prospectivity mapping

Neural network analysis of multi-element geochemistry

Multi-element soil geochemical data was analysed using neural network software for a client undertaking exploration for precious metals. Significant elemental associations known to typify certain mineralisation styles were identified and areas of relative prospectivity were delineated. The resulting data were post-processed using industry standard GIS software and imagery suitable for both internal and external stakeholder interest was generated. 

Integrated photogeological and 3D modelling study successfully completed

The study successfully delineated the aerial extent and relative thickness of a sequence of sub-horizontally layered sediments and volcaniclastics targeted by an international mining company for its mineral endowment, across a substantial area using remotely sensed imagery. As the features were captured in 3D while being view stereoscopically using a digital photogrammetric workstation, 3D geological models were constructed from which approximate unit and overburden thickness metrics were able to be estimated. The study also provided a series of maps showing relative prospectivity and numerous targets were highlighted for follow up investigation.