The magnetotelluric (MT) method is increasingly being applied to map tectonic architecture and mineral systems. Under the Exploring for the Future (EFTF) program, Geoscience Australia has invested significantly in the collection of new MT data. The science outputs from these data are underpinned by an open-source data analysis and visualisation software package called MTPy. MTPy started at the University of Adelaide as a means to share academic code among the MT community. Under EFTF, we have applied software engineering best practices to the code base, including adding automated documentation and unit testing, code refactoring, workshop tutorial materials and detailed installation instructions. New functionality has been developed, targeted to support EFTF-related products, and includes data analysis and visualisation. Significant development has focused on modules to work with 3D MT inversions, including capability to export to commonly used software such as Gocad and ArcGIS. This export capability has been particularly important in supporting integration of resistivity models with other EFTF datasets. The increased functionality, and improvements to code quality and usability, have directly supported the EFTF program and assisted with uptake of MTPy among the international MT community. <b>Citation:</b> Kirkby, A.L., Zhang, F., Peacock, J., Hassan, R. and Duan, J., 2020. Development of the open-source MTPy package for magnetotelluric data analysis and visualisation. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

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 and 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 standardisation 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.

The Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP) aims to collect long period magnetotelluric data on a half degree (~55 km) grid across the Australian continent. New datasets have been collected in Northern Australia, as part of Geoscience Australia’s Exploring for the Future (EFTF) program with in-kind contributions from the Northern Territory Geological Survey and the Geological Survey of Queensland. This web service depicts the location of the 155 sites which were used in this study.

The Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP) aims to collect long period magnetotelluric data on a half degree (~55 km) grid across the Australian continent. New datasets have been collected in Northern Australia, as part of Geoscience Australia’s Exploring for the Future (EFTF) program with in-kind contributions from the Northern Territory Geological Survey and the Geological Survey of Queensland. This web service depicts the location of the 155 sites which were used in this study.

This animation shows how Magnetotelluric (MT) Surveys Work. It is part of a series of Field Activity Technique Engagement Animations. The target audience are the communities that are impacted by our data acquisition activities. There is no sound or voice over. The 2D animation includes a simplified view of what magnetotelluric (MT) stations and equipment looks like what the equipment measures and how the survey works.

The under-cover geology of the southern Thomson Orogen in north-western New South Wales and south-western Queensland is largely unknown due to the extensive, up to 600 m thick Cenozoic and Mesozoic cover. This cover (mainly consisting of Eromanga Basin and Lake Eyre Basin rocks) results in very restricted basement outcrop, with a subsequent lack of understanding of subsurface lithologies, structures and the potential for the location of economic resources. As a result, this area was selected for a regional, multi-disciplinary project (the Southern Thomson Project) by Geoscience Australia and its State partners the Geological Survey of New South Wales and the Geological Survey of Queensland. The Project reflects the focus of the UNCOVER Initiative (Australian Academy of Science 2012) that aims to form the basis for Australia's potential future discovery and development of new economic mineral resources. The Southern Thomson Project involves many geoscientific disciplines including geophysics, geochronology, geochemistry and stratigraphy to better understand the region and promote mineral exploration by reducing exploration risk. This report focuses on some of the initial reconnaissance and pre-drilling geophysical data collected in 2014 - in particular gravity data, AEM (Airborne Electromagnetics) and MT (Magnetotellurics) along two regional north-south traverses, and a shorter east-west traverse in the northern part of the region. The major aim of this study is to compare AEM and MT electrical conductivity data acquired along these traverses, and integrate them with interpretation of available deep seismic reflection data to generate a series of 2D geological models, which can be tested via forward gravity modelling and subsequent density inversions. This integrative approach allows for a more robust understanding of the crustal architecture and cover thickness (or depth to basement) variations in the Southern Thomson region. The main findings of this report are: 1) Cover thicknesses of 0 to >500 m were initially estimated along various traverses through a combination of AEM and MT data interpretation as well as existing data from drill holes and water bores. Most datasets yield broadly similar results in terms of relative cover thickness variations, although AEM cannot be reliably used when cover thickness is greater than ~150 m due to limitations in the Depth Of Investigation (DOI), and Broadband MT (BBMT) tends to overestimate cover thickness where it is known to be less than 50 m. Cover thickness estimates using MT methods (especially AMT - Audio-frequency Magnetotellurics) agree with other datasets such as existing drill holes/water bores, GABWRA (Great Artesian Basin Water Resource Assessment; Ransley and Smerdon 2012) depth to basement results, and targeted high-resolution ground geophysical surveys (Goodwin et al. in prep). On this regional scale, AMT likely provides the most suitable resolution for estimating cover thicknesses of 0 - 1000 m. 2) Cover thicknesses estimated by AEM and MT conductivity sections have been tested by forward gravity modelling and produce better matches with the observed gravity responses compared to an averaged, uniform cover thickness. This observation shows cover thickness variations can produce discernible variations in gravity responses and need to be taken into account in gravity modelling. Further, this supports the use of a combined approach in using AEM, MT and gravity models to asses cover thickness variations over a broad region. 3) Several alternative interpretations of deep seismic reflection data along the southern part of one of the regional MT traverses (Line 3) were performed to assess crustal architecture. These were tested by forward gravity modelling with subsequent inversions (allowing modelled bodies' density to vary) producing a close match between the observed and modelled gravity responses with reasonable geological densities of crustal units given the limited known and/or inferred rock properties in this region. 4) Two-dimensional (2D) cross-section models along each line were generated by integrating the recent interpretation of basement geology (Purdy et al. 2014) with AEM and MT conductivity sections. These models were tested via forward gravity modelling and subsequent inversions (allowing modelled bodies' density to vary). This approach showed that the most accurate model was a thickened crust north of the Olepoloko Fault (the Southern Thomson region). 5) Many of the 2D forward models produced reasonable matches between the observed and calculated (modelled) gravity responses with respect to the large scale crustal architecture and location of prominent resistive bodies (inferred as felsic igneous intrusions) observed in MT conductivity sections. However, gravity inversions sometimes produced unrealistic densities of crustal units given the (limited) known rock properties in this region. Despite these limitations, the simplistic 2D forward models provide a good starting point for future refinement as more geological, geophysical, geochemical and petrophysical data become available.