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the average variogram versus discretiza-
tion level (starting with 1 × 1 × 1 and going
to 20 × 20 × 20). Plot two lines—one with
the zero values for coincident discretization
points and another for this corrected.
Question 2: Calculate the average variogram for regular
cubic block sizes from 1 through 20 m with
the zero effect correctly handled. Comment
on your choice of discretization level. Plot
and tabulate (1) the average variogram versus
block size, and (2) the block variance versus
block size.
Harris GW (1997) Measurement of blast induced rock movement in
surface mines using magnetic geophysics. Unpublished M.S. Thesis,
Department of Mining Engineering, University of Nevada Reno
Hoerger S (1992) Implementation of indicator Kriging at Newmont
Gold Company, In: Kim YC (ed) Proceedings of the 23rd interna-
tional APCOM symposium, published by the Society of Mining,
Metallurgy, and Exploration, Inc., Tucson, April 7-11, pp 205-213
Isaaks EH (2004) The kriging oxymoron: a conditionally unbiased and
accurate predictor, 2nd ed. In: Proceedings of geostatistics banff
2004. Springer, 2005, 1:363-374
Isaaks EH, Davis B (1999) The kriging oxymoron, Presented at the
1999 Society of Mining Engineers Annual Convention, Denver
Isaaks EH, Srivastava RM (1989) An introduction to applied geostatis-
tics. Oxford University Press, New York, p 561
Journel AG, Huijbregts ChJ (1978) Mining geostatistics. Academic
Press, New York
Journel AG, Kyriakidis P (2004) Evaluation of mineral reserves: a sim-
ulation approach. Oxford University Press, New York
Machuca-Mory D, Babak O, Deutsch CV (2007) Flexible change of
support model suitable for a wide range of mineralization styles,
Transactions, Society of Mining Engineering, SME
Matheron G (1976) A simple substitute for conditional expectation: the
disjunctive kriging, In: Guarascio M, David M, Huijbregts C (eds)
Advanced geostatistics in the mining industry. Reidel, Dordrecht,
pp 221-236
Pakalnis R, Poulin R, Vongpaisal S (1995) Quantifying dilution for
underground mine operations. Annual meeting of the Canadian Insti-
tute of Mining, Metallurgy and Petroleum, Halifax, May 14-18, 1995
Parker HM (1980) The volume-variance relationship: A useful tool for
mine planning. In: Geostatistics. McGraw-Hill, pp 61-91
Rivoirard J (1994) Introduction to disjunctive kriging and non-linear
geostatistics. Claredon Press, Oxford, p. 190
Rossi ME (2002) Recursos Geológicos o Reservas Mineras? In: Pro-
ceedings from the Sextas Jornadas Argentinas de Ingeniería de
Minas, San Juan, Argentina, Mayo 30-Junio 1
Rossi ME, Parker HM (1993) Estimating recoverable reserves: is it
hopeless? Presented at the Forum 'Geostatistics for the Next Cen-
tury', Montreal, June 3-5
Rossi ME, Parker HM, Roditis YS (1993) Evaluation of existing geo-
statistical models and new approaches in estimating recoverable
reserves, XXIV APCOM'93, Montreal, October 31-November 3
Roth C, Deraisme J (2000). The information effect and estimating
recoverable reserves, In: Kleingeld WJ, Krige DG (eds) Proceedings
of the sixth international geostatistics congress, Cape Town, April,
pp 776-787
Verly G (1984) Estimation of spatial point and block distributions: The
multiGaussian model. Ph.D. Dissertation, Department of Applied
Earth Sciences, Stanford University
Verly G (2000) Accounting for mining dilution and misclassification
in resource block modeling. In: Kleingeld WJ, Krige DG (eds) Pro-
ceedings of the sixth international geostatistics congress, Cape Town,
April, pp 788-797
Yang RL, Kavetsky A (1990) A three dimensional model of muckpile
formation and grade boundary movement in open pit blasting. Int J
Min Geol Eng 8:13-34 (Chapman y Hall, London)
Zhang S (1994) Rock movement due to blasting and its impact on ore
grade control in Nevada open pit gold mines. Unpublished M.S. The-
sis, Department of Mining Engineering, University of Nevada Reno
7.6.3
Part Three: Change of Shape Models
The global mean does not change with scale. The variance
changes in a predictable manner; however, the shape change
is not precisely known.
Question 1: Consider cubic block sizes of 5, 10, and 20 m.
Calculate the scaled distributions using the
(1) afine, (2) indirect lognormal, and (3) dis-
crete Gaussian models. Plot the original Cu
histogram and all of the scaled histograms.
Comment on the results.
Question 2: Attempt to quantify the importance of the
shape change by plotting grade tonnage
curves at the 10 m scale. Discuss the differ-
ent models and explain where you require
such a model.
References
Abramovitz M, Stegun I (1964) Handbook of mathematical functions.
Dover Publication, New York, p 1046 (9th print)
Armstrong M, Matheron G (1986) Disjunctive kriging revisited (Parts I
and II). Math Geol 18(8):711-742
Badenhorst C, Rossi M, (2012) Measuring the impact of the change
of support and information effect at Olympic Dam. In: Proceedings
of the IX international geostatistics congress, Oslo, June, Springer,
pp 345-357
David M (1977) Geostatistical ore reserve estimation. Elsevier,
Amsterdam
GeoSystems International Inc. (1999) Conditional simulation study for
the michilla mine. Unpublished Internal Report, Minera Michilla S.A.
Guardiano FB, Parker HM, Isaaks EH (1995) Prediction of recover-
able reserves using conditional simulation: a case study for the fort
knox gold project, Alaska. Unpublished Technical Report, Mineral
Resource Development, Inc.
 
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