Abstract
Conventional methods for the estimation of mineral resources potential are broadly subdivided into two groups: subjective models based upon ore genetic theories and objective models based upon multiple geological observations. This paper examines some objective means that brings the two types of model together and jointly utilizes the information from both ore genesis and geological observations in delineation of promising areas for mineral exploration. These promising areas are here referred to as intrinsic geological units. They are so-called because they are not identified directly with respect to mineral deposits, but delineated in terms of some critical genetic factor, a necessary condition for formation of the mineral deposits. Four major steps are involved in this analysis. First, establish the structure of “critical genetic factor-recognition criteria-multiple geodata” for the deposit type of interest. Next, estimate probabilities of occurrence of each of the recognition criteria based upon geological observations. Third, a synthesized probability measure for occurrence of critical genetic factor is determined as an optimum linear combination of the probabilities estimated in the second stage. Finally, intrinsic geological units are delineated by optimally discretizing the probability measure for the critical genetic factor. This estimation procedure is formulated into a three-stage optimization model: logistic regression-quadratic programming-optimum discretization, which is demonstrated with a case study on epithermal Au-Ag mineral deposits in the Walker Lake quadrangle of California and Nevada. In this case study, heat source is selected as the critical genetic factor and it is identified by three selected recognition criteria: Au-Ag mineral occurrence, Tertiary intrusive, and hydrothermal alteration. The intrinsic geological units for epithermal Au-Ag deposits are delineated on the basis of six different preprocessed and integrated geological, geochemical, and geophysical fields.
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