Application of statistical approaches to analyze geological, geotechnical and hydrogeological data at a fractured-rock mine site in Northern Canada

Mine site characterization often results in the acquisition of geological, geotechnical and hydrogeological data sets that are used in the mine design process but are rarely co-evaluated. For a study site in northern Canada, bivariate and multivariate (hierarchical) statistical techniques are used to evaluate empirical hydraulic conductivity estimation methods based on traditional rock mass characterisation schemes, as well as to assess the regional hydrogeological conceptual model. Bivariate techniques demonstrate that standard geotechnical measures of fracturing are poor indicators of the hydraulic potential of a rock mass at the study site. Additionally, rock-mass-permeability schemes which rely on these measures are shown to be poor predictors of hydraulic conductivity in untested areas. Multivariate techniques employing hierarchical cluster analysis of both geotechnical and geological data sets are able to identify general trends in the data. Specifically, the geological cluster analysis demonstrated spatial relationship between intrusive contacts and increased hydraulic conductivity. This suggests promise in the use of clustering methods in identifying new trends during the early stages of hydrogeological characterization.