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Geostatistical Framework for Modelling Clay Deposits: Nova Veneza Case Study in Southern Brazil

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Geostatistics Rio 2000

Abstract

The region of Criciúma, Southern Brazil, is known as one of the main ceramic industrial districts in the world. Clay minerals are one of the key ingredients in the ceramic industry. Clay characteristics including several physical and chemical parameters need to be known throughout the entire deposit to help in defining the mining plan, scheduling and blending strategies.

This paper proposes a geostatistical framework to model two essential clay properties required to be controlled in the ceramic industrial process, respectively water absorption and linear retraction. The methodology proposed is illustrated in a deposit consisting of two sedimentary systems conditioned by tectonic structures. These structures define two anisotropy systems interacting and affecting the spatial continuity of the parameters studied. Geological, topographical and geomorphological mapping were followed by geostatistical evaluation. Two distinct geological domains were defined, resulting in two sub-datasets. Samples available from auger holes were logged and analysed at different lengths (support), requiring the use of accumulations to overcome the problem caused by multiple sample supports.

Ordinary kriging was selected to estimate 25 x 25m blocks and stochastic simulation was used to assess the variability of the thickness values assigned to each block. Risk on recoverable reserves was quantified. The results obtained encourage the application of the proposed methodology as they proved to be more efficient than traditional evaluation methods.

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References

  • Armstrong, M. 1998. “Basic linear geostatistics”, Berlin, Springer. 153 p

    Book  MATH  Google Scholar 

  • Barba, A., Feli,. C., Garcia, J., Ginés, F., Sanchez, E., Sanz, V.and Beltran, V. 1997 “Materias primas para la fabricación de soportes de baldosas ceramicas”, Instituto de Tecnologia Ceramica, Castellón, 292 p.

    Google Scholar 

  • Borgman, L. E. and Frahme, R.B. 1975. “A Case Study: Multivariate Properties of Bentonite in Northeastern Wyoming”, in: “Advanced geostatistics in the mining industry”, Nato Advanced Study Industry, Rome, p.381390

    Google Scholar 

  • Bortoluzzi, C.A., Awdziej, J. and Zardo, S.M., 1987. “Geologia da Bacia do Parana em Santa Catarina”, in: “Textos Basicos de Geologia e Recursos Minerais de Santa Catarina”, DNPM/Coordenadoria de Recursos Minerais da Secretaria da Ciência e Tecnologia, Minas e Energia, Florianópolis, 216 p.

    Google Scholar 

  • Costa, J.F., 1997. “Developments in Recoverable Reserves and Ore Body Modeling”, PhD Thesis, WH Bryan Mining Geology Research Centre, The University of Queensland, 333 p.

    Google Scholar 

  • David, M. 1997. “Geostatistical Ore Reserve Estimation”, Elsevier, Amsterdam.

    Google Scholar 

  • Dimitrakopoulos, R. 1998. “Conditional Simulation Algorithms for Modeling Orebody Uncertainty in Open Pit Optimisation”, International Journal of Surface, Reclamation and Environment, vol. 12, p. 173–179.

    Article  Google Scholar 

  • Durâo, F., Cortez, L., Brito, G.and Orea, S. 1999. “Optimization of Ceramic Pastes Production by Modeling the Chemical and Physical Properties of their Clay Components”, Proceedings, 28th International Symposium on Computer Applications in the Mineral Industries (APCOM), Golden, U.S.A, 511–518, October.

    Google Scholar 

  • Goovaerts, P., 1997. “Geostatistics for Natural Resources Evaluation”, Oxford University Press, 438 p.

    Google Scholar 

  • Isaaks, E.H., 1990. “The Application of Monte Carlo Methods to the Analysis of Spatially Correlated Data”, PhD

    Google Scholar 

  • Thesis, Stanford University, USA, 213p.

    Google Scholar 

  • Joumel A. G. and Huijbregts C. 1978. “Mining geostatistics”, London, Academia Press, 600 p. Isaaks E.H.and Srivastava R.M 1989. “An introduction to applied geostatistics”, N.Y: OUP. 561 p.

    Google Scholar 

  • Krige, D.G. 1981. “Lognormal-de Wijsian Geostatistics for Ore Evaluation South African Institute of Mining and Metallurgic”, Johannesburg, 51 p.

    Google Scholar 

  • Matheron, G. 1963. “Principles of Geostatistics”, Economic Geology, No. 58, p. 1246–1266.

    Article  Google Scholar 

  • Rossi, M.E. and Alvarado C., S.B. 1998 “Conditional simulations applied to recoverable reserves”, Proceedings, 27`h International Symposium on Computer Applications in the Mineral Industries (APCOM), London, United Kingdom, 19–23, April.

    Google Scholar 

  • Rossi, M.E. 1999. “Uncertainty and Risk Models for Decision-Making Processes” - Proceedings, 28th International Symposium on Computer Applications in the Mineral Industries (APCOM), Golden, U.S.A, 185–195, October.

    Google Scholar 

  • Silva, E.L., Ceita, A., Raspa, G. Sim-5es, J. and Bruno, R. 2000. “Estimation of the `In Situ’ Grain-Size Distribution Curve of Quihita Kaolin Deposit (South of Angola)”, WJ Kleingeld and DG Krige (eds.), Geostats 2000, Cape Town.

    Google Scholar 

  • Srivastava, R. M. 1994. “The Visualization of Spatial Uncertainty”, in “Stochastic Modeling and Geostatistics

    Google Scholar 

  • Principles, Methods and Case Studies“, The American Association of Petroleum Geologists, Julsa, p339–345. Stangler, R.L. 1999. ”Geostatistical Evaluation of a Clay Mineral Deposit in Nova Veneza, Brazil“, CFSG Report

    Google Scholar 

  • Centre de Geostatistique de Fontainebleau, France, S-378.

    Google Scholar 

  • Thwaites, A.M. 1998. “Assessment of geological uncertainty for a mining project”, Proceedings, 27th International Symposium on Computer Applications in the Mineral Industries (APCOM), London, United Kingdom, 391404, April.

    Google Scholar 

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© 2002 Springer Science+Business Media Dordrecht

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Stangler, R.L., Strieder, A.J., Koppe, J.C., Costa, J.F., Armstrong, M. (2002). Geostatistical Framework for Modelling Clay Deposits: Nova Veneza Case Study in Southern Brazil. In: Armstrong, M., Bettini, C., Champigny, N., Galli, A., Remacre, A. (eds) Geostatistics Rio 2000. Quantitative Geology and Geostatistics, vol 12. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-1701-4_10

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  • DOI: https://doi.org/10.1007/978-94-017-1701-4_10

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-5954-3

  • Online ISBN: 978-94-017-1701-4

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