Data Envelopment Analysis: A knowledge-driven method for mineral prospectivity mapping

This paper describes the application of a proposed method in mineral prospectivity mapping (MPM), i.e. the Data Envelopment Analysis (DEA) technique as a well-known approach in the operational research which involves the representation and integration of the evidential map layers derived from different geo-datasets consisting of the geological, geophysical and geochemical layers of Nowchun Cu-Mo deposit located in the SE of Iran. DEA has proven to be a useful tool for assessing efficiency or productivity of organizations, which in managerial decision making is of fundamental practical importance. Its powerful ranking characteristic for varieties of alternatives in a multiple criteria decision-making problem was used to produce the desired MPM in the region of interest. The outputs were validated by taking into account the twenty-nine boreholes that have been classified into five classes based upon the amounts of Cu grade above an economical cut off value of 0.2% multiplied by its thickness along each borehole. The performance of the proposed method was investigated as well showing its strong applicability in the MPM process while reducing the cost of exploratory drilling in the prospect area. (C) 2015 Elsevier Ltd. All rights reserved.