Extension of the CGA Maceral Chemistry Database and Development of Optical Mineral Markers

CSIRO have developed an optical reflected light imaging and analysis system (Coal Grain Analysis) which provides reflectance and composition information on individual coal particles.  A feature of this system is that colour images, collected with an air objective, are mosaiced together to enable detailed (micron level) information to be obtained on particle sizes up to 4mm.

This project is an extension of ACARP project C20040 'Improved Understanding of Coal Exploration Samples by Coal Grain Analysis' but also has a second goal to extend the CGA system's capability to provide detail on coal minerals.

During ACARP project C20040 this system was used to develop and validate correlations between maceral chemistries and maceral reflectance for a suite of six Australian coals from different coal measures.  These results showed that for a similar mean random maceral reflectance value, the inertinite contains less carbon and more oxygen than does the vitrinite.  The inertinite and vitrinite constituents which have similar reflectance values came from coals of different rank, the inertinite material was a component of a lower rank coal.  The hydrogen, nitrogen and volatile matter contents for both the vitrinite and inertinite maceral groups decreased as maceral reflectance increased.

For this project an additional 6 Australian coking coals were analysed using a similar methodology.  This has increased the total number of samples for which we have maceral chemistry information to 12, which is a sufficient number to make a meaningful assessment of the link between maceral reflectance and maceral chemistry.

For coking coals whole coal reflectogram data has been used to develop models which predict the performance of single coals and coal blends during coking (Gupta et al., 2012).  At this stage we are unclear what implications these differences in carbon content and volatile matter between vitrinite and inertinite with the same reflectance may have for using whole coal reflectogram data for predicting coking behaviour.

To investigate whether there are differences in the relationships between maceral reflectance and maceral chemistry for coals from different Australian coal measures or basins, the 12 coals which have been studied were grouped into three general regions which were the Rangals/Baralaba coal measures, the German Creek/Goonyella coal measures and the Newcastle/Illawarra coal measures.  These results suggested that the trends which were observed between maceral reflectance and maceral chemistry were not coal measure specific.  This suggests that observed differences in coking performance between coals from these coal measures are not due to differences in maceral chemistry but may however be due to other factors such as differences in mineralogy or in the coal structure/texture of the individual particles of coal after crushing to produce coke oven feed.  

The second project goal was to modify the CGA system capabilities to provide detail on coal minerals.  This built on the findings from a previous CSIRO study which established that many of the minerals present in coking coals have colour reflectance fingerprints which allow them to be identified in optical reflected light images.

This information is considered to have most benefit to understanding the deleterious effect that some minerals have during coke making as it enables size information and mineral maceral associations to be determined.  CGA results are also used quite extensively for the assessment of exploration samples.  Mineral maceral association information obtained for these samples would assist in assessing liberation and determining whether specific minerals, such as apatite, calcite and siderite, which can affect coking coal performance during utilisation, are likely to preferentially report to the product coal or to rejects.

The CGA software is currently undergoing a significant upgrade so that it can report these details and other recent developments.  Integration of mineral species and maceral chemistry information into the CGA processing software will enable an estimate of chemical properties and mineral species abundance and size information to be made for each individual particle.