Design of optimal gas drainage and gas management programs throughout the mining cycle is contingent upon a thorough understanding of the gas emission mechanisms specific to the geological and operational conditions in a particular location. As mining progresses from exploration, through development and into production, the resolution of data typically used for gas emission prediction improves spatially and with respect to time. Quantification and management of risk associated with sudden gas release during mining (outbursts) and accumulation of noxious or combustible gases within the mining environment is reliant on gas emission prediction, which is spatially relevant and applicable to the mining stage being undertaken. Using iterative spatial interpolation techniques, appropriate resolution gas emission model input data may be used to continually improve both the resolution and accuracy of model outputs and also determine triggers where model recalculation is required. Proposed techniques are validated through a case study of gas core samples obtained from two southern Sydney basin mines producing metallurgical coal from the Bulli seam over a period of 10 years. Alignment of data in various geospatial and extraction time-based context, including relationships to hydrological features and geological structures, combined with experimental results assessing the influence of changes in confining stress and gas pressure, appear to align with modelled outputs and recent historical gas emission data. The results suggest variability and limitations associated with the present traditional approaches to gas emission prediction and design of gas management practices may be addressed using predictions derived from improved spatial datasets, and analysis techniques incorporating fundamental physical and energy related principles.
Patrick Booth, Heidi Brown, Jan Nemcik and Ting Ren, Determination of Gas Emission in the Mining Life Cycle, Proceedings of the 18th Coal Operators' Conference, Mining Engineering, University of Wollongong, 273-283.