High-Resolution Shallow Structure Constrained by ambient noise S-wave tomography using dense linear arrays—a case study in northern Hong Kong

Authors

  • Guoxu Chen The Hong Kong Polytechnic University, Hong Kong Author
  • Tao Xie The Hong Kong Polytechnic University, Hong Kong Author
  • Zhiqian Liu The Hong Kong Polytechnic University, Hong Kong Author
  • Liang Lyu The Hong Kong Polytechnic University, Hong Kong Author
  • Hansong Pang The Hong Kong Polytechnic University, Hong Kong Translator
  • Boyang Su The Hong Kong Polytechnic University, Hong Kong Author
  • Shupeng Chai The Hong Kong Polytechnic University, Hong Kong Author
  • Andy Y. F. Leung The Hong Kong Polytechnic University, Hong Kong Author
  • Yiqing Ni The Hong Kong Polytechnic University, Hong Kong Author
  • Qi Zhao The Hong Kong Polytechnic University, Hong Kong Author
  • Dennis C.S. Lau Atkins Réalis Asia Limited, Hong Kong Author

DOI:

https://doi.org/10.21467/proceedings.7.7.18

Abstract

Conducting shallow structure tomography in Hong Kong is of great significance for engineering construction, urban underground space utilization, and geological disaster prevention. In this study, we deployed a linear array of 48 node seismometers at a construction site in northern Hong Kong and collected ambient noise data for about 2 days. The effects of different stacking durations and stacking methods on the noise cross-correlation function (NCF) were tested, indicating that the signal-to-noise ratio of NCF can be effectively improved by considering weighted methods during short-time stacking. We used the passive source-based multi-channel analysis of surface wave method (MASW) to extract the Rayleigh wave dispersion curve and inverted it to obtain the two-dimensional S-wave profile of the test site. Our results demonstrate that shallow S-wave tomography based on ambient noise data can quickly, safely and non-invasively constrain shallow structures, showing great potential for underground engineering applications.

References

Aki, K., Christoffersson, A., & Husebye, E. S. (1977). Determination of the three‐dimensional seismic structure of the lithosphere. Journal of Geophysical Research, 82(2), 277-296.

Bensen, G. D., Ritzwoller, M. H., Barmin, M. P., Levshin, A. L., Lin, F., Moschetti, M. P., Shapiro, N. M., & Yang, Y. (2007). Processing seismic ambient noise data to obtain reliable broad-band surface wave dispersion measurements. Geophysical Journal International, 169(3), 1239-1260. https://doi.org/10.1111/j.1365-246X.2007.03374.x

Brocher, T. M. (2005). Empirical relations between elastic wavespeeds and density in the Earth's crust. Bulletin of the Seismological Society of America, 95(6), 2081-2092.

Buchen, P. W., & Ben-Hador, R. (1996). Free-mode surface-wave computations. Geophysical Journal International, 124(3), 869-887. https://doi.org/10.1111/j.1365-246X.1996.tb05642.x

Chan, Y., Ho, K., & Pun, W. (1994). A new marble rock mass classification system for the interpretation of karst morphology in Hong Kong. HKIE Transactions, 1(2), 1-12.

Cheng, F., Xia, J., Luo, Y., Xu, Z., Wang, L., Shen, C., Liu, R., Pan, Y., Mi, B., & Hu, Y. (2016). Multichannel analysis of passive surface waves based on crosscorrelations. Geophysics, 81(5), EN57-EN66.

Cheng, F., Xia, J., Xu, Y., Xu, Z., & Pan, Y. (2015). A new passive seismic method based on seismic interferometry and multichannel analysis of surface waves. Journal of Applied Geophysics, 117, 126-135. https://doi.org/https://doi.org/10.1016/j.jappgeo.2015.04.005

Foti, S., Parolai, S., Albarello, D., & Picozzi, M. (2011). Application of surface-wave methods for seismic site characterization. Surveys in Geophysics, 32, 777-825.

Herrmann, R. B. (2013). Computer programs in seismology: An evolving tool for instruction and research. Seismological Research Letters, 84(6), 1081-1088.

Kästle, E. D., Soomro, R., Weemstra, C., Boschi, L., & Meier, T. (2016). Two-receiver measurements of phase velocity: cross-validation of ambient-noise and earthquake-based observations. Geophysical Journal International, 207(3), 1493-1512. https://doi.org/10.1093/gji/ggw341

Lobkis, O. I., & Weaver, R. L. (2008). On the emergence of the Green’s function in the correlations of a diffuse field.

Luu, K. (2021). disba: Numba-accelerated computation of surface wave dispersion. Zenodo, Dec.

Nakata, N., & Snieder, R. (2012). Estimating near-surface shear wave velocities in Japan by applying seismic interferometry to KiK-net data. Journal of Geophysical Research: Solid Earth, 117(B1). https://doi.org/https://doi.org/10.1029/2011JB008595

Park, C. B., Miller, R. D., & Xia, J. (1999). Multichannel analysis of surface waves. Geophysics, 64(3), 800-808.

Peterson, J. R. (1993). Observations and modeling of seismic background noise (2331-1258).

Schimmel, M., & Paulssen, H. (1997). Noise reduction and detection of weak, coherent signals through phase-weighted stacks. Geophysical Journal International, 130(2), 497-505. https://doi.org/10.1111/j.1365-246X.1997.tb05664.x

Schimmel, M., Stutzmann, E., & Gallart, J. (2011). Using instantaneous phase coherence for signal extraction from ambient noise data at a local to a global scale. Geophysical Journal International, 184(1), 494-506. https://doi.org/10.1111/j.1365-246X.2010.04861.x

Sewell, R. (2000). The pre-quaternary geology of Hong Kong. Hong Kong Geological Survey, Geotechnical Engineering Office, Civil ….

Shapiro, N. M., Campillo, M., Stehly, L., & Ritzwoller, M. H. (2005). High-resolution surface-wave tomography from ambient seismic noise. Science, 307(5715), 1615-1618. https://doi.org/10.1126/science.1108339

Van den Bergh, F., & Engelbrecht, A. P. (2004). A cooperative approach to particle swarm optimization. IEEE transactions on evolutionary computation, 8(3), 225-239.

Virieux, J., & Operto, S. (2009). An overview of full-waveform inversion in exploration geophysics. Geophysics, 74(6), WCC1-WCC26.

Xia, J., Miller, R. D., & Park, C. B. (1999). Estimation of near-surface shear-wave velocity by inversion of Rayleigh waves. Geophysics, 64(3), 691-700.

Downloads

Published

2025-11-21

How to Cite

[1]
Guoxu Chen, “High-Resolution Shallow Structure Constrained by ambient noise S-wave tomography using dense linear arrays—a case study in northern Hong Kong”, AIJR Proc., vol. 7, no. 7, pp. 203–212, Nov. 2025, doi: 10.21467/proceedings.7.7.18.