Rock Mechanics and Rock Engineering

, Volume 52, Issue 1, pp 183–197 | Cite as

Distribution Characteristics of Mining-Induced Seismicity Revealed by 3-D Ray-Tracing Relocation and the FCM Clustering Method

  • Zewei WangEmail author
  • Xibing Li
  • Xueyi Shang
Original Paper


Induced seismicity in underground mining zones reflects inner changes of the rock structure caused by human activities, thus providing potential information for hazard assessment. Precise hypocenter parameters and magnitudes of the induced micro-earthquakes as well as their spatial distributions are essential for understanding the seismicity. We first accurately relocate 834 micro-earthquakes recorded by a 28-sensor micro-seismic monitoring system from an underground phosphate mine, using an iterative pseudo-bending ray-tracing method and a 3-D velocity structure obtained by seismic tomography. We then determine the local magnitudes of the events by a well-recalibrated formula, and finally analyze the seismicity for different parts of the mine divided by the fuzzy c-means clustering method according to the spatial distribution of the micro-earthquakes. The bimodal distribution of the recalibrated local magnitudes indicates two fundamentally different processes of rock failure may exist in the mine. They are possibly fracture-dominated rupture and friction-dominated slip, i.e., tensile failure and shear failure of the surrounding rock. The clustering result shows that mining practices cause very different seismic features in different parts of the mine. Furthermore, we find that most of the large events are located in low-V zones, and that events occurred in the lower velocity zones tend to have a correspondingly larger magnitude, as revealed by the seismicity analysis and seismic tomography.


Induced seismicity Underground mine Three-dimension ray-tracing Relocation Local magnitude Fuzzy c-means (FCM) clustering method 

List of Symbols


The observed travel time from the ith event to the jth station (s)


The calculated travel times from the ith event to the jth station (s)


The hypocenter parameters of ith event in the Cartesian coordinates (m)


The occurrence time of ith event (s)


The perturbation of a parameter


The velocity at the nth node of the 3-D grid (m/s)


Error terms

\(\left( {\frac{{{\text{d}}x}}{{{\text{d}}s}},\frac{{{\text{d}}y}}{{{\text{d}}s}},\frac{{{\text{d}}z}}{{{\text{d}}s}}} \right)\)

Components of the unit vector tangent to the ray path at the hypocenter and pointing in the direction of ray propagation


Velocity at the hypocenter (m/s)


The parameter of path length (m)


Maximum ground displacement measured at the station (nm)


Distance from the station to the source (km)


Constant representing geometrical spreading


Constant representing attenuation


Constant term to adjust the magnitude value within a reasonable range


Station correction term


The membership value of ith event to jth cluster


The distance from ith event to the center of jth cluster


Fuzzy parameter


The center of jth cluster


Number of events


Number of clusters


Probability distribution function



This work was supported by Grants (nos. 41430213, 41590863 and 41630642) from the National Natural Science Foundation of China, and Grant (no. 2018M633224) from China Postdoctoral Science Foundation. The free software GMT (Wessel and Smith 1998) was used for making the figures in this study. We are very grateful to Professor Giovanni Barla (Editor in Chief), Professor Ian Main and an anonymous referee for their thoughtful review comments and suggestions which have improved this paper.


