Day Three
North American Perspectives
Description
The structural interpretation of ore deposits in 3D is a key aspect of deposit understanding in mining exploration and exploitation. Three-dimensional structural interpretations support exploration targeting, resource estimation, and geomechanical modelling. The 3D structural interpretation of an ore deposit is generally conducted using all available relevant data, including drilling data, underground and surface observations, and geophysical survey data.
In general, drilling data is the most used dataset as it can have widespread coverage of a deposit. Although drill core descriptions are generally used as the primary data to directly identify structures, the visualization of assay data can be used as a powerful indirect tool to identify structural patterns and structures.
Multi-element assays and sometimes large suits of major, minor, and trace elements are often available in assayed intervals within ore deposits. This multivariate data is useful for understanding mineralization, lithology, and alteration variability; however, its interpretation often requires domain expertise in geochemistry and ore deposit geology. This limits its usage for structural interpretation.
This paper proposes a simple workflow based on a series of statistical, machine learning, and visualization tools that allows rapid integration of geochemical data to support structural interpretation.
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