Scholarly record
LOWERING THE ESTIMATION VARIANCE BY LITHOLOGY AND ALTERATION SEPARATION
Abstract
In the detailed exploration and reserve estimation, with separating the alteration (as the controller of the grade) in ore reserve and estimating the reserve in each alteration, the estimation variance will decrease and the accuracy of the estimation will increase. In the other hand without any additional drilling, it is also possible to decrease the estimation variance by lowering the sill of variograms. In this method, we have categorized the data into different lithologies and different alterations such as skarn and dikes (DK1a and DK1b) and potassic, phyllic, proplytic and argilic alterations. The variances and sills of all populations decreased noticeably. Due to lowering the variance and sill of variogram, the estimation variance of blocks decreased significantly. The reduced variance is 20 percent of total variance which could be achieved by additional drilling (at least 16000 m).
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References13
O. Asghari, A. Hezarkhani, 2006, Sequential Gaussian Simulation (SGS) of the Choghart iron deposit, Iran, MPES conference, Torino, Italy, p.p. 369-375.
O. Asghari & A. Hezarkhani, 2006, Geostatistical modeling and reserve estimation of Sungun Porphyry Copper ore deposit through ordinary kriging method SGEM conference, Sofia, Bulgaria. Vol. II, p.p. 451-462.
O. Asghari & A. Hezarkhani, 2006, Choghart ore deposit estimation and risk estimation by Sequential Gaussian Simulation (SGS) method. Amirkabir Scientific journal, Vol. 64, p.p. 51-59.
O. Asghari & A. Hezarkhani, 2006, Geostatistical modeling and reserve estimation of Sungun porphyry copper deposit. MPES conference, Torino, Italy, p.p. 363-368.
Costa J.F. and Zingano J.A. and Koppe, J.C. ,(2000), “Simulation -An Approach to Risk Analysis in Coal Mining”, Exploration and Mining Geology Vol .9 No.1 pp
49. Mining and Geology
Deustch, C.V. and Journel, A.G., 1998, GSLIB: Geostastical Software Library and user's guide: Oxford Univ. Press, New York, 340 p.
Dimitrakopoulos, R. And Fonseca, M.B., (2003), Assessing Risk in Grade- Tonnage Curves in a Complex Copper Deposit, Northern Brazil, Based on an Efficient Joint Simulation of Multiple Correlated Variables, APCOM, pp 373-382.
Hassani Pak, A.A. and Sharafodin, M., 2002, Analysis of exploratory data, Tehran University publishing, 987 p.
Moor, F. and Modabberi S., 2003, Origin of Choghart iron oxide deposit, Bafq mining district, Central Iran: new isotopic and geochemical evidence, Journal of science, Islamic Republic of Iran 14(3), pp 259-269.
Saeed, S.,2005, Deposit Estimation and Risk Estimation by Sequential Gaussian Geostatistical Simulation Method, Iranian Mining Engineering Conference-2005, pp
Vann, J., Bertoli, O. and Jackson, S., (2002), Geostatistical Simulation for Quantifying Risk, Geostatistical Association of Australian symposium.
Webster, R. and Oliver, M., 2000, Geostatistic for Environmental Scientists, John Wiley & sons, New York, 270p.
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