b'AEGC 2021Short abstractsLoupe is a backpack-portable, two-person, time-domain285: Reversible jump sequential Monte Carlo for model electromagnetics (TEM) system that uses a Slingraminference of airborne Induced Polarisationconfiguration to allow resistivity sounding data to be collected continuously at walking pace. The signals from the receiverMr Laurence Davies 1, Dr Alan Yusen Ley-Cooper2, Prof coils are carried to the transmitter via an umbilical cable thatChristopher Drovandi1 and Dr Matthew Sutton1also serves to maintain a set distance between the receiver and transmitting antennae. At a typical walking speed of 5 km/ 1 Queensland University of Technologyhr, data are collected at ~3 m intervals. Data are typically2 Geoscience Australiawindowed into 22 approximately logarithmically-spacedExact methods of Bayesian model selection require exhaustive window intervals, ranging from ~6 sec to ~2.3 msec aftercomputation of normalising constants or sampling of the transmitter shutoff. The data were inverted using Aarhusinv in ajoint posterior of parameters and models via reversible jump 12 layer smooth-model configuration. Markov chain Monte Carlo (RJMCMC). Until recently, the latter has been favoured in geophysics applications where there Examination of the inverted data suggests that it is unlikelyis a mid-to-high cardinality of the set of candidate models. that there is a sizeable conductive plume originating fromHowever, RJMCMC schemes alone do not easily lend themselves the northwest in this data set (based on the expectationto parallel computing. The focus of this talk is to explore the that there might still be conductive contaminant still in thepotential efficiencies of cross-dimensional proposals within groundwater, from the old plant and landfill sites). There arethe embarrassingly parallelisable static Sequential Monte Carlo intriguing conductive features in the data that are worth(SMC) class of algorithms as applied to parameter and model investigating although these may be related to natural saltinference in electrical properties of the Earth. Of particular accumulation along the river, as is seen at other sites alonginterest is the detection of induced polarisation effects in the river. airborne electromagnetic data. Advantages of this approach will be investigated numerically in a simulation study followed by an application to real data.281: Constraining regional-scale groundwater transport predictions using multiple geophysical techniques 286: Helicopter airborne Electromagnetics at low base frequencies - Western Australia case studiesDr Michael Hatch, Prof Graham Heinson1, Mr Ben Kay1, Mr Chris Li2 and Ms Rebecca Doble2 Dr Adam Smiarowski 11 School of Physical Sciences, University of Adelaide 1 CGG Multi-Physics2 CSIROLow-base frequency ( less than 25 Hz) airborne electromagnetic It is becoming more common to incorporate geophysicalsurveying has only been available for a few years. The data sets in groundwater models, thereby not just relying onadvantages are longer measuring time to better discriminate often spatially sparse data from traditional geohydrologicalstrong conductors and to see through conductive cover, as techniques. Not only are the geophysical data sets usuallywell as utilising a long time-duration transmitter to better spatially far less sparse, but they can often be collectedenergise strong conductors. Low base frequency AEM is more non-invasively. A disadvantage is that there may be nodifficult because of increased sensitivity to system motion/consistent/obvious link between the geophysical datarotation noise and fewer available stacks. For strong conductors, and properties that the groundwater model is simulating.the extra signal from the wider pulse available with low-base It is therefore necessary to derive coupling relationshipsfrequency more than compensates for the reduction in stacking. between the geophysical data and the underlyingA comparison of field data from a 30 Hz and 7.5 Hz system hydrogeology. This is usually performed in a deterministicshowed significantly better detection to a conductive body at manner and the uncertainty inherent in the geophysical400 m depth with the low-base frequency system. Here, we data (as well as in the coupling) is rarely incorporated.show a case study from a graphite exploration survey using In this study we collect a number of geophysical data12.5 Hz data. The low-base frequency AEM data provides better sets, including audio-frequency magnetotellurics (AMT),definition of a known mineralization zone and identifies areas time&checkhyphenorendash;domain electromagnetics (TEM)with further mineralization potential. The AEM data show and nuclear magnetic resonance (NMR), and then bydistinct anomalies over graphite-rich zones and agreed with combining these information sets with scattered and sparsedepths to mineralization from drilling.hydrological measurements, the geophysical information can be coupled with other data in a stochastic groundwater298: The role of mine waste in the fight against climate modelling framework. These geophysical techniques providechangeconstraints on hydraulic conductivity, water table depth, hydrostratigraphy and porosity. When using geophysicalDr Anita Parbhakar-Fox 1data as parameters in groundwater model inversion, it is1 W.H.Bryan Geology and Mining Centre, Sustainable Minerals critical to quantify and account for their uncertainty toInstitute, The University of Queenslandavoid incorrectly biasing model outcomes. This study shows how this can be achieved using an ensembler-smootherThe global response to climate change, initiated by the Paris modelling method incorporating PESTPP-IES. This approachAgreement, has been to encourage countries to transition is illustrated using geophysical and hydrological data fromto low-carbon economies. New technologies such as electric Kapunda, South Australia, to evaluate the impact of avehicles, low-emission power sources and products for the simulated In-Situ Recovery (ISR) copper mining operation. medical and defence sectors are required to support this. 111 PREVIEW AUGUST 2021'