b'AEGC 2023Short abstractscomes under scrutiny. These data sets have been used to checkzinc. The mineral potential maps were derived from mineral the older methods named above, so a comparison of methodssystems concepts through the development of mappable spatial is provided. Also, to investigate the robustness of the method,proxies of the theoretical mineral system components. These noise is added to the synthetic dataset and the results arewere then combined using a knowledge-driven approach to considered with the other methods. highlight areas where favourable criteria for these systems are spatially coincident. In addition to the potential for hosting the Geothermal study using modeling of magnetotelluriccopper or lead-zinc mineralisation, the potential for these mineral systems as a resource for critical minerals such as germanium, data: A case study from the Sabalan region, Iran. gallium, and indium as recoverable by- or co-products has Fatemeh Firoozi1 and Abolghasem Kamkar-Rouhani2 been examined. Where possible, each output mineral potential map was then validated using spatial statistics to demonstrate 1 Isfahan University of Technologyefficacy in the prediction of known mineralisation. The six 2 Shahrood University of Technology mineral potential maps utilise large volumes of pre-competitive geoscience data to reduce the exploration search space for This research aims to examine subsurface structures in Sabalansediment-hosted deposits and highlight areas of elevated geothermal region, northwest of Iran using three-dimensionalprospectivity in under-explored regions of Australia.(3-D) modeling of magnetotelluric (MT) data. For this, we have used MT data of 24 stations from 28 stations acquired along 6 survey lines in the northwest part of the region, namely MoeilDistal, proximal and sweet-spot: limitations in source valley. These MT data have been acquired by EDC in 2007.information content of magnetic field data.Since the real earth has three dimensions, 3-D inversion has obvious advantages over two-dimensional (2-D) inversion, andClive Foss and James Austintherefore, we have used 3-D inversion of MT data to obtain aCSIRO 3-D electrical image of the subsurface structures of the region. In this research work, WSINV3DMT code has been employedWe propose that unconstrained inversion estimates of for 3-D inversion of the acquired MT data. As a result, apparentmagnetisation are only justified from segments of data in which resistivity and phase cross-sections have been obtained.that magnetisation is the dominant source of curvature of the Furthermore, dimensionality analysis of the MT data has beenfield. At moderate to large separations from a magnetisation (in carried out by using polar diagrams of the impedance tensor.a distal field) measurements can be acceptably matched with The results of this dimensionality analysis indicate that shallowa dipole model to provide estimates of total magnetisation subsurface structures can be considered as one-dimensional(magnetic moment including direction) and its centre (x,y,z) (1-D) or 2D structures, however, deep structures should bebut not its distribution about that centre. Closer to the considered as 3-D structures. After preparing the modelmagnetisation (in a proximal field) where a dipole model does parameters and designing the suitable modeling blocks, 3-Dnot acceptably explain the field variation it may be feasible to Occams inversion of the MT data has been made. The locationestimate aspects of the spatial distribution of magnetisation of the geothermal reservoir in the region is determined frombut with reduced confidence in its total magnetic moment and the results of the 3-D Occams inversion. Moreover, the resultscentre. Field variations due to inhomogeneous magnetisation of the 3-D inversion of the MT data have been compared withcan be explained with homogeneous magnetisation models the results of the 2-D models, and then, the results have beenup to the point that the inhomogeneity causes an additional interpreted using geological information from the region. Fromcurvature feature in the data. At that point the magnetic field the interpretation results of this study, we have found that thecan be explained as due to multiple internally homogeneous geothermal reservoir is located at the depth of 800 to 2562 m. magnetisations or multiple magnetic moments. Each curvature feature in the magnetic field supports estimation of a single Sediment-hosted mineral potential mapping ofhomogeneous magnetisation (with caveats of non-uniqueness ubiquitous with solution of the inverse problem). We call these Australia: Geoscience data integration for national- samples of the field data sweet-spots. Magnetic field data which scale assessment. is not part of a sweet-spot does not provide useful information about the distribution of magnetisation. Space filling (voxel) Arianne Ford, Jonathan Cloutier, David Huston and Michaelmagnetisation models can be found which are acceptably Doublier consistent with complete magnetic field data sets but these are Geoscience Australia only tested at the sweet-spots in the data. We illustrate these limitations with examples of sweet-spot inversions of both distal Integration of high-quality digital geoscience data using aand proximal field data.mineral systems-based mineral potential mapping approach supports: 1) improved understanding of the key processes that have shaped Australias geology and concentrated its resources;Regional mapping of the disruption of source 2) insights into how big data can be transformed into predictivemagnetisation estimates by near-surface power. Sediment-hosted mineral systems are important tomagnetisations.understand as they represent potential opportunities for both the base metals and critical minerals that are vital to deliveringClive Foss 1 and Jackie Hope2Australias low carbon economy. To support this goal, the mineral1 CSIRO potential of six sediment-hosted mineral systems has been2 Geoscience Australiaevaluated in this project: sediment-hosted stratiform copper, Isa-type copper, siliciclastic mafic lead-zinc, siliciclastic carbonateMuch of Australia is covered with regional magnetic field lead-zinc, Irish-type lead-zinc, and Mississippi Valley-type lead- surveys. In both the primary magnetic line data and derived 97 PREVIEW FEBRUARY 2023'