Underground mining-induced subsidence is responsible for damages to built features, assets, surface and underground water resources, and other environmental features. The ability to predict and manage the effects of underground longwall coal mining on ground surface is deemed necessary for coal mining companies to seek approval from regulatory organisations. This ability is particularly important in cases where higher magnitudes of subsidence and extents of damage to ground surface are expected, such as multi-seam longwall mining-induced subsidence. By reducing the number of untouched coal resources, the number of multi-seam coal mines has increased to meet today's energy requirement. This increase has brought new challenges to mine subsidence engineers as the observed subsidence above multi-seam coal mines indicate significantly different subsidence characteristics in comparison with that of single-seam mining. Multi-seam subsidence observations suggest that there is a different strata movement mechanism involved in the multi-seam mining, which is yet to be fully understood. In addition, the multi-seam mining-induced subsidence is a case dependent phenomenon and currently available subsidence predictive methodologies are unable to account for this case dependency of the multi-seam subsidence to achieve reliable subsidence predictions. The aim of this study is to first investigate strata movement mechanism and ground surface subsidence characteristics resulting from multi-seam longwall mining extractions and then, at the second stage, use the results of this investigation to characterise and develop a reliable multi-seam subsidence predictive methodology. For this purpose, several investigation methods are utilised, such as physical and numerical modelling techniques and factual subsidence observational data analysis. The key finding from these investigations was that multi-seam mining configuration, i.e. relative location of the longwall panels in the two mining seams and interburden thickness, is the most influential factor that alters the strata movement pattern and shape of the multi-seam subsidence. Extraction of lower longwall panel from under previously extracted longwall panels creates specific strata movement patterns and areas of fracture closure/opening above the previously extracted upper mining seam, depending on the multi-seam mining configuration. Closure of cracks and reduced bridging ability of the previously caved strata result in enhanced magnitude of subsidence above overlapping areas of longwall panels in the two mining seams. Existence of previously disturbed and caved areas also alters the strata movement pattern and subsidence characteristics above the edges of the lower panels. It was found that where edges of the longwall panels are vertically aligned in the two mining horizons a steep and concentrated subsidence profile forms above the edge of the lower panel. In contrast, where lower panel's edge is located under the previously extracted upper panel a smooth and wide subsidence profile occurs. At the next stage, results from different investigation methods were used to characterise the multi-seam subsidence. For this purpose and to avoid generalisation of the multi-seam subsidence, it was suggested to divide the extracted lower panel into a number of segments with different segmental subsidence parameters in accordance with the relative location of the panels in the mining seams. By this method, multi-seam subsidence due to any mining configuration can be characterised. The proposed characterisation was then employed to modify a conventional subsidence prediction method, namely, Influence Function Method (IFM). The modified method is called Discrete Influence Function Method (Discrete-IFM). This method is based on superpositioning of subsidence influence from extracted discrete segments with different subsidence parameters, which together form the extracted longwall panel, to calculate the final multi-seam subsidence profile. The outstanding advantage of the Discrete-IFM in comparison with other conventional subsidence prediction methods is its ability to predict subsidence profile of any shape and magnitude for every multi-seam mining configuration. Finally, the ability of the Discrete-IFM to predict multi-seam subsidence profiles was demonstrated in a multi-seam mine case study. For this purpose, the Discrete-IFM was first calibrated by two control cases. The multi-seam subsidence in other locations was then predicted by means of the calibrated method. The prediction results by Discrete-IFM were also compared with selected commonly used prediction methods. This comparison results indicated improved ability of the Discrete-IFM to predict the multi-seam subsidence and its specific characteristics due to various multi-seam mining configurations. The findings presented in this study would enable mining engineers to determine the extent of the multi-seam subsidence. The proposed conceptualised characterisation of the subsidence can be used to reliably predict the multi-seam subsidence due to various mining configurations and evaluate the impact of multi-seam mining on the ground surface.
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