ArticlePloS one2025
Rock physics-based approach to assess the effectiveness of cement-based backfill materials in coal mining.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Coal production for energy generation results in series of ecological and environmental degradation in mining areas. backfilling of goafs is considered as a suitable method for the mitigation of aforementioned problems. Being economical, sustainable and safe to use for filing voids, supporting ground and managing the waste, cemented paste backfill (CPB) is the best choice for underground mining. However, the prediction of mechanical and elastic properties of CPB based on varying composition and curing time always remain a complex and difficult job. Traditional empirical studies although advantageous are tedious, lengthy and incapable to incorporate important aspects of geo-mechanical instabilities of backfill materials. In current study, a numerical approach is applied to simulate and evaluate the compressional (Vp) and shear (Vs) wave velocities, along with Vp/Vs ratio of CPB materials with varying flyash and biochar concentration at different curing intervals (3, 7, 14, 21 and 28 days). By applying a rock physics model, the proposed methodology offers a unique way to examine the effect of curing time and compositional variation on the elastic wave properties of CPB, ultimately offer insights into the internal structure and strength development over time. Simulation outcomes show that a high concentration of flyash and low concentration of biochar exhibit best elastic responses, with high Vp, Vs and low Vp/Vs ratio serving as precise indicator of materials mechanical integrity and heterogeneity. Eventually this study provides a time-efficient, cost-effective, and non-destructive method to analyze multiple backfill compositions in situations where laboratory work is lacking. Furthermore, this study promotes the use of rock-physics modeling at preliminary stage of material evaluation, with emphasizing its utility, productivity, and capability to enhance prediction precision in geo-mechanical investigations.
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