Scholarly record
APPLYING THE BOTH GEOSTATISTICAL ESTIMATION AND THE SEQUENTIAL GAUSSIAN SIMULATION WITHIN THE CHOGHART FE DEPOSIT
Abstract
To carry out the geostatistical studies, a spherical model was fitted over an empirical variogram. Plotting the empirical variogram in different directions, and it showed that there are neither geometric nor regional anisotropy. For simulating via Sequential Gaussian Simulation (SGS) method, data were transferred to standard normal and then simulated 100 times (in this way 100 realizations were created). All of the realizations were honor to histogram and the variogram, so all realizations are valid. E\_Type and probability maps are drawn in 12.5 meters intervals and gradetonnage curves were drowning for each realization. E\_ Type maps evaluate average 108 million tones for the whole deposit. Grade-tonnage curves were showed the range of tonnage variance that is between 97 and 116 million tones. According to ordinary kriging method, all of the exploitable blocks with the dimension of 12.5*25*25 (m3) were block-estimated and the results show that the intact reserve of the exploitable minerals was found to be 112 million tons of ore with an average iron grade of 56\%.
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References15
Asghari, O., 2003, Geostatistical Modeling and Reserve Estimation of Choghart Iron Ore Deposit through Geostatistics Method, Iran. P. 150.
Clark, I., 1999, A case Study in The Application of Geostatistics to Lognormal and Quasi-Lognorm al Problems , APCOM.
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 43-49.
Darvishzadeh, A., 2002, and Geology of Iran, Amirkabir public ation, pp901. 6th International Multidisciplinary Scientific GeoConference SGEM2006 www.sgem.org Int er nat ional Confer ence SGEM 200 6 476
Deustch, C.V. and Journel, A.G., 1992, 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.
HassaniPak, A.A. and Sharafodin, M., 2002, Analysis of exploratory data, Tehran University publishing, 987 p.
Journel, A.G. and Huijbergts, CH.J. 1978, Mining Geostatistics, 2nd printing (Revised). Academic, press, London.
Madani, H., 1995, Introduction to Geostatistics, Amirkabir University publishing,
Michel, D., 1982, Geostatistical Ore Reserve Estimation, Elsevier Scientific Publishing Co.
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.,200 5, Deposit Estimation and Risk Estimation by Sequential Gaussian Geostatistical Simulation Method, Iranian Mining Engineering Conference -2005, pp
Samani, B.A.,1988, Metallogeny of the Precambrian in Iran, Precambrian research, 39, pp 85-105.
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. 6th International Multidisciplinary Scientific GeoConference SGEM2006 www.sgem.org
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