Abstract
In this study, drilled core values from the Magnesite Incorporated Company—its original Turkish name being Manyezit Anonim Sirketi (MAS)—Beylikova Magnesite Open-Pit Mine in Eskisehir-Turkey provided multivariate ore grade and reserve estimates that were used to integrate geostatistical estimation methods with Geographic Information Systems (GIS) technology. GIS technology is known for with its visual and spatial query capabilities in three-dimensional (3D) environments. Using the company’s topographical maps, a digital terrain model of the mine area of interest was generated in a GIS environment. Bore hole locations, drilled core values and cutting depths were also input to the sophisticated spatial geodatabase. Ore impurity grade values were analyzed according to their lognormal distributions, then evaluated by applying their corresponding variogram and cross-variogram models — models used in ordinary cokriging. To estimate ore reserve and grade, ordinary cokriging techniques were used: a twovariable model with two different variable combinations and a three-variable model. Spatial queries were applied to estimation results in a 3D GIS platform in order to determine the location, shape, and quantity of the ore body. Subsequently, the Mean Standardized Square Error (MSSE) statistical procedure was applied to the estimation results to assess and compare their accuracy. Based on these assessments, it was determined that ordinary cokriging with three variables was the most appropriate and accurate approach for estimating ore grade distribution and reserve in Beylikova Open-Pit Mine.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Journel, A.G. and Huijbregts, C.J., Mining Geostatistics, London: Academic Press, 1978.
Armstrong, M., Basic Linear Geostatistics, Heidelberg: Springer, 1998.
Tercan, A.E. and Sarac, C., Maden Yataklarinin Degerlendirilmesinde Jeoistatistiksel Yöntemler (Geostatistical Methods in Evaluation of Ore Deposits), Turkish Chamber of Geological Engineers Publications, Ankara, 1998.
Isaaks, E.H. and Srivastava, R.M., An Introduction to Applied Geostatistics, New York: Oxford University Press, 1989.
Cressie, N., The Origins of Kriging, Mathematical Geology, 1990, vol. 22.
Tobler, W.R., A Computer Movie Simulating Urban Growth in the Detroit Region, Economic Geography, 1970, vol. 46.
Aronoff, S., Geographic Information Systems: A Management Perspective, Ottawa: WDL Publications, 1989.
Smith, D.R. and Paradis, A.R., Three-Dimensional GIS for the Earth Sciences, Three Dimensional Applications in Geographical Information Systems, J. Raper (Ed.), London: Taylor and Francis, 1989.
Uygucgil, H., Çok Degiskenli Maden Yataklarinda Reserv Tenör Tahmininde Jeoistatistik ve Cografi Bilgi Sistemleri Tekniklerinin Kullanimi (Geostatistics and Geographic Information Systems Usage of Reserve and Grade Estimation in Multivariate Mineral Deposits), PhD Thesis, Eskisehir Osmangazi University, Eskisehir, Turkey, 2007.
Yamamato, J.K., On Unbiased Back-Transform of Lognormal Kriging Estimates, Computational Geosciences, 2007, vol. 11.
Chiles, J.P. and Delfiner, P., Geostatistics: Modeling Spatial Uncertainty, New York: Wiley Series in Probability and Statistics, 1999.
Wackernagel, H., Multivariate Geostatistics, 3rd Completely Revised Edition, Heidelberg: Springer, 2003.
Author information
Authors and Affiliations
Corresponding author
Additional information
The article is published in the original.
Rights and permissions
About this article
Cite this article
Uygucgil, H., Konuk, A. Reserve estimation in multivariate mineral deposits using geostatistics and GIS. J Min Sci 51, 993–1000 (2015). https://doi.org/10.1134/S1062739115050186
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S1062739115050186