  1. Akaike H (1973) Information theory and an extension of the maximum likelihood principle. In: 2nd International symposium on information theory, Tsahkadsor, Armenia, USSR, September 2–8, 1971, Budapest: Akadémiai Kiadó, pp 267–281Google Scholar
  2. Bagh S, Alhasan A, Tello S (2014) Local magnitude calibration of the Syrian National Digital Seismological Network. Seismol Res Lett 85:324–333. CrossRefGoogle Scholar
  3. Benetatos C, Málek J, Verga F (2013) Moment tensor inversion for two micro-earthquakes occurring inside the Háje gas storage facilities, Czech Republic. J Seismol 17:557–577. CrossRefGoogle Scholar
  4. Bezdek JC, Ehrlich R, Full W (1984) FCM: the fuzzy c-means clustering algorithm. Comput Geosci 10:191–203CrossRefGoogle Scholar
  5. Cai W, Dou L, Cao A, Gong S, Li Z (2014) Application of seismic velocity tomography in underground coal mines: a case study of Yima mining area Henan, China. J Appl Geophys 109:140–149. CrossRefGoogle Scholar
  6. Davis SD, Frohlich C (1991) Single-link cluster analysis, synthetic earthquake catalogues, and aftershock identification. Geophys J Int 104:289–306CrossRefGoogle Scholar
  7. Dong L, Li X (2013) A microseismic/acoustic emission source location method using arrival times of PS waves for unknown velocity system. Int J Distrib Sens Netw 9:307489. CrossRefGoogle Scholar
  8. Dong L, Wesseloo J, Potvin Y, Li X (2016) Discriminant models of blasts and seismic events in mine seismology. Int J Rock Mech Min Sci 86:282–291. CrossRefGoogle Scholar
  9. El-Isa ZH, Eaton DW (2014) Spatiotemporal variations in the b-value of earthquake magnitude–frequency distributions: classification and causes. Tectonophysics 615:1–11. CrossRefGoogle Scholar
  10. Finnie GJ (1999) Using neural networks to discriminate between genuine and spurious seismic events in mines. Pure Appl Geophys 154:41–56. CrossRefGoogle Scholar
  11. Fischer AD, Peng Z, Sammis CG (2008) Dynamic triggering of high-frequency bursts by strong motions during the 2004 Parkfield earthquake sequence. Geophys Res Lett 35:150–152. CrossRefGoogle Scholar
  12. Ge M (2005) Efficient mine microseismic monitoring. Int J Coal Geol 64:44–56. CrossRefGoogle Scholar
  13. Haney F, Kummerow J, Langenbruch C, Dinske C, Shapiro SA, Scherbaum F (2011) Magnitude estimation for microseismicity induced during the KTB 2004/2005 injection experiment. Geophysics 76:WC47–WC53CrossRefGoogle Scholar
  14. Holland AA (2013) Earthquakes triggered by hydraulic fracturing in South-Central Oklahoma. Bull Seismol Soc Am 103:1784–1792. CrossRefGoogle Scholar
  15. Hua Y, Zhao D, Xu Y (2017) P wave anisotropic tomography of the Alps. J Geophys Res Solid Earth 122:4509. CrossRefGoogle Scholar
  16. Hung MC, Yang DL (2001) An efficient fuzzy C-means clustering algorithm. In: IEEE international conference on data mining, pp 225–232Google Scholar
  17. Hutton LK, Boore DM (1987) The ML scale in Southern California. Bull Seismol Soc Am 77:2074–2094Google Scholar
  18. Jennings PC, Kanamori H (1983) Effect of distance on local magnitudes found from strong motion records. Bull Seismol Soc Am 73:265–280Google Scholar
  19. Jordan TH, Chen YT, Gasparini P, Madariaga R, Main IG, Marzocchi W, Papadopoulos G, Sobolev G, Yamaoka K, Zschau J (2011) Operational earthquake forecasting. State of knowledge and guidelines for utilization. Ann Geophys 54:361–391Google Scholar
  20. Keir D, Stuart GW, Jackson A, Ayele A (2006) Local earthquake magnitude scale and seismicity rate for the Ethiopian rift. Bull Seismol Soc Am 96:2221–2230CrossRefGoogle Scholar
  21. Kijko A, Graham G (1998) Parametric-historic procedure for probabilistic seismic hazard analysis part I: estimation of maximum regional magnitude mmax. Pure Appl Geophys 152:413–442. CrossRefGoogle Scholar
