Estimation of mineral resources using grade domains: Critical analysis and a suggested methodology

Journal of The South African Institute of Mining and Metallurgy

Volumn 105, Issue 4, 2005, Pages 247-255

  Emery, X ^a   Ortiz, J M ^a  

^a UNIVERSITY OF CHILE   (Chile)

Author keywords

Conditional bias; Geological control; Geostatistics; Grade zoning; Kriging

Indexed keywords

ANISOTROPY; COMPUTER SIMULATION; COPPER; DATA ACQUISITION; MATHEMATICAL MODELS; RANDOM PROCESSES;

CRITICAL ANALYSIS; GEOLOGICAL CONTROL; GRADE ZONING; MINERAL RESOURCE CLASSIFICATION;

MINERAL RESOURCES;

EID: 18844417129     PISSN: 0038223X     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (14)

1. DUKE, J.H. and HANNA, P.J. Geological Interpretation for Resource Modelling and Estimation. Mineral Resource and Ore Reserve Estimation -The AusIMM Guide to Good Practice. Edwards, A.C. (ed.). Melbourne. The Australasian Institute of Mining and Metallurgy, 2001. pp. 147-156.
2. GUIBAL, D. Variography, a Tool for the Resource Geologist. Mineral Resource and Ore Reserve Estimation-The AusIMM Guide to Good Practice. Edwards, A.C. (ed.). Melbourne. The Australasian Institute of Mining and Metallurgy, 2001. pp. 85-90.
3. STEGMAN, C.L. How Domain Envelopes Impact on the Resource Estimate -Case Studies from the Cobar Gold Field, NSW, Australia. Mineral Resource and Ore Reserve Estimation-The AusIMM Guide to Good Practice. Edwards, A.C. (ed.). Melbourne. The Australasian Institute of Mining and Metallurgy, 2001. pp. 221-236.
4. EFRON, B. The jackknife, the bootstrap, and other resampling plans. Philadelphia, Society for Industrial and Applied Mathematics, 1982. 100 pp.
5. JOURNEL, A.G. and HUIJBREGTS, C.J. Mining Geostatistics. London, Academic Press, 1978. 600 pp.
6. SINCLAIR, A.J. and BLACKWELL, G.H. Applied mineral inventory estimation. Cambridge, Cambridge University Press, 2002. 381 pp.
7. MATHERON, G. La déstructuration des hautes teneurs et le krigeage des indicatrices. Internal report N-761, Centre de Géostatistique, Ecole des Mines de Paris, Fontainebleau, 1982.33 pp.
8. GOOVAERTS, P. Geostatistics for natural resources evaluation. New York, Oxford University Press, 1997. 480 pp.
9. ROYLE, A.G. How to use geostatistics for ore reserve classification. World Mining, 1977. vol. 30, pp. 52-56.
10. SABOURIN, R. Application of a geostatistical method to quantitatively define various categories of resources. Geostatistics for Natural Resource Characterization. Verly, G., David, M., Journel, A.G., and Maréchal, A. (eds.). Dordrecht. Reidel, 1984. vol. 1, pp. 201-215.
11. BLACKWELL, G.H. Relative kriging errors - a basis for mineral resource classification. Exploration and Mining Geology, 1998. vol. 7, no. 1-2, pp. 99-106.
12. ARMSTRONG, M., GALLI, A.G., LE LOC'H, G., GEFFROY, F., ano ESCHARD, R. Plurigaussian simulations in geosciences. Berlin, Springer, 2003. pp. 149.
13. LARRONDO, P., LEUANGTHONG, O., and DEUTSCH, C.V. Grade estimation in multiple rock types using a linear model of coregionalization for soft boundaries. International Conference Mining Innovation Minin 2004. Magri, E., Ortiz, J., Knights, P., Henríquez, F., Vera, M., and Barahona, C. (eds.). Santiago de Chile, Gecamin Ltda, 2004. pp. 187-196.
14. WACKERNAGEL, H. Multivariate geostatistics: an introduction with applications. Berlin, Springer, 2003. pp. 387.