Statistical decision in regional exploration; application of regression and Bayesian classification analysis in the southwest Wisconsin zinc area

A statistical decision model based on regression and Bayesian classification techniques is designed to help predict the most favorable drilling targets in regional exploration programs. The procedure is applied to a 225 square mile portion of the southwest Wisconsin zinc area hitherto little explored. The analysis led to the selection of 22 targets with high success probabilities (0.80 or better) and high regression estimates.The validity of the method depends on the quality of field data and on a careful selection of relevant factors rather than the nature of the field techniques used for the coverage. The aim of the method is to assist the exploration management in making objective decisions fully consistent with the initial goals of the programs.