  22. Kijko A, Lasocki S, Graham G (2001) Non-parametric seismic hazard in mines. Pure Appl Geophys 158:1655–1675. CrossRefGoogle Scholar
  23. Kılıç T, Ottemöller L, Havskov J, Yanık K, Kılıçarslan Ö, Alver F, Özyazıcıoğlu M (2017) Local magnitude scale for earthquakes in Turkey. J Seismol 21:35–46. CrossRefGoogle Scholar
  24. Li X, Weng L (2016) Numerical investigation on fracturing behaviors of deep-buried opening under dynamic disturbance. Tunn Undergr Space Technol 54:61–72. CrossRefGoogle Scholar
  25. Li X, Shang X, Wang Z, Dong L, Weng L (2016a) Identifying P-phase arrivals with noise: an improved Kurtosis method based on DWT and STA/LTA. J Appl Geophys 133:50–61. CrossRefGoogle Scholar
  26. Li X, Wang Z, Dong L (2016b) Locating single-point sources from arrival times containing large picking errors (LPEs): the virtual field optimization method (VFOM). Sci Rep 6:19205. CrossRefGoogle Scholar
  27. Li X, Shang X, Morales-Esteban A, Wang Z (2017) Identifying P phase arrival of weak events: the Akaike Information Criterion picking application based on the Empirical Mode Decomposition. Comput Geosci 100:57–66. CrossRefGoogle Scholar
  28. Lolli B, Gasperini P, Mele FM, Vannucci G (2015) Recalibration of the distance correction term for local magnitude (ML) computations in Italy. Seismol Res Lett 86:1383–1392. CrossRefGoogle Scholar
  29. Lu C, Dou L, Zhang N, Xue J, Wang X, Liu H, Zhang J (2013) Microseismic frequency-spectrum evolutionary rule of rockburst triggered by roof fall. Int J Rock Mech Min Sci 64:6–16. CrossRefGoogle Scholar
  30. Mohd-Nordin MM, Song K-I, Cho G-C, Mohamed Z (2014) Long-wavelength elastic wave propagation across naturally fractured rock masses. Rock Mech Rock Eng 47:561–573. CrossRefGoogle Scholar
  31. Mutke G, Pierzyna A, Baranski A (2016) b-Value as a criterion for the evaluation of rockburst hazard in coal mines. In: 3rd Int symp mine saf sci eng, pp 1–5Google Scholar
  32. Naoi M, Nakatani M, Horiuchi S, Yabe Y, Philipp J, Kgarume T, Morema G, Khambule S, Masakale T, Ribeiro L, Miyakawa K, Watanabe A, Otsuki K, Moriya H, Murakami O, Kawakata H, Yoshimitsu N, Ward A, Durrheim R, Ogasawara H (2014) Frequency–magnitude distribution of − 3.7 ≤ M W ≤ 1 mining-induced earthquakes around a mining front and b value invariance with post-blast time. Pure Appl Geophys 171:2665–2684. CrossRefGoogle Scholar
  33. Ottemöller L, Sargeant S (2013) A local magnitude scale ML for the United Kingdom. Bull Seismol Soc Am 103:2884–2893. CrossRefGoogle Scholar
  34. Paap B, Steeghs P (2016) Calibration of a local magnitude relationship for microseismic events using earthquake data. Geophysics 81:KS123–KS132CrossRefGoogle Scholar
  35. Peng K, Li X, Wang Z (2015) Hydrochemical characteristics of groundwater movement and evolution in the Xinli deposit of the Sanshandao gold mine using FCM and PCA methods. Environ Earth Sci 73:1–16. CrossRefGoogle Scholar
  36. Richardson E, Jordan TH (2002) Seismicity in deep gold mines of South Africa: implications for tectonic earthquakes. Bull Seismol Soc Am 92:1766–1782. CrossRefGoogle Scholar
  37. Richter CF (1935) An instrumental earthquake magnitude scale. Bull Seismol Soc Am 25:1–32Google Scholar
  38. Roberts NS, Bell AF, Main IG (2015) Are volcanic seismic b-values high, and if so when? J Volcanol Geotherm Res 308:127–141CrossRefGoogle Scholar
  39. Schwarz GE (1978) Estimating the dimension of a model. Ann Stat 6:461–464CrossRefGoogle Scholar
  40. Si S, Tian X, Gao R (2017) Constraints on upper mantle Vp/Vs ratio variations beneath eastern North China from receiver function tomography. J Asian Earth Sci 138:341–356. CrossRefGoogle Scholar
  41. Simmons G (1964) Velocity of compressional waves in various minerals at pressures to 10 kilobars. J Geophys Res 69:1117–1121. CrossRefGoogle Scholar
