The middle to lower Jurassic sequence in Australia's Surat Basin has been identified as a potential reservoir system for geological CO2 storage. The sequence comprises three major formations with distinctly different mineral compositions, and generally low salinity formation water (TDS<3000 mg/L). Differing geochemical responses between the formations are expected during geological CO2 storage. However, given the prevailing use of saline reservoirs in CCS projects elsewhere, limited data are available on CO2-water-rock dynamics during CO2 storage in such low-salinity formations. Here, a combined batch experiment and numerical modelling approach is used to characterise reaction pathways and to identify geochemical tracers of CO2 migration in the low-salinity Jurassic sandstone units. Reservoir system mineralogy was characterized for 66 core samples from stratigraphic well GSQ Chinchilla 4, and six representative samples were reacted with synthetic formation water and high-purity CO2 for up to 27 days at a range of pressures. Low formation water salinity, temperature, and mineralization yield high solubility trapping capacity (1.18 mol/L at 45°C, 100 bar), while the paucity of divalent cations in groundwater and the silicate reservoir matrix results in very low mineral trapping capacity under storage conditions. Formation water alkalinity buffers pH at elevated CO2 pressures and exerts control on mineral dissolution rates. Non-radiogenic, regional groundwater-like 87Sr/86Sr values (0.7048-0.7066) indicate carbonate and authigenic clay dissolution as the primary reaction pathways regulating solution composition, with limited dissolution of the clastic matrix during the incubations. Several geochemical tracers are mobilised in concentrations greater than found in regional groundwater, most notably cobalt, concentrations of which are significantly elevated regardless of CO2 pressure or sample mineralogy.

This GA Record report is one of a series of 4 reports undertaken by the GA Groundwater Group under the National Collaboration Framework Project Agreement with the Office of Water Science (in the Department of the Environment). The report was originally submitted to the OWS in July 2013, and subsequently reviewed by Queensland government. The Maryborough Basin in Queensland is a priority coal-bearing sedimentary basin that is not currently slated for Bioregional Assessment.

This GA Record is one of a series of 4 reports completed by the GA Groundwater Group under the National Collaboration Framework Project Agreement with the Office of Water Science (Dept of the Environment). The report was originally submitted to OWS as a GA Professional Opinion, and was subsequently reviewed by Queensland government. The Laura Basin in north Queensland is a priority coal-bearing sedimentary basin that is not currently slated for Bioregional Assessment.

The Severe Wind Hazard Assessment for Queensland - SWHA(Q), is a collaborative project between Geoscience Australia (GA) and Queensland Fire and Emergency Services (QFES) which aims to provide realistic and tangible information on the potential physical impacts of tropical cyclones on Queensland communities. This is intended to enable the emergency management sector and Local Governments to more effectively engage with the community on the current and future risks posed by cyclones and inform long term strategic risk management strategies.

<p>Geoscience Australia (GA) generated a series of gravity and magnetic grids and enhancements covering Northern Australia. Several derivative gravity datasets have been generated 1) for the North-West Shield Western Australia region (approximately between latitudes 7‒26⁰ S and longitudes 110‒130⁰ E), 2) for the Northern Territory (approximately between latitudes 7‒26⁰ S and longitudes 125.5‒141⁰ E) and for Queensland (approximately between latitudes 7‒30⁰ S and longitudes 135‒160⁰ E). The magnetic dataset has been generated only for the North-West Shield Western Australia region (approximately between latitudes 7‒26⁰ S and longitudes 110‒130⁰ E). The magnetic and gravity data were downloaded from the Geophysical Archive Data Delivery System (GADDS), website (http://www.geoscience.gov.au/cgi-bin/mapserv?map=/nas/web/ops/prod/apps/mapserver/gadds/wms_map/gadds.map&mode=browse). Satellite Free-air (FA) gravity v27.1 (released March 11, 2019) and Satellite Topography v19.1 (released January 14, 2019) data were sourced from Sandwell et al. (2014) and downloaded from the Scripps Institution of Oceanography (SIO), National Oceanic and Atmospheric Administration (NOAA), U.S. Navy and National Geospatial-Intelligence Agency (NGA) (SIO Satellite Geodesy, website, http://topex.ucsd.edu/WWW_html/mar_grav.html). The Satellite Bouguer gravity grid with onshore correction density of 2.67 gcm-3 and offshore correction density of 2.20 gcm-3 was derived from the Free-air gravity v27.1 and Topography data V19.1. This Bouguer gravity grid was used for filling areas of data gaps in the offshore region. <p>Data evaluation and processing of gravity and magnetic data available in the area of interest resulted in the production of stitched onshore-offshore Bouguer gravity grid derived from offshore satellite Bouguer gravity grid and GA’s onshore ground and airborne gravity survey data and a stitched Total Magnetic Intensity (TMI) grid derived from airborne and shipborne surveys (Tables 1 and 5). A Reduction to the Pole (RTP) grid was derived from the stitched TMI grid. The TMI, RTP, FA and terrain corrected Bouguer gravity anomalies are standard datasets for geological analysis. The free-air gravity anomaly provides the raw and basic gravity information. Images of free-air gravity are useful for first-pass interpretation and the data is used for gravity modelling. Magnetic anomalies provide information on numerous magnetic sources, including deep sources as arising from the structure and composition of magnetic basement and shallow sources such as intra-sedimentary magnetic units (e.g. volcanics, intrusions, and magnetic sedimentary layers). A standard TMI image will contain information from all these sources. Geosoft Oasis montaj software was used throughout the data processing and enhancement procedure and the montaj GridKnit module was used to generate the stitched gravity and magnetic grids. <p>Enhancement techniques have been applied to the final processed Bouguer gravity and RTP magnetic grids to highlight subtle features from various sources and to separate anomalies from different source depths. These enhancement techniques are described in the next section. <p>Enhancement processing techniques and results <p>A summary of image processing techniques used to achieve various outcomes is described in Table 1. <p>Data type Filter applied Enhancement/outcome <p>Gravity/Magnetic First vertical derivative (1VD) Near surface features (e.g. intrabasinal) <p>Gravity/Magnetic Upward continuation Noise reduction in data <p>Gravity/Magnetic Low pass filter, or large distance upward continuation Enhancement of deep features (e.g. basement) <p>Gravity/Magnetic High pass filter Enhancement of shallow features (e.g. surface anomalies) <p>Gravity/Magnetic Tilt filter and 1VD Enhancement of structure (e.g. in basement) <p>Gravity/Magnetic ZS-Edgezone and ZS-Edge filters Enhancement of edges <p>Gravity/Magnetic horizontal modulus / horizontal gradient Enhancement of boundaries <p>Magnetic RTP (reduction to the pole), Compound Anomaly, and Analytic Signal filter Accurate location of sources

