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Alison Kirkby

Publications and source records attributed to Alison Kirkby.

2 recordsLinked to original sources

Lithospheric conductors reveal source regions of convergent margin mineral systems

The clean energy transition will require a vast increase in metal supply, yet new mineral deposit discoveries are declining, due in part to challenges associated with exploring under sedimentary and volcanic cover. Recently, several case studies have demonstrated links between lithospheric electrical conductors imaged using magnetotelluric (MT) data and mineral deposits, notably Iron Oxide Copper Gold (IOCG). Adoption of MT methods for exploration is therefore growing but the general applicability and relationship with many other deposit types remains untested. Here, we compile a global inventory of MT resistivity models from Australia, North and South America, and China and undertake the first quantitative assessment of the spatial association between conductors and three mineral deposit types commonly formed in convergent margin settings. We find that deposits formed early in an orogenic cycle such as volcanic hosted massive sulfide (VHMS) and copper porphyry deposits show weak to moderate correlations with conductors in the upper mantle. In contrast, deposits formed later in an orogenic cycle, such as orogenic gold, show strong correlations with mid-crustal conductors. These variations in resistivity response likely reflect mineralogical differences in the metal source regions of these mineral systems and suggest a metamorphic-fluid source for orogenic gold is significant. Our results indicate the resistivity structure of mineralized convergent margins strongly reflects late-stage processes and can be preserved for hundreds of millions of years. Discerning use of MT is therefore a powerful tool for mineral exploration.

North America, South America

The MTPy software package for magnetotelluric data analysis and visualisation

The magnetotelluric (MT) method is increasingly being applied to a wide variety of geoscience problems. However, the software available for MT data analysis and interpretation is still very limited in comparison to many of the more mature geophysical methods such as the gravity, magnetic or seismic reflection methods. MTPy is an open source Python package to assist with MT data processing, analysis, modelling, visualization and interpretation. It was initiated at the University of Adelaide in 2013 as a means to store and share Python code amongst the MT community (Krieger & Peacock, 2014). Here we provide an overview of the software and describe recent developments to MTPy. These include new functionality and a clean up and standardization of the source code, as well as the addition of an integrated testing suite, documentation, and examples in order to facilitate the use of MT in the wider geophysics community.

Journal of Open Source Software