THE NATIONAL GEOCHEMICAL SURVEY OF AUSTRALIA: BACKGROUND AND PROGRESS

Australia lacks a complete geochemical data coverage, but this is being addressed through an ambitious project – the National Geochemical Survey of Australia (NGSA) – which was launched by Geoscience Australia in January 2007. Such a dataset informs on the concentrations and distributions of chemical elements in the near-surface environment.

Building on methods developed during precursor pilot projects, NGSA targets catchment outlet (overbank) sediments as a uniform sampling medium. A shallow and a deeper level are being collected in 1390 catchments covering 91% of the country. Sampling is carried out by State and Northern Territory geoscience agencies following protocols described in a detailed Field Manual and practiced during in-field training; all equipment and consumables are provided centrally. Dry and moist Munsell colours, soil pH, digital photographs and GPS coordinates are recorded in the field.

In the laboratory, these transported, fine-grained regolith materials are dried and a split is archived for future use. Electrical conductivity and pH of 1:5 (soil:water) slurries, laser particle size distribution and infrared spectroscopy are measured on the remaining split. This split is further sieved into two grain-size fractions (<2 mm and <75 μm) for analysis by x-ray fluorescence (XRF), inductively-coupled mass spectrometry (ICP-MS) after total digestion (multi-element) as well as after aqua regia digestion (multi-element, including low level gold), and by specialised methods for platinum group elements, fluorine and selenium. All procedures are documented in a detailed Sample Preparation Manual.

As at July 2009, 80% of the samples have been collected and most analyses have been completed for the first 50% of these samples. Some preliminary results will be outlined.

The project will contribute fundamental knowledge to the energy and mineral resources exploration industry by its completion in June 2011. This pre-competitive knowledge, used in combination with other datasets, can reduce exploration cost/risk by helping target more detailed activities. Spin-offs into other applications are also expected.