This report presents the results of scanning electron microscopy (SEM) analyses on 2 core samples from the GSWA Waukarlycarly 1 stratigraphic well drilled in the Canning Basin. The well was drilled as part of a co-funded collaboration between Geoscience Australia (GA) and the Geological Survey of Western Australia (GSWA) aimed at gathering new subsurface data on the potential mineral, energy and groundwater resources in the southern Canning Basin. The collaboration resulted in the acquisition of the Kidson Deep Crustal Seismic Reflection Survey in 2018; and the drilling of deep stratigraphic well GSWA Waukarlycarly 1, located along the Kidson Sub-basin seismic line within the Waukarlycarly Embayment in 2019 (Figure 1). GSWA Waukarlycarly 1 reached a total depth of 2680.53 m at the end of November 2019 and was continuously cored through the entire Canning Basin stratigraphy. Coring was complemented by the acquisition of a standard suite of wireline logs and a vertical seismic profile. The work presented in this report constitutes part of the post well data acquisition. The purpose of the SEM analysis was to determine mineralogy and textural relationships between grains, verify the presence of organic material at the micro-scale, document i) the presence of diagenetic alterations to the detrital mineral assemblage and ii) eventual distribution of visible pores.

<div>Geoscience Australia maintains a national collection of marine geological samples and analytical data from across the Australian region. Digital records of these datasets are held within the Marine Sediment Database (MARS), available as an online resource of c. 2.6 million entries. Here we have extracted data from MARS to collate sediment properties for over 15,000 seabed samples for use as a standalone dataset. Analytical data includes textural composition (mud, sand, gravel), summary statistics for particle size distributions, textural class and calcium carbonate values (where available). Information on sample water depth, location and marine survey is also provided. The sample set spans the coast, continental shelf, slope and deep ocean locations across the Australian marine region (covering the extent of the AusBathyTopo 250m 2023 grid). This dataset has utility for a broad range of purposes including seabed characterisation, sediment transport modelling, habitat characterisation, seabed engineering studies and fundamental geological and sedimentological research.</div><div><br></div><div>Additional metadata of this dataset are provided in the word document accompanied with the dataset. The metadata document describes the attribute table, the sediment carbonate classification and the sediment facies.</div>

This resource contains a predicted seabed mud content grid for the greater Darwin Harbour region as part of a baseline seabed mapping program of Darwin Harbour and Bynoe Harbour. This project was funded through offset funds provided by an INPEX-led Ichthys LNG Project to the Northern Territory Government's Department of Environment and Natural Resources (NTG-DENR) with co-investment from Geoscience Australia (GA) and the Australian Institute of Marine Science (AIMS). The intent of this program is to improve knowledge of the marine environments in the Darwin and Bynoe Harbour regions by collating and collecting baseline data that enable the creation of thematic habitat maps and information to underpin marine resource management decisions. The predicted seabed mud content grid was derived from a compilation of multiple surveys undertaken by GA, AIMS and NTG-DENR between 2011 and 2017, including GA0333 (Siwabessy et al., 2015), GA0341 (Siwabessy et al., 2015), GA0351/SOL6187 (Siwabessy et al., 2016), GA4452/SOL6432 (Siwabessy et al., 2017), GA0356 (Radke et al., 2017), and GA0358 and GA0359 (Radke et al., 2018), adding to those from a previous survey GA0333 collected by GA, AIMS and NTG-DENR. This dataset provides spatially continuous predictions of seabed %mud (< 63 µm) content for the Darwin and Bynoe harbour region, northern Australian marine margin. Data are presented in 10 m resolution raster grids format and ascii text file. Predictions are based on 395 samples and nine environmental variables derived from high resolution multibeam sonar bathymetry and backscatter data. Accuracy of predictions is very high, with a VEcv = 62% for mud; and the predictive accuracy has been increased by 198.3% for mud in comparison with the commonly used method (i.e., IDW). Absences in predictions occur in this dataset as a result of non-availability associated with predictive variables. This dataset supersedes previous predictions of mud content for the Darwin and Bynoe harbour region with demonstrated improvements in predictive accuracy.