Assessment of coal deposit using multivariate statistical analysis techniques

Abstract

ABSTRACTEnergy is one of the indispensable factors regarding the economic development of Turkey. Examination of calorific values in coal deposits has importance in the production of energy, and thus planning of the coal deposit. In this article, multivariate statistical analysis techniques, including cluster analysis and discriminant analysis, were applied to calorific values obtained from boreholes. Cluster analysis grouped borehole locations into two clusters based on the similarity of calorific values. Afterwards, discriminant functions were supported to cluster analysis and developed a linear discriminant function. Based on the locations of the boreholes, it was concluded that calorific values are a highly central part of the coal deposit. Thus, this article shows the usefulness of multivariate statistical analysis techniques for understanding spatial variation of coal deposits and effective deposit management.