Short-term Models - Mineral Resource Estimation - page 233

Question 4: Simulate 100 realizations of the grade. Plot the
average grade and four realizations to verify
that the simulated realizations are reasonable.
The average grade model should look very
close to the kriged model created previously.
Question 5: Calculate the expected proit assuming a cost/
price/recovery structure that will give about
50 % ore in the model area.
Question 6: Establish initial polygon limits for an ore/
waste interface. Optimize the dig limits for
different digability settings.

Douglas IH, Rossi ME, Parker HM (1994) Introducing economics in
grade control: the breakeven indicator method. Preprint No 94-223,
Albuquerque, February 14-17
Goovaerts P (1997) Geostatistics for natural resources evaluation.
Oxford University Press, New York, p 483
Isaaks EH (1990) The application of Monte Carlo methods to the anal-
ysis of spatially correlated data. Ph.D. Thesis, Stanford University,
p 213
Journel AG (1988) Fundamentals of geostatistics in five lessons. Stan-
ford Center for Reservoir Forecasting, Stanford
Matthey J (2001) Special report: Platinum 2001
Neufeld CT, Norrena KP, Deutsch CV (2005) Guide to geostatistical
grade control and dig limit determination. Guidebook series, vol 1.
Centre for Computational Geostatistics, Edmonton
Parker HM (1991) Statistical treatment of outlier data in epithermal
gold deposit reserve estimation. Math Geol 23:125-199
Rossi ME, Parker HM (1993) Estimating recoverable reserves: is it
hopeless? In: Forum 'Geostatistics for the next century', Montreal,
3-5 June
Srivastava RM (1987) Minimum variance or maximum profitability.
CIMM 80(901):63-68

References

Aguilar CA, Rossi ME (1996) Método para Maximizar Ganancias en
San Cristóbal, Minería Chilena, Santiago, Chile, Ed. Antártica, No.
175, pp 63-69, January