  42. Simpson DW (1976) Seismicity changes associated with reservoir loading. Eng Geol 10:123–150. CrossRefGoogle Scholar
  43. Stiros SC, Kontogianni VA (2009) Coulomb stress changes: from earthquakes to underground excavation failures. Int J Rock Mech Min Sci 46:182–187. CrossRefGoogle Scholar
  44. Suzuki K, Oda M, Kuwahara T, Hirama K (1995) Material property changes in granitic rock during long-term immersion in hot water. Eng Geol 40:29–39. CrossRefGoogle Scholar
  45. Thurber CH (1983) Earthquake locations and three-dimensional crustal structure in the Coyote Lake Area, central California. J Geophys Res Solid Earth 88:8226–8236. CrossRefGoogle Scholar
  46. Um J, Thurber C (1987) A fast algorithm for two-point seismic ray tracing. Bull Seismol Soc Am 77:972–986Google Scholar
  47. Van Eijs RMHE, Mulders FMM, Nepveu M, Kenter CJ, Scheffers BC (2006) Correlation between hydrocarbon reservoir properties and induced seismicity in the Netherlands. Eng Geol 84:99–111. CrossRefGoogle Scholar
  48. Vinciguerra S, Trovato C, Meredith PG, Benson PM (2005) Relating seismic velocities, thermal cracking and permeability in Mt. Etna and Iceland basalts. Int J Rock Mech Min Sci 42:900–910. CrossRefGoogle Scholar
  49. Wang Z, Zhao D, Liu X, Chen C, Li X (2017a) P and S wave attenuation tomography of the Japan subduction zone. Geochem Geophys Geosyst 18:1688–1710. CrossRefGoogle Scholar
  50. Wang Z, Zhao D, Liu X, Li X (2017b) Seismic attenuation tomography of the source zone of the 2016 Kumamoto earthquake (M 7.3). J Geophys Res Solid Earth 122:2988–3007. CrossRefGoogle Scholar
  51. Wang J, Main IG, Musson RMW (2017c) Earthquake clustering in modern seismicity and its relationship with strong historical earthquakes around Beijing, China. Geophys J Int 211:1027–1040Google Scholar
  52. Weng L, Huang L, Taheri A, Li X (2017) Rockburst characteristics and numerical simulation based on a strain energy density index: a case study of a roadway in Linglong gold mine, China. Tunn Undergr Space Technol 69:223–232. CrossRefGoogle Scholar
  53. Wessel P, Smith WHF (1998) New, improved version of generic mapping tools released, Eos. Trans Am Geophys Union 79:579–579. CrossRefGoogle Scholar
  54. Xie XL, Beni G (1991) A validity measure for fuzzy clustering. IEEE Trans Pattern Anal Mach Intell 13:841–847CrossRefGoogle Scholar
  55. Xu N, Li T, Dai F, Li B, Zhu Y, Yang D (2015) Microseismic monitoring and stability evaluation for the large scale underground caverns at the Houziyan hydropower station in Southwest China. Eng Geol 188:48–67. CrossRefGoogle Scholar
  56. Yao Y, Wang Q, Liao W, Zhang L, Chen J, Li J, Yuan L, Zhao Y (2017) Influences of the Three Gorges Project on seismic activities in the reservoir area. Sci Bull 62:1089–1098. CrossRefGoogle Scholar
  57. Zhao D, Hasegawa A, Horiuchi S (1992) Tomographic imaging of P and S wave velocity structure beneath northeastern Japan. J Geophys Res 97:19909–19928. CrossRefGoogle Scholar
  58. Zhou J, Li X, Shi X (2012) Long-term prediction model of rockburst in underground openings using heuristic algorithms and support vector machines. Saf Sci 50:629–644CrossRefGoogle Scholar
  59. Zhou J, Li X, Mitri HS (2016) Classification of rockburst in underground projects: comparison of ten supervised learning methods. J Comp Civ Eng 30:04016003. CrossRefGoogle Scholar
  60. Zimmer VL, Sitar N (2015) Detection and location of rock falls using seismic and infrasound sensors. Eng Geol 193:49–60. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Earth Sciences and EngineeringSun Yat-sen UniversityGuangzhouChina
  2. 2.School of Resources and Safety EngineeringCentral South UniversityChangshaChina

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