MODELING STRUCTURAL CONTROL OF GOLD MINERALIZATION AT THE FLORIDA CANYON EPITHERMAL GOLD DEPOSIT, NEVADA: A 3-D GIS APPROACH

The Florida Canyon Au-Ag deposit in Pershing County, Nevada is a large, disseminated, low sulfidation epithermal gold deposit. This deposit is located along the range-bounding fault of the northwestern margin of the Humboldt Range. Mineralization and hydrothermal alteration are hosted by siliciclastic metasedimentary rocks of Triassic age. Gold mineralization is most intensely developed at the intersection of the N-S range-bounding fault and a NE-trending shear zone. Geologic information indicates gold distribution is primarily controlled by structural features such as faults, shear-zones and locally fractures. Consequently, anomalous Au concentration maps can be helpful in mapping controlling structural features that are partially known or remain unrecognized.

A three-dimensional drill-hole dataset with Au assays reported for every five feet was available for this project. A GIS-based analysis of Au concentrations using both raster and vector type data provided a three-dimensional model of gold distribution in the deposit. Anomalous gold concentrations followed the known trace of the range-bounding fault and NE-trending shear zone which served to validate the mapping approach. Other Au anomalies with much less obvious structural control were mapped including linear zones trending NE-SW across the deposit and irregular zones in eastern part of the deposit, which could represent areas of structural intersections. Using advanced 3-D GIS techniques, data layers of relevant geological features such as lithology, surfaces defining limits of oxidation can be combined with the Au concentration maps for interpretation. Furthermore, applying statistical constraint such as limits of standard deviations, it is possible to create 3-D spatial-statistical models of Au distribution that may reveal particularly subtle structural features controlling mineralization. Such novel approaches of mapping element distribution can be useful in the advanced stages of mineral exploration.