Advanced Resource Assessment Methods

Staff

Tasks

Project summary:

The fundamental reason for the Mineral Resource Program is to provide useful minerals information to policy makers. Needed information comes from two situations: estimates of resources, reserves, or composition of known mineral deposits and estimates of resources in undiscovered deposits. This project addresses the clear need to improve undiscovered deposit estimation. The project objective is to improve methodologies, tools, and models for quantitative mineral-resource and mineral-environmental assessments. Quantitative methods and models are required in order to make resource assessments explicit and reproducible, to allow uncertainty to be presented, and to allow alternative method comparisons. We need to know the uncertainty of estimates if we are to reduce it. The project's focus is on being able to make unbiased quantitative assessments in a format needed in decision-support systems so that the consequences of alternative courses of action with respect to minerals can be examined.

The project represents an integrated research strategy to improve tools for quantitative mineral-resource and mineral-environmental assessments. Fundamental to this strategy is the development of quantitative mineral deposit models. Far too few thoroughly explored mineral deposits are available in most local areas for reliable identification of the important geoscience variables or for robust estimation of undiscovered deposits-thus we need mineral-deposit models. Mineral-deposit models represent the glue that bonds together diverse information on geology, mineral occurrences, geochemistry, and geophysics used in resource assessments and mineral exploration. Quantifying attributes of the geologic environment of deposit models enables reliable integration of different kinds of information in GIS-based analysis and decision support systems. Also, relative frequencies of deposit attributes provide perspective for mineral-environmental deposit models [based on detailed "representative deposits"]. Wherever spatial data, such as rock types, structure, and associated deposit types prove predictive, it is possible to integrate the information to classify deposits and occurrences into types as well as link GIS data to mineral-deposit models. These quantitative attributes could then be used in the objective and unbiased identification and classification of permissive terranes in resource assessments. [The project is designed to take advantage of recent advances that increase the chances of successful deposit site selection and unbiased "favorability" estimation]. The project is designed to construct economic filters that can be used on all mineral-deposit types. It will also improve the MARK 3 simulator by making it's interface more user friendly, better documenting features and models, and incorporating the economic filters.