This grid dataset is an estimation of the relative surface potential for recharge within the McBride Basalt Province. This process combined numerous factors together as to highlight the areas likely to have higher potential for recharge to occur. Soil permeability and surface geology are the primary inputs. Vegetation and slope were excluded from consideration, as these were considered to add too much complexity. Furthermore, this model does not include rainfall intensity – although this is known to vary spatially through average rainfall grids, this model is a depiction of the ground ability for recharge to occur should a significant rainfall event occur in each location. The relative surface potential recharge presented is estimated through a combination of soil and geological factors, weighting regions that are considered likely to have greater potential for recharge (e.g. younger basalts, vent-proximal facies, and highly permeable soils). Near-surface permeability of soil layers has been considered as a quantified input to the ability for water to infiltrate soil strata. It was hypothesised that locations proximal to volcanic vents would be preferential recharge sites, due to deeply penetrative columnar jointing. This suggestion is based on observations in South Iceland, where fully-penetrating columnar joint sets are more prevalent in proximal facies compared to distal facies in South Iceland (Bergh & Sigvaldson 1991). To incorporate this concept, preferential recharge sites are assumed to be within the polygons of vent-proximal facies as derived from detailed geological mapping datasets. Remaining geology has been categorised to provide higher potential recharge through younger lava flows. As such, a ranking between geological units has been used to provide the variation in potential recharge estimates. <b>References</b> Bergh, S. G., & Sigvaldason, G. E. (1991). Pleistocene mass-flow deposits of basaltic hyaloclastite on a shallow submarine shelf, South Iceland. Bulletin of Volcanology, 53(8), 597-611. doi:10.1007/bf00493688

The Upper Burdekin Chloride Mass Balance Recharge web service depicts the recharge rates have been estimated at borehole locations in the Nulla and McBride basalt provinces. Using rainfall rates, rainfall chemistry and groundwater chemistry, the recharge rates have been estimated through the Chloride Mass Balance approach.

This dataset includes point estimates of groundwater recharge in mm/year. Recharge rates have been estimated at monitoring bore locations in the basaltic aquifers of the Nulla and McBride basalt provinces. Recharge estimates have been calculated using the “chloride mass balance” method. The chloride mass balance process assumes that the chloride ion is a conservative tracer in precipitation, evapotranspiration, recharge and runoff; and that all the chloride is from rainfall, instead of for example halite saturation or dissolution processes. So the volumetric water balance and the flux of chloride balance must both be true. Assuming that runoff and evapotranspiration are negligible (so approximated by zero), the equation is simplified: Water balance P=ET+R+Q Water balance multiplied by chloride concentrations (chloridefluxbalance) P∙Cl_ppt=ET∙Cl_ET+R∙Cl_gw+Q∙Cl_riv | ΔCl_reac≈0 Assumptions to simplify equation P∙Cl_ppt=R∙Cl_gw | Q≈0 & ET≈0 Rearranging for recharge rate (unknown) R=P∙(Cl_ppt)/(Cl_gw ) | Q≈0 & ET≈0 Where P = precipitation rate; ET = evapotranspiration rate; R = recharge rate; Q = runoff to streams; Clppt = concentration of Cl in precipitation; ClET = concentration of chloride in evapotranspiration; Clgw = concentration of Cl in groundwater; Clriv = concentration of chloride in river runoff; ΔClreac = change in chloride concentrations from reactions.

This service provides Estimates of Geological and Geophysical Surfaces (EGGS). The data comes from cover thickness models based on magnetic, airborne electromagnetic and borehole measurements of the depth of stratigraphic and chronostratigraphic surfaces and boundaries.

The Great Artesian Basin Research Priorities Workshop, organised by Geoscience Australia (GA), was held in Canberra on 27 and 28 April 2016. Workshop attendees represented a spectrum of stakeholders including government, policy, management, scientific and technical representatives interested in GAB-related water management. This workshop was aimed at identifying and documenting key science issues and strategies to fill hydrogeological knowledge gaps that will assist federal and state/territory governments in addressing groundwater management issues within the GAB, such as influencing the development of the next Strategic Management Plan for the GAB. This report summarises the findings out of the workshop.