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Personne :
Guido, Sébastien

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Guido

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Sébastien

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Département de génie des mines, de la métallurgie et des matériaux, Faculté des sciences et de génie, Université Laval

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ncf11923164

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Voici les éléments 1 - 2 sur 2
  • PublicationRestreint
    Stope performance assessment at the Goldcorp Eleonore mine using bivariate analysis
    (ISRM, 2017-10-02) Guido, Sébastien; Grenon, Martin; Germain, Paul
    Comparing stope performance relative to the engineering design is of paramount importance for any mining operation. A database was created of 105 stopes mined between 170 m and 800 m below surface from July 2014 to November 2016 at the Goldcorp Eleonore mine. The database consists of more than 20 parameters defining spatial, mining, geometrical, geological, drill-and-blast, and temporal stope properties. Univariate and bivariate statistical analyses were conducted using the database to better understand the root causes of stope performance. The study has allowed parameters controlling stope performance to be identified. These are the spatial localization of the stope (mining horizon, mining lenses, and central location within the orebody), the mining method, and the orientation of the major structures relative to stope orientation, the global stope drilling pattern and the stand-up time.
  • PublicationRestreint
    Contributions to geomechanical stope optimization at the Goldcorp Eleonore Mine using statistical analysis.
    (International Society for Rock Mechanics and Rock Engineering, 2018-10-01) Guido, Sébastien; Grenon, Martin
    Stope performance is critical and is therefore usually assessed in mine operations. However, the factors controlling stope performance (such as overbreak) are not always fully understood. This was the case at the Goldcorp Eleonore operation, a relatively new mine located in a new mining area hundreds of kilometers from other existing operations. Still, stope design guidelines had to be elaborated to mitigate hanging wall overbreak and sustain a high mining rate from narrow vein stopes (as many as four per week) at acceptable costs. This paper presents a database of 105 stopes, mined between July 2014 and November 2016, which collated more than 50 parameters defining spatial, geometrical, geomechanical, geological and stope performance aspects. The points in this database were superimposed on the existing Stability Graph with ELOS curves (Clark, 1998) to assess its accuracy at Eleonore. This accuracy was shown to be limited and improvements were needed for forward analyses to be reliable. Improved predictions were obtained using various statistical analysis techniques such as multiple linear regressions (MLR), binary logistic regressions and principal component logistic regressions (PCLR) with parameters other than those used in the standard method. These statistical techniques and their results are presented in this paper and compared with those from the existing stability graph.