b'AEM 2023Short abstractsof apparent resistivity on the frequency of the signal. The classicSelf-Organizing Map (SOM) classifications, and Supervised Deep approach to modelling IP consists in deriving analytical modelsNeural Network (SDNN) targeting of the geophysical data. The of frequency dependent resistivity of each layer of the model.new targeting approach has further reduced the number of However, the number of parameters for such models growspriority targets from previous five (5) to three (3), which includes fast with the number of layers. Hence the problem of numericalmost of the known epithermal Au-Ag occurrences, as well as inversion becomes intractable due to high dimensionality andtwo areas for follow-up.ill conditioning.This work suggests an approach to overcoming this problem.ZTEM Airborne Natural Field EM-Magnetics and mineral We show that the effects of IP are concentrated in relativelytargeting results over the Berg Porphyry Copper small number of layers and propose a simple algorithm forProject, near Houston, British Columbia.finding them. The results of inverting real data showing strong IP are presented. Jean M Legault and Karl KwanGeotech Ltd., Aurora, ON, CanadaThoughts on layered inversions A ZTEM natural field helicopter EM and magnetic survey was Andrew King flown over the Berg copper-molybdenum-silver project in the Huckleberry district, near Houston in central British Columbia, CSIRO, Kensington, WA, Australia Canada. Mineralisation at Berg surrounds a quartz monzonite The earth is composed of layers of rock of different lithology,intrusion. Analyses of the airborne geophysical responses, with sharp boundaries between them, so surely it is better tousing 2D-3D inversions, show combined well-defined ring-use layered AEM models than smooth models? However, thislike resistivity low surrounding a resistive core and similar idealised cartoon model is complicated by the fact that mostannular magnetic high and low signatures over the known and electrical conductance is through pore water of varying salinitysuspected porphyry deposits, similar to those previously found rather than through the rock matrix, and by factors, such asin ZTEM surveys over other porphyry deposits in the Western weathering gradients, which will induce gradients in physicalCordillera. A mineral targeting approach is implemented that properties. This paper discussed experiences with trying to useuses a semi-automated, machine-learning (ML) assisted method layered, rather than smooth, inversions of AEM data. that includes: Structural Complexities (SC), Self-Organizing Map (SOM) classifications, and Supervised Deep Neural Network (SDNN) targeting of the geophysical data. The new targeting Targeting epithermal Au-Ag using helicopter TDEM,approach has identified both the Berg and Bergette porphyry magnetic, and radiometric data at Lawyers Project,copper occurrences, as well as two others our areas for follow-North-Central BC, Canada. up that also host known mineral showings.Jean M Legault and Karl Kwan Reconciling the previously incompatible through the Geotech Ltd., Aurora, ON, Canada continental scale AusAEM surveyIn September 2018, Geotech Ltd. completed a VTEM helicopterA.Yusen Ley-Cooper, Ross R Brodie, Anandaroop A Ray and Neil time-domain electromagnetic, magnetic and radiometricSymingtonsurvey on behalf of Benchmark Metals Inc. over the Lawyers property, in northcentral BC. The magnetic results reveal aGeoscience Australia, Symonston, ACT, Australiastrong spatial relationship between sharp magnetic lineamentsGeoscience Australia (GA) has acquired hundreds of thousands and the known mineralisation. Radiometric results show thatof line-km of airborne electromagnetic (AEM) data over mineralisation is characterised by hydrothermal alterationthe years to better understand the Australian subsurface. A resulting in potassium enrichment, manifested as K/Th highs.more recent planned approach of acquisition has been the The VTEM electromagnetic results identified local EM anomaliesAusAEM programme. This systematic effort has delivered representing both discrete and structural conductors. However,extensive detailed conductivity-depth-models over large none of the EM anomalies making up conductive zonesswaths of land. This effort will deliver a continental-scale, coincide with the known epithermal mineralisation, instead alllong lasting geophysical dataset. Simultaneously, GAs in-the known Au-Ag deposits and occurrences are located in zoneshouse processing and inversion codes enable the seamless of high apparent resistivity. integration of conductivity models from both helicopter and Subsequent analysis of the VTEM data analysed using AIIPfixed wing systems, compatibility of X and Z component data mapping revealed that all the known Au-Ag mineralised zonesfrom the same survey, as well as the reconciliation of historical coincide with moderate to high Cole-Cole time constant (TAU)and recent datasets. Of particular note, is the reprocessing anomalies, consistent with relatively coarse-grained polarisableof data using the magnitude of the measured magnetic field material, such as disseminated sulphides or hydrothermallyin the plane of the inline flight direction. It deals with many altered clays. transmitter-receiver geometry problems and leads to glitch-free subsurface images. GAs efforts in advancing the modelling The previous targeting approach focused on individual analysesand inversion codes have verified the presence of geological of magnetic, structural, radiometric, EM resistivity and AIIPunits at deeper depths in stratigraphic sequences than we results, then arriving at a targeting model, based on geologicallywere able to resolve pre-2016. The concerted development of and geophysically based considerations. A new approacha strategic acquisition programme together with modelling for targeting uses a semi-automated, machine-learning (ML)and inversion codes have allowed us to stitch together a nearly assisted approach that includes: Structural Complexities (SC),continent-wide dataset59 PREVIEW AUGUST 2023'