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A Statistical Method to Assess the Data Integrity and Reliability of Seismic Monitoring Systems in Underground Mines

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Abstract

Data integrity and reliability during seismic event detection are the main factors limiting the effectiveness of seismic monitoring systems in underground mines. As it is impossible for current seismic monitoring systems to record all mining-induced seismic events, the incomplete seismic dataset may cause significant bias during data analyses and interpretation processes. Evaluation of seismic data integrity in mine seismology and eliminate its impact on seismic analyses is a critical issue that needs to be addressed. Therefore, this paper presents the results of a study that investigated the characteristics of seismic data and its integrity by assessing the event detection probability of the seismic monitoring system in an underground coal mine. The wave picking capacities of individual geophones are first evaluated, and the detection probabilities for seismic events within a specific monitoring area are then calculated. The results showed that geophones presented different wave picking capacities for seismic events at various locations and energy magnitudes: a larger event detection probability and a broader detection range is observed for higher energy seismic events. A method to correct seismic data is also proposed to improve the completeness of the recorded seismic data, which provides more information on the frequencies of seismic events than the raw data. This paper enhances the method of assessing seismic data reliability and improving the accuracy of seismic analyses in underground mines.

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References

  • Cai W, Dou L, Si G, Cao A, Gong S, Wang G, Yuan S (2019) A new seismic-based strain energy methodology for coal burst forecasting in underground coal mines. Int J Rock Mech Min Sci 123:104086

    Article  Google Scholar 

  • Cao A, Dou L, Wang C, Yao X, Dong J, Gu Y (2016) Microseismic precursory characteristics of rock burst hazard in mining areas near a large residual coal pillar: a case study from Xuzhuang Coal Mine, Xuzhou, China. Rock Mech Rock Eng 49:4407–4422

    Article  Google Scholar 

  • Cao W, Shi J, Si G, Durucan S, Korre A (2018) Numerical modelling of microseismicity associated with longwall coal mining. Int J Coal Geol 193:30–45. https://doi.org/10.1016/j.coal.2018.04.010

    Article  Google Scholar 

  • Cao A, Gao SS (2002) Temporal variation of seismic b-values beneath northeastern Japan island arc. Geophys Res Lett 29:48-41-48–43

    Article  Google Scholar 

  • D’Alessandro A, Luzio D, D’Anna G, Mangano G (2011) Seismic network evaluation through simulation: an application to the Italian National Seismic Network. Bull Seismol Soc Am 101:1213–1232

    Article  Google Scholar 

  • Falmagne V (2002) Quantification of rock mass degradation using micro-seismic monitoring and applications for mine design. PhD thesis, Queen's University

  • Gibowicz SJ, Kijko A (1994) An introduction to mining seismology, vol 55. Polish Academy of Sciences, Poland

    Book  Google Scholar 

  • Gibowicz SJ, Lasocki S (2001) Seismicity induced by mining: Ten years later. Adv Geophys 44:39–181

    Article  Google Scholar 

  • Glazer S (2018) Mine seismology: seismic warning concept. Springer

    Book  Google Scholar 

  • Godano C (2017) A new method for the estimation of the completeness magnitude. Phys Earth Planet Inter 263:7–11

    Article  Google Scholar 

  • Gutenberg B, Richter C (1944) Frequency of earthquakes in California. B Seismol Soc Am 34:185–188

    Article  Google Scholar 

  • Hudyma MR (2008) Analysis and interpretation of clusters of seismic events in mines. University of Western Australia

    Google Scholar 

  • Ishimoto M (1936) Observations of earthquakes registered with the microseismograph constructed recently. Bull Earthquake Res Inst Univ Tokyo 17:443–478

    Google Scholar 

  • Kaiser PK, Maloney SM (1997) Scaling laws for the design of rock support. In: T S (ed) Seismicity associated with mines, reservoirs and fluid injections, vol 2–3. Springer, pp 415–417

    Chapter  Google Scholar 

  • Liu J-p, Feng X-t, Li Y-h, Sheng Y (2013) Studies on temporal and spatial variation of microseismic activities in a deep metal mine. Int J Rock Mech Min Sci 60:171–179

