Recognition coefficient of spatial geological features, an approach to facilitate criteria weighting for mineral exploration targeting

Document Type : Research Paper


1 Faculty of Engineering, Malayer University, Malayer, Iran.

2 Department of Mining Engineering, Faculty of Engineering, University of Birjand, Birjand, Iran.

3 School of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran



The different methods for the delineation of favorable areas for mineral exploration utilize exploration criteria in regard to targeted mineral deposits. The criteria are elicited according to conceptual model parameters of the targeted mineral deposits. The selection of indicator criteria, the evaluation of their comparative importance, and their integration are critical in mineral prospectivity modeling. In data-driven methods, indicator features are weighted using functions whereby the importance of certain indicator criteria may be ignored. In this paper, a data-driven method is described for recognizing and converting exploration criteria into quantitative coefficients representing favorability for the presence of the targeted mineral deposits. In this approach, all of the indicator features of the targeted mineral deposits are recognized and incorporated into the modeling procedure. The method is demonstrated for outlining favorable areas for Mississippi valley-type fluorite deposits in an area, north of Iran. The method is developed by studying and modeling the geological characteristics of known mineral occurrences. The degree of prediction ability of each exploration criterion is quantified as a recognition coefficient, which can be used as a weight attributed to the criterion in mineral exploration targeting to outline favorable areas.


Main Subjects

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