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QG services |
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services > conditional simulation
& risk
Project economics, especially at early stages when only resource
drilling is available, are often highly sensitive to both grade
and tonnage. There are consequently two significant risks on
resource quantification: (1) risk on tonnage ("geological
risk"); and (2) risk on grade ("geostatistical risk").
Geological risk
Much of the work done in recent times on risk, using geostatistical
simulation tools, has neglected to allow for the inherent
geometric risks. In other words there has been sole focus on
grade simulation.
The degrees of freedom inherent in a geological model may considered
to be potentially high because of wide drill spacing or potential
structural complexity. To quantify geological risk requires
close collaborative work between project geologists and geologically
trained, experienced geostatisticians. It may be possible to
generate a range of 'plausible;' geological models (all consistent
with the base data).
For example, QG have helped clients generate three plausible,
different models, with the resultant geometries labelled as
‘Pessimistic’, ‘Median’ and ‘Optimistic’
cases. These cases can be used to generate volumes within which
simulated grade distributions (from conditional simulations)
can be assessed.
Geostatistical risk
Conditional simulation
(CS) has gained in popularity in recent times, as computer speeds
have exponentially climbed. These tools are effectively 'spatial
Monte Carlo' approaches, and they offer enormous power in several
areas of application:
- Risk analysis (generate many images of the mineralisation
and evaluate risk)
- Confidence Intervals (an extension of the idea of risk
analysis)
- Recoverable Resource estimation: especially in the bivariate
case (gold-copper, etc.) where the 'joint distribution'
must be estimated
- Bench-height and other selectivity studies
- Multivariate recoverable resource estimation (by conditional
cosimulation)
- Evaluation of drill-spacing ('estimation variance study')
- Change of support
- Grade control (by economic optimisation)
It is interesting to note that, while there are many applications
of CS, many users are
not clear about these methods, and many applications are not
driven by clear goals.
Putting it all together
QG can help to put conditional simulation tools to proper use,
since they have:
Software tools
QG use Isatis software and can arrange a trial of this excellent
geostatistical package for you.
Click here
for more information on Isatis.
Other sources of simulation software include the GSLIB
system. |
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Scott Jackson (left), Scott Dunham (centre), and John Vann (right) are the Directors of Quantitative Group
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