The geology of any given area is probably the single most important indicator of its mineral potential. Key words: Bayesian probability, weights of evidence, spatial correlation, mineral potential mapping, Baguio gold district (Philippines) The probabilistic approach to mineral potential mapping is effective for the Baguio district in that the predictive maps depict several zones of high potential that contain or are close to the known gold occurrences. Cross-comparison of each predictive map with the other gold occurrence dataset indicate that at least 56% of the gold occurrence points fall within zones of high potential. The predictive maps based on each occurrence dataset show that 79% and 70% of the known large-scale and small-scale gold occurrences, respectively, fall within zones of high potential. The datasets used are geological map, map of faults/fractures and large-scale and small-scale gold occurrences data. Conditional independence is tested by pairwise chi-square tests and by overall comparison of predicted and observed number of mineral occurrences. Combining the binary maps requires that these are conditionally independent from one another with respect to the mineral occurrences.

The result is a map of posterior probabilities whose magnitude represent mineral potential. The loge of the posterior odds of a mineral occurrence given the presence/absence of a predictor pattern is then obtained by adding the weights of each binary pattern and the loge of the prior odds. In this study, the Studentized C served as the basis for converting multi-class 'proximity maps' into binary predictor patterns. The contrast,, provides a measure of the spatial correlation between a binary pattern and a set of occurrence points. The natural logarithms (loge) of these probabilities represent the weight for the pattern present, W+, and the weight for the pattern absent, W. Using Bayes' rule, two probabilities can be computed that a binary predictor pattern contains a mineral occurrence. International Institute for Aerospace Survey and Earth Sciences, Delft, The Netherlands AbstractĪ probabilistic approach to mineral potential mapping is demonstrated in the Baguio gold district, Philippines. International Institute for Aerospace Survey and Earth Sciences, Delft, The Netherlands Mines and Geosciences Bureau, Regional Office No. Return to GeoComputation 99 Index Geologically-constrained probabilistic mapping of gold potential, Baguio District, Philippines Geologically-constrained probabilistic mapping of gold potential, Baguio District, Philippines

Where is gold found geologically