Vignette d'image

Straubhaar, Julien

Nom
Straubhaar, Julien
Affiliation principale
Site web
Email
julien.straubhaar@unine.ch
Identifiants
https://libra.unine.ch/handle/123456789/151
_
0000-0003-2718-4332

Résultat de la recherche

Filtres

2
2
Réinitialiser les filtres

Paramètres

Voici les éléments 1 - 2 sur 2
  • Publication
    Accès libre
    Pilot Point Optimization of Mining Boundaries for Lateritic Metal Deposits: Finding the Trade-off Between Dilution and Ore Loss
    (2018)
    Yasin Dagasan
    ;
    Renard, Philippe 
    ;
    Julien Straubhaar 
    ;
    Oktay Erten
    ;
    Erkan Topal
    Geological contacts in lateritic metal deposits (footwall topographies) often delineate the orebody boundaries. Spatial variations seen in such contacts are frequently higher than those for the metal grades of the deposit. Therefore, borehole spacing chosen based on the grade variations cannot adequately capture the geological contact variability. Consequently, models created using such boreholes cause high volumetric uncertainties in the actual and targeted ore extraction volumes, which, in turn, lead to high unplanned dilution and ore losses. In this paper, a method to design optimum ore/mining boundaries for lateritic metal deposits is presented. The proposed approach minimizes the dilution/ore losses and comprises two main steps. First, the uncertainty on the orebody boundary is represented using a set of stochastic realizations generated with a multiple-point statistics algorithm. Then, the optimal orebody boundary is determined using an optimization technique inspired by a model calibration method called Pilot Points. The pilot points represent synthetic elevation values, and they are used to construct smooth mining boundaries using the multilevel B-spline technique. The performance of a generated surface is evaluated using the expected sum of losses in each of the stochastic realizations. The simulated annealing algorithm is used to iteratively determine the pilot point values which minimize the expected losses. The results show a significant reduction in the dilution volume as compared to those obtained from the actual mining operation.
  • Publication
    Accès libre
    Automatic Parameter Tuning of Multiple-Point Statistical Simulations for Lateritic Bauxite Deposits
    (2018)
    Yasin Dagasan
    ;
    Renard, Philippe 
    ;
    Straubhaar, Julien 
    ;
    Oktay Erten
    ;
    Erkan Topal
    The application of multiple-point statistics (MPS) in the mining industry is not yet widespread and there are very few applications so far. In this paper, we focus on the problem of algorithmic input parameter selection, which is required to perform MPS simulations. The usual approach for selecting the parameters is to conduct a manual sensitivity analysis by testing a set of parameters and evaluating the resulting simulation qualities. However, carrying out such a sensitivity analysis may require significant time and effort. The purpose of this paper is to propose a novel approach to automate the parameter tuning process. The primary criterion used to select the parameters is the reproduction of the conditioning data patterns in the simulated image. The parameters of the MPS algorithm are obtained by iteratively optimising an objective function with simulated annealing. The objective function quantifies the dissimilarity between the pattern statistics of the conditioning data and the simulation image in two steps: the pattern statistics are first obtained using a smooth histogram method; then, the difference between the histograms is evaluated by computing the Jensen–Shanon divergence. The proposed approach is applied for the simulation of the geological interface (footwall contact) within a laterite-type bauxite mine deposit using the Direct Sampling MPS algorithm. The results point out two main advantages: (1) a faster parameter tuning process and (2) more objective determination of the parameters.