We're investigating aspects of resource exploration, including mineral resources based on petrographic, geochemical, computational and geophysical methods.
The Mineral and Energy Resources Research Group researches nearly all aspects of resource exploration, including energy and mineral resources. Research encompasses fundamental processes which ultimately drive the formation and accumulation of valuable raw Earth materials.
Project STELLAR (Spatio TEmporaL expLorAtion for Resources) is a collaboration between BHP and the EarthByte Group aimed at implementing big and complex spatio-temporal data analysis and modelling to support the needs of BHP in global resource exploration. Split into multiple phases over the next 3.5 years, the project will connect BHP’s warehouse of global resource knowledge with the EarthByte Group’s expertise in tectonic, geodynamic and surface process modelling. STELLAR is structured into four programs, (1) Plate Tectonics and Geodynamics, led by ARC DECRA Fellow Dr Sabin Zahirovic, (2) Paleogeography, led by Dr Maria Seton, (3) Surface Processes and Stratigraphy, led by Dr Tristan Salles and (4) Spatio-Temporal Data Mining, led by Prof Dietmar Müller. Together with technical leaders from BHP the team will integrate geodata through geological time, couple plate reconstructions with geodynamic models, construct dynamic paleo-elevation models, design adaptable landscape evolution models and provide key inputs for spatio-temporal data analysis for global resource exploration towards a low-emissions economy.
We are developing machine learning approaches to aid mineral exploration. One example is the Capricorn Orogen of Western Australia, where the underexplored Gascoyne Province is largely blanketed by sedimentary and regolith cover, making it especially important to use cost-effective methods to improve our understanding of its geology and ultimately promote mineral exploration investment.
Here we are developing a method that exploits the association of mineral deposits with crustal faults. One approach uses computer vision techniques to learn the association between mineral deposits and geological lineaments in Landsat data. A second approach fuses geological field observations with geophysical data, particularly magnetic and gravity anomalies, to create a probabilistic map of the three-dimensional structure of geological boundaries. In a third case study we developed a Gaussian classifier methodology to develop iron ore prospectivity mapping of the Yilgarn and Pilbara cratons. A fourth case study is focussed on combining a multitude of geological and geophysical data sets to create porphyry copper-gold prospectivity maps for regions in central NSW. A fifth case study is based on spatio-temporal analysis of mineral deposits, enabled by the pyGPlates Python library for spatio-temporal data mining.
Efficiently extracting subduction zone characteristics for age-coded ore deposits allows us to unravel the tectonic environments of Pacific-rim porphyry copper-gold deposits along the Andes since the Late Cretaceous. Future pyGPlates applications will integrate tectonic reconstructions with high-resolution high-performance computer simulations and statistical model analysis and optimisation for the development of an “experimental planet”. These linked technologies have the potential to reveal the big picture of how crustal and deep-Earth processes interact, and thus the intricate pathways in the planet’s geological development. Collaborators in these projects include researchers from Curtin University and the Sydney Informatics Hub.
Ore deposits are the products of highly selective mass transfer processes created in response to large-scale tectonic events. We study the evolution of Earth’s continents in relation to the temporal and spatial distribution of ore deposits in order to define mineral systems at all scales. Tectonic cycles, from the development and break up of supercontinents to the recurring associations of magma types and specific ore types are studied to establish which factors provide optimal metal sources, ore fluid pathways and sites of efficient mineral deposition. Our studies employ combinations of field work, microscopic observations, geochemistry and isotopic tracers along with remotely sensed data. We employ computer-based plate reconstructions and numerical models of early continent development to understand ore formation over the last 3 billion years.