Numerical modelling of microseismicity associated with longwall coal mining
Численное моделирование микросейсмичности, связанной с разработкой угольных пластов длинными забоями
2018-04-23
SCID: 54.1/y73h84tg
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FLAC3Ddiscrete fracture networkfracture slip seismicitylongwall coal miningmicroseismicity modelling
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Abstract (AI)
Microseismicity has long been a precursor for underground mining hazards such as rockbursts and coal and gas outbursts. In this research, a methodology combining deterministic stress and failure analysis and stochastic fracture slip evaluation, based upon the widely accepted fracture slip seismicity-generation mechanism, has been developed to simulate microseismic events induced by longwall mining. Using the built-in DFN facility in FLAC3D, discrete fractures following a power law size distribution are distributed throughout a 3D continuum model in a probabilistic way to account for the stochastic nature of microseismicity. The DFN-based modelling approach developed was adopted to simulate the evolution of microseismicity induced by the progressive face advance in a longwall top coal caving (LTCC) panel at Coal Mine Velenje, Slovenia. At each excavation step, global stress and failure analysis with reference to the strain-softening post-failure behaviour characteristic of coal, and fracture slip evaluation for microseismicity are conducted sequentially. The model findings are compared to the microseismic event data recorded during a long-term field monitoring campaign conducted at the same LTCC panel. It was found that the released energy and frequency-magnitude distribution of microseismicity are associated with the slipped fracture sizes and fracture size distribution. These features for recorded microseismic events were fairly constant until a xylite rich heterogeneous zone ahead of the working face was approached, which indicates that fractures within the extracted coal seam follow the same size distribution. The features obtained from modelled microseismic events were consistent over the production period, and matched well the field observations. Furthermore, the model results indicate that the power law fracture size distribution can be used to model longwall-mining-induced microseismicity. This model provides a unique prospective to understand longwall coal mining-induced microseismicity and lays a foundation to predict microseismicity, or even rockburst potential in specific geological realisations.
Key Findings
1
A coupled deterministic stress-failure and stochastic fracture-slip methodology was developed to simulate microseismicity induced by progressive longwall mining.
2
Observed microseismic characteristics remained broadly constant until the working face approached a xylite-rich heterogeneous zone, supporting a common fracture-size distribution within the extracted coal seam.
3
Released seismic energy and frequency-magnitude distributions were linked to slipped-fracture sizes and their distribution.
4
Simulations of a longwall top coal caving panel at Coal Mine Velenje reproduced microseismic evolution during progressive face advance and matched field observations well.
5
The FLAC3D discrete-fracture-network model represents fractures probabilistically using a power-law size distribution, accounting for the stochastic nature of microseismic events.
6
The results indicate that power-law fracture-size distributions are suitable for modelling longwall-mining-induced microseismicity.
Research Object
microseismicity induced by progressive face advance in a longwall top coal caving (LTCC) coal-mining panel
Research Subject
the relationship of released energy and frequency–magnitude distribution to slipped fracture sizes and their power-law distribution during longwall mining
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2018-04-23
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