the patience
Raimon Tolosana
En/na JW ha escrit:
Hello Readers,
More talk and not test. I want to know what the KWBP methodology does
with the Bre-X data. Is that too much to ask?
Kind regards,
Jan W Merks
+
+ To post a message to the list, send it to [email protected]
+ To unsubscribe, send email to majordomo@ jrc.it with no subject and
"unsubscribe ai-geostats" in the message body. DO NOT SEND
Subscribe/Unsubscribe requests to the list
+ As a general service to list users, please remember to post a summary of
any useful responses to your questions.
+ Support to the forum can be found at http://www.ai-geostats.org/
+
+ To post a message to the list, send it to [email protected]
+ To unsubscribe, send email to majordomo@ jrc.it with no subject and "unsubscribe
ai-geostats" in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the
list
+ As a general service to list users, please remember to post a summary of any
useful responses to your questions.
+ Support to the forum can be found at http://www.ai-geostats.org/
