Automatic parameter tuning of multiple-point statistical simulations for lateritic bauxite deposits

Yasin Dagasan, Philippe Renard, Julien Straubhaar, Oktay Erten, Erkan Topal

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Article number220
JournalMinerals
Volume8
Issue number5
DOIs
Publication statusPublished - May 1 2018

Fingerprint

Bauxite deposits
bauxite
Tuning
Statistics
simulation
Sensitivity analysis
Bauxite mines
histogram
conditioning
sensitivity analysis
Mineral industry
Simulated annealing
parameter
simulated annealing
laterite
Deposits
footwall
mining industry
Sampling
statistics

Keywords

  • Bauxite mining
  • Direct sampling
  • Laterite
  • MPS
  • Multiple-point statistics
  • Parameter selection
  • Pattern statistics
  • Pseudo-histogram
  • Simulated annealing
  • Simulations

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Geology

Cite this

Automatic parameter tuning of multiple-point statistical simulations for lateritic bauxite deposits. / Dagasan, Yasin; Renard, Philippe; Straubhaar, Julien; Erten, Oktay; Topal, Erkan.

In: Minerals, Vol. 8, No. 5, 220, 01.05.2018.

Research output: Contribution to journalArticle

Dagasan, Yasin ; Renard, Philippe ; Straubhaar, Julien ; Erten, Oktay ; Topal, Erkan. / Automatic parameter tuning of multiple-point statistical simulations for lateritic bauxite deposits. In: Minerals. 2018 ; Vol. 8, No. 5.
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