    Article  Google Scholar 

  • Mendecki AJ (1996) Seismic monitoring in mines. Chapman & Hall, London

    Book  Google Scholar 

  • Mendecki AJ (2016) Mine seismology reference book: seismic hazard. Institute of Mine Seismology

    Google Scholar 

  • Mignan A, Werner M, Wiemer S, Chen C-C, Wu Y-M (2011) Bayesian estimation of the spatially varying completeness magnitude of earthquake catalogs. B Seismol Soc Am 101:1371–1385

    Article  Google Scholar 

  • Ogata Y, Katsura K (1993) Analysis of temporal and spatial heterogeneity of magnitude frequency distribution inferred from earthquake catalogues. Geophys J Int 113:727–738

    Article  Google Scholar 

  • Schorlemmer D, Woessner J (2008) Probability of detecting an earthquake. B Seismol Soc Am 98:2103–2117

    Article  Google Scholar 

  • Si G, Durucan S, Jamnikar S, Lazar J, Abraham K, Korre A, Shi J-Q, Zavšek S, Mutke G, Lurka A (2015) Seismic monitoring and analysis of excessive gas emissions in heterogeneous coal seams. Int J Coal Geol 149:41–54

    Article  Google Scholar 

  • Si G, Cai W, Wang S, Li X (2020) Prediction of relatively high-energy seismic events using spatial–temporal parametrisation of mining-induced seismicity. Rock Mech Rock Eng 53:5111–5132

  • Wang C-l, Wu A-x, Liu X-h, Li R (2009) Study on fractal characteristics of b value with microseismic activity in deep mining. Earth Planet Sci Lett 1:592–597

    Article  Google Scholar 

  • Wang C, Cao A, Zhang C, Canbulat I (2019) A new method to assess coal burst risks using dynamic and static loading analysis. Rock Mech Rock Eng 53:1113-1128

    Google Scholar 

  • Wang C, Si G, Zhang C, Cao A, Canbulat I (2021) Location error based seismic cluster analysis and its application to burst damage assessment in underground coal mines. Int J Rock Mech Min Sci 143:104784

    Article  Google Scholar 

  • Wesseloo J (2014) Evaluation of the spatial variation of b-value. J S Afr I Min Metall 114:823–828

    Google Scholar 

  • Wiemer S, Wyss M (2000) Minimum magnitude of completeness in earthquake catalogs: examples from Alaska, the western United States, and Japan. B Seismol Soc Am 90:859–869

    Article  Google Scholar 

  • Woessner J, Wiemer S (2005) Assessing the quality of earthquake catalogues: estimating the magnitude of completeness and its uncertainty. B Seismol Soc Am 95:684–698

    Article  Google Scholar 

  • Woodward KR, Tierney SR (2017) Seismic hazard estimation using databases with bimodal frequency–magnitude behaviour. In: M Hudyma & Y Potvin (eds) Proceedings of the first international conference on underground mining technology. Australian Centre for Geomechanics, pp 219–232

  • Zhang C, Canbulat I, Hebblewhite B, Ward CR (2017) Assessing coal burst phenomena in mining and insights into directions for future research. Int J Coal Geol 179:28–44. https://doi.org/10.1016/j.coal.2017.05.011

    Article  Google Scholar 

  • Zúñiga FR, Wyss M (1995) Inadvertent changes in magnitude reported in earthquake catalogs: Their evaluation through b-value estimates. B Seismol Soc Am 85:1858–1866

    Article  Google Scholar 

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Acknowledgements

The first author would like to acknowledge the financial support of the China Scholarship Council–UNSW, Sydney Project (no. 201706420062).

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Correspondence to Chengguo Zhang.

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Wang, C., Si, G., Zhang, C. et al. A Statistical Method to Assess the Data Integrity and Reliability of Seismic Monitoring Systems in Underground Mines. Rock Mech Rock Eng 54, 5885–5901 (2021). https://doi.org/10.1007/s00603-021-02597-7

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  • DOI: https://doi.org/10.1007/s00603-021-02597-7

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