Abstract
Over the last two decades, Mineral Resources Tasmania has been developing regional 3D geological and geophysical models for prospective terranes at a range of scales and extents as part of its suite of precompetitive geoscience products. These have evolved in conjunction with developments in 3D modeling technology over that time. Commencing with a jurisdiction-wide 3D model in 2002, subsequent modeling projects have explored a range of approaches to the development of 3D models as a vehicle for the better synthesis and understanding of controls on ore-forming processes and prospectivity. These models are built on high-quality potential field data sets. Assignment of bulk properties derived from previous well-constrained geophysical modeling and an extensive rock property database has enabled the identification of anomalous features that have been targeted for follow-up mineral exploration. An aspect of this effort has been the generation of uncertainty estimates for model features. Our experience is that this process can be hindered by models that are too large or too detailed to be interrogated easily, especially when modeling techniques do not readily permit significant geometric changes. The most effective 3D modeling workflow for insights into mineral exploration is that which facilitates the rapid hypothesis testing of a wide range of scenarios whilst satisfying the constraints of observed data.
Highlights
We discuss the outcomes of 3D geological and geophysical modeling in Tasmania, starting with the Statewide 3D geological model released by Mineral Resources Tasmania (MRT) in 2002
The Mathinna Supergroup, an Ordovician to Early Devonian turbiditic sequence with cumulative stratigraphic thicknesses exceeding 10 km, is the oldest unit exposed in the Eastern Tasmanian terrane (Figure 2), Cambrian ultramafic rocks are interpreted on geophysical evidence to underlie much of the northern half of the Eastern
The potential field contribution from any magnetic/gravity source located beyond the extents of the local model can interfere with this model and be erroneously attributed to its response when the data are inverted
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Metrics multiple geological models facilitate that satisfy the geophysical [10] These advances allow us to quantify uncertainty (to a degree) of the geometry of geologWe detail and discuss our modeling efforts over the last decade, and present new ical units at depth through statistically generated 3D sensitivity metrics from multiple results using statistically generated 3D sensitivity metrics to address uncertainty. These geological models that satisfy the geophysical observations [10].
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