Callide Coalfields produces a sub-bituminous, very subhydrous, low rank, steaming coal with good combustion properties, primarily for domestic power generation. Geological input into planning of coal extraction requires expedient production of detailed structural, lithological, analytical, geophysical and geotechnical data. The CSIRO-developed SIROLOG borehole logging software and hardware system allows for detailed spectrometric analysis of coal/interburden. The gamma-gamma and neutron-gamma SIROLOG techniques both provide improved prediction of ash content over other borehole techniques. The neutron-gamma technique also predicts density and some important ash constituents (especially iron, alumina and silica). The software/hardware configuration allows for quick, easy interpretation of coal seam depth and lithology, parting thickness and ash/ash constituent contents immediately after a borehole has been logged. Within certain mine areas in the Callide Basin, the iron content of mined coal is widely variable in both vertical and lateral extent within and between seams. This variability creates problems in predicting the slagging behaviour of as-received' coal during combustion, especially where the iron content of the ash exceeds 19 per cent. Using the SIROLOG tool in co-operation with traditional borehole sample laboratory analysis results, patterns in this variability can be determined and related to geological properties and process of formation of the coal seams. Subsequently, areas of high iron can be predicted in advance of mining. Since 1992, on-going collection and interpretation of SIROLOG downhole geophysical log data has significantly contributed to a number of research projects related to gaining a preliminary understanding of the iron distribution and formation during the Coal Measures' deposition. Because the probe was able to record variations in coal mineral matter content, it was found to complement more conventional techniques such as reflected light petrography, X-Ray Diffraction and SEM techniques that examine the mineralogy of iron species. Additionally, software has been developed to allow integration of SIROLOG data into existing geology databases, enhancing coal quality modelling and daily prediction of parameters such as raw ash, silica and iron contents that are indicators of ash fusion propensity. The correlation of SIROLOG-derived iron geophysical traces between drillholes and other sample points highlighted lithological and structural controls in the iron distribution in the sequence previously not detected. This work has allowed the development of a methodology for predicting iron in advance of mining and reconciling as-sold coal quality to that predicted. Predictions are currently being assessed at the coal face as mining progresses through high-iron zones.