f Challenges in Integrating AEM and Borehole Geophysical and Hydrogeological Information to Produce Maps of Hydrogeological Properties and Tectonics

In this study, the SkyTEM system was used to map key functional elements of the hydrogeological system critical to the identification and assessment of managed aquifer recharge (MAR) sites and potential groundwater resource targets. A suite of customized interpretation products were produced through integration of AEM data with data from 60 sonic-cored holes and 40 new rotary mud and. Data obtained from this program drilling includes: sedimentary facies, textures (including grain size), mineralogy, redox state and whole rock geochemistry; hydrogeophysical data (nuclear magnetic resonance (NMR), induction and gamma logs); hydraulic data (from slug and pump tests), hydrochemistry (from groundwater and porefluid samples), and hydrodynamic data from the monitoring of groundwater levels in 40 boreholes pre- and post-flooding in 2010-2011. Customised interpretation products developed through integration of these datasets include: maps of the sedimentary system including palaeochannels with favourable hydraulic properties; hydrostratigraphy; confining aquitards; textural classes within the sedimentary system; tectonic elements; zones of inter-aquifer leakage and groundwater flow pathways; groundwater salinity, aquifer transmissivity; MAR storage volumes; and groundwater storage estimates in various water quality classes (0-600; 600-1200; and 1200-3000 mg/L). The products were integrated with other datasets (including time series vegetation condition, surface geomorphology, flood inundation) for MAR risk assessments of various options and targets, with a priority target identified and positively assessed. Volume estimates for fresh, acceptable and brackish groundwater stored within discrete targets was particularly challenging due to the hydrogeological complexity. The methodology used relied upon a multi-scale approach. Salinity class thresholds were estimated by comparing the pore fluid data with the AEM response. Bulk volumes for each water quality class in a target were then calculated using these thresholds on an AEM depth slice basis, which had been mapped into textural classes. Gravimetric water and textural data from sonic cores were compared with borehole NMR data and laboratory effective porosities (from Lexan-encapsulated core) to estimate an effective porosity range for each textural class. These were used to convert the depth-slice bulk volume estimates to stored groundwater volumes. Sensitivity analysis revealed that there are significant uncertainties in volume estimates using this approach. There can be orders of magnitude differences in volume calculation depending on the AEM inversions used, with significant variations also found depending on the salinity thresholds used, and the uncertainties linked to the effective porosity estimation. This study has demonstrated the importance of selecting the most appropriate AEM system and optimizing the AEM inversions for generating a wide range of customized interpretation products. For estimating groundwater quality and volumes, there are large uncertainties due to the inherent issues with individual measurement methods, compounded by integration, scaling and extrapolation issues. Such mapping and estimates of groundwater salinity and volumes are still useful guides, but ultimately, the assessment of groundwater resources identified using these datasets requires numerical groundwater and solute transport modeling . Such modeling is needed to determine the duration and rates of supply possible from the identified targets, and to assess potential environmental and resource impacts from prolonged extraction during drought conditions.