Data Envelopment Analysis as a tool for the exploration phase of mining

Tommi Kauppinen*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

The exploration of mining has often been limited by time-consuming methods of analysis. This paper introduces Data Envelopment Analysis (DEA) as a new tool for the exploration phase of mining. DEA is a non-parametric method for data fusion, and it is used alongside with the on-site Raman analysis. Ten meters of halved rock drillcore from the Kittila mine (Suurikuusikko deposit) were pulverised and homogenised, thus ensuring that each meter had a representative sample. These 10 samples, one for each meter, were subsequently measured with a grid measurement (32×32 measurement each) using the Raman setup. All the data points were analysed using the point-count method. After identifying the frequency at which potentially valuable minerals appear in the samples, this information was analysed using DEA. The study ends by presenting an efficiency score for each meter of drillcore. These efficiency scores enable geologists to judge more rapidly which parts of the drillcore must be logged more carefully. In addition, Principal Component Analysis (PCA) is discussed as an alternative for producing similar results to DEA.

Original languageEnglish
Pages (from-to)96-102
Number of pages7
JournalCOMPUTERS AND GEOSCIENCES
Volume93
DOIs
Publication statusPublished - 1 Aug 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • Data Envelopment Analysis
  • Exploration phase of mining
  • Principal Component Analysis
  • Raman analysis

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