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Local Estimation of the Recoverable Reserves: Comparing Various Methods with the Reality on a Porphyry Copper Deposit

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Geostatistics for Natural Resources Characterization

Abstract

The objective of this article is to compare the estimates based on several non-linear methods with the actual figures. The methods tested were disjunctive kriging, multi-Gaussian kriging and a new method (uniform conditioning) which is simpler and computationally quicker than these two and yet still gives comparable results.

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References

  1. Matheron, G., 1976 (a), “Transfert functions and their estimations”, Proceeding of NATO A.S.I., D. Reidel, p. 221–236

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  2. Matheron, G., 1975 (b), “Les fonctions de transfert de petits panneaux”, CGMM, Fontainebleau, France.

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  3. Matheron, G., 1978, “Le krigeage disjonctif et le paramétrage local des reserves”, Ecole d’Eté, CGMM, Fontainebleau, France.

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  6. Verly, G., 1983, “The Multigaussian Approach and its Applications to the Estimation of Local Reserves”, J. of Math. Geol., Vol. 15, n° 2, pp. 263–290.

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Author information

Authors and Affiliations

  1. Centre de Géostatistique et de Morphologie Mathématique, Ecole Nationale Superieure des Mines de Paris, Fontainebleau, France

    Daniel Guibal & Armando Remacre

Authors
  1. Daniel Guibal
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  2. Armando Remacre
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Editor information

Editors and Affiliations

  1. Department of Applied Earth Sciences, Stanford University, Stanford, California, 94305, USA

    Georges Verly (Student) & Andre G. Journel (Professor) (Student) &  (Professor)

  2. Departement de Chimie Mineral, Ecole Polytechnique, C.P. 6079 Succ. A, Montreal, Quebec, H3C 3A7, Canada

    Michel David (Professor) (Professor)

  3. Societe Elf Aquitaine (Production), DOTI-Developpement, 64018, Pau, France

    Alain Marechal (Engineer) (Engineer)

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© 1984 D. Reidel Publishing Company

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Guibal, D., Remacre, A. (1984). Local Estimation of the Recoverable Reserves: Comparing Various Methods with the Reality on a Porphyry Copper Deposit. In: Verly, G., David, M., Journel, A.G., Marechal, A. (eds) Geostatistics for Natural Resources Characterization. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3699-7_25

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  • DOI: https://doi.org/10.1007/978-94-009-3699-7_25

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-8157-3

  • Online ISBN: 978-94-009-3699-7

  • eBook Packages: Springer Book Archive

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