Opportunities for Sustainability with Multiscale Minerals Value Chain Integration

Abstract:
Recent advances in sensing have augmented ore discovery, mining and sorting procedures that promise to improve the effectiveness and sustainability of mining operations. While these activities operate at different spatial and temporal scales, combining posterior models can further benefit the sustainability of exploration and mining operations. Discovering the combination of data and modelling techniques that operate across scales to achieve reliable predictions takes time and effort.

Traditionally, we use geophysics at the regional (100s km) to camp (10s km) scales. Geophysical datasets, like gravity and magnetics can be interpreted to identify geological structures that help us discover mineral deposits. The utility of geophysics at these scales means they are almost ubiquitous features for machine learning models that predict locations of mineralisation at different scales. We use petrophysics to make sense of our interpretations as properties like density and magnetic susceptibility form a critical knowledge link between geophysics and geology. For example, density data helps with gravity data and is an important rock property for many activities in the minerals value chain. This presentation presents the challenges, potential solutions and benefits for data integration in the minerals value chain.

Dr Mark Lindsay, DARE Domain Lead – Minerals:
Mark Lindsay completed his BSc (Honours) at Monash University in 2008 and graduated from his PhD at Monash University and Université Paul Sabatier (Toulouse III) in October 2013.

He is currently a Science Leader at the CSIRO and leads “Minerals 4D” and digitalisation of the mining value chain. Mark is also an Adjunct Senior Research Fellow in the School of Earth Sciences, Centre for Exploration Targeting, at the University of Western Australia. His research interests include complex Earth systems, knowledge management and representation, uncertainty and ambiguity in 3D geological and mineral exploration modelling, and the process and psychology of data interpretation. These themes are an important field of research that have the potential to have a large impact on current practices of deterministic modelling and risk assessment.

Mark is working toward a stochastic approach to modelling that attempts to understand the importance of different data types in answering geoscientific questions, and how knowledge and associated uncertainties propagate through the mining value chain.