Targeting Workflow Report

The Targeting Workflow is designed to guide the user through a step-by-step process of combining 3D datasets by different processes to obtain a comprehensive exploration interpretation. The result of the combination is an additional quantitative layer of interpretation that is tied with a multi-disciplinary approach to targeting.

The different combination methods can be based on either subjective empirical models or probabilistic models, referred to as knowledge-driven and data-driven approaches, respectively. Knowledge-driven approaches are based on the experience of domain experts and include processes such as Boolean Logic, Index Overlay, Multi-Class Index Overlay, Dempster-Shafer Belief Theory, and Fuzzy Logic. Data-driven approaches require that known occurrences of what we are looking for exist in the earth model, such as a set of deposits, and include the Prospector Model, Weights-of-Evidence, Weighted Logistic Regression, Likelihood Ratio, and Neural Networks, among others. In addition, hybrid models using combinations of two or more different approaches have proven to be effective in many studies. Harris and Sanborn-Barrie (2006)¹ provide a comprehensive overview of the various modeling approaches.

The Targeting Workflow provides functionality to perform Boolean Logic, Index Overlay, Multi-Class Index Overlay, and Weights-of-Evidence prediction models. Each uses a combination of exploration criteria to generate a prediction model which can be used for targeting XYZ drillhole target positions to be further investigated for mineral potential. Each of the processes implemented here is based on documentation from Bonham-Carter (1994)².