1887
Volume 71 Number 7
  • E-ISSN: 1365-2478

Abstract

Abstract

Body‐wave reflections are sensitive to sharp velocity contrasts, making them useful for lithological imaging. We analysed seismic data from natural earthquake, ambient noise and mine blasts to map P‐wave reflection profiles at the Hishikari mine area by autocorrelation analysis. Because fissure‐filled gold veins are dominant in this area, we evaluated the potential of autocorrelation analysis for investigating the shallow subsurface, including the ore deposits. Seismic interferometry is commonly performed based on the autocorrelation of ambient noise or natural earthquake signals; here, we instead used blasting in the mine because blast events include high‐frequency signals that boost the spatial resolution of the imaging. To effectively extract P‐wave reflections from seismic signals including blast events, we applied Gaussian smoothing and spectral whitening to remove source effects and then investigated the optimum frequency band. We successfully obtained auto‐correlograms showing high‐resolution seismic reflectors at shallow formation depths. These reflections are interpreted to be lithological boundaries shallower than 500 m. A comparison with profiles obtained from ambient noise and earthquake data showed that blasting signals yielded highly spatially consistent reflections that would not be achievable with natural or ambient seismic sources. This study highlights the potential of using blast autocorrelation seismic analysis during short survey periods. By using single‐blast shots and dense seismic station spacings, we successfully achieved higher resolution 3D reflection images of lithological interfaces, possibly including ore veins.

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2023-09-09
2025-11-11
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References

  1. Aldawood, A., Almarzoug, M., Silvestrov, I., Bakulin, A. (2022) Characterizing shallow subsurface using 3D seismic while drilling with a downhole pilot. The Leading Edge, 41(5), 304–312. https://doi.org/10.1190/tle41050304.1
    [Google Scholar]
  2. Aldawood, A., Silvestrov, I. & Bakulin, A. (2019) Virtual Shear‐wave source delivers a reliable S‐wave velocity model for VSP imaging. In: 81st EAGE conference and exhibition 2019. European Association of Geoscientists & Engineers, pp. 1–5. https://doi.org/10.3997/2214‐4609.201900695
    [Google Scholar]
  3. Becker, G. & Knapmeyer‐Endrun, B. (2018) Crustal thickness across the Trans‐European Suture Zone from ambient noise autocorrelations. Geophysical Journal International, 212(2), 1237–1254. https://doi.org/10.1093/gji/ggx485
    [Google Scholar]
  4. Bensen, G.D., Ritzwoller, M.H., Barmin, M.P., Levshin, A.L., Lin, F., Moschetti, M.P. et al. (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
    [Google Scholar]
  5. Chimoto, K. & Yamanaka, H. (2019) S‐Wave velocity structure exploration of sedimentary layers using seismic interferometry on strong motion records. Exploration Geophysics, 50(6), 625–633. https://doi.org/10.1080/08123985.2019.1654835
    [Google Scholar]
  6. Chimoto, K. & Yamanaka, H. (2020). Tuning S‐wave velocity structure of deep sedimentary layers in the Shimousa region of the Kanto Basin, Japan, using autocorrelation of strong‐motion records. Bulletin of the Seismological Society of America, 110(6), 2882–2891. https://doi.org/10.1785/0120200156
    [Google Scholar]
  7. Claerbout . (1968) Synthesis of a layered medium from its acoustic transmission response. Geophysics, 33(2), 264–269.
    [Google Scholar]
  8. Gorbatov, A., Saygin, E. & Kennett, B.L.N. (2013) Crustal properties from seismic station autocorrelograms. Geophysical Journal International, 192(2), 861–870. https://doi.org/10.1093/gji/ggs064
    [Google Scholar]
  9. Heath, B.A., Hooft, E.E.E. & Toomey, D.R. (2018) Autocorrelation of the seismic wavefield at Newberry Volcano: Reflections from the magmatic and geothermal systems. Geophysical Research Letters, 45, 2311–2318. https://doi.org/10.1002/2017GL076706
    [Google Scholar]
  10. Ishihara, S., Sakamaki, Y., Sasaki, A., Teraoka, Y. & Terashima, S. (1986) Role of the basement in the genesis of the Hishikari gold‐quartz vein deposit, southern Kyushu, Japan. Mining Geology, 36, 495–509.
    [Google Scholar]
  11. Ito, Y. & Shiomi, K. (2012) Seismic scatterers within subducting slab revealed from ambient noise autocorrelation. Geophysical Research Letters, 39(19), L19303. https://doi.org/10.1029/2012GL053321
    [Google Scholar]
  12. Izawa, E., Kurihara, M. & Itaya, T. (1993) K‐Ar ages and initial Ar isotopic ratio of adularia‐quartz veins from the Hishikari gold deposit, Japan. Resource Geology Special Issue, 14, 63–69.
    [Google Scholar]
  13. Izawa, E., Urashima, Y., Ibaraki, K., Suzuki, R., Yokoyama, T., Kawasaki, K. et al. (1990) The Hishikari gold deposit: high grade epithermal veins in Quaternary volcanics of southern Kyushu, Japan. Journal of Geochemical Exploration, 36, 1–56.
    [Google Scholar]
  14. Kennett, B.L.N., Saygin, E. & Salmon, M. (2015) Stacking autocorrelograms to map Moho depth with high spatial resolution in southeastern Australia. Geophysical Research Letters, 42(18), 7490–7497. https://doi.org/10.1002/2015GL065345
    [Google Scholar]
  15. Mroczek, S. & Tilmann, F. (2021) Joint ambient noise autocorrelation and receiver function analysis of the Moho. Geophysical Journal International, 225(3), 1920–1934. https://doi.org/10.1093/gji/ggab065
    [Google Scholar]
  16. Nakahara, H. (2006) Theoretical background of retrieving Greens function by cross‐correlation: one‐dimensional case. Geophysical Journal International, 165, 719–728.
    [Google Scholar]
  17. Okada, K. (1995) Geophysical exploration for epithermal gold deposits: case studies from the Hishikari Gold Mine, Kagoshima, Japan. Exploration Geophysics, 26(2–3), 78–83. https://doi.org/10.1071/EG995078
    [Google Scholar]
  18. Okada, K. (2000) Geophysical exploration at Hishikari gold mine, Kagoshima, Japan. The Leading Edge, 19(7), 673–816. https://doi.org/10.1190/1.1438708
    [Google Scholar]
  19. Okada, K., Minami, Y. & Ono, M. (2018) Microtremor survey for exploration targetting epithermal vein systems at the Hishikari Gold Mine, Kagoshima, Japan. In: 2nd conference on geophysics for mineral exploration and mining. European Association of Geoscientists & Engineers, pp. 1–5. https://doi.org/10.3997/2214‐4609.201802740
    [Google Scholar]
  20. Oren, C. & Nowack, R.L. (2017) Seismic body‐wave interferometry using noise autocorrelations for crustal structure. Geophysical Journal International, 208(1), 321–332. https://doi.org/10.1093/gji/ggw394
    [Google Scholar]
  21. Romero, P. & Schimmel, M. (2018) Mapping the basement of the Ebro Basin in Spain with seismic ambient noise autocorrelations. Journal of Geophysical Research: Solid Earth, 123(6), 5052–5067. https://doi.org/10.1029/2018JB015498
    [Google Scholar]
  22. Saygin, E., Cummins, P.R. & Lumley, D. (2017) Retrieval of the P wave reflectivity response from autocorrelation of seismic noise: Jakarta Basin, Indonesia. Geophysical Research Letters, 44(2), 792–799. https://doi.org/10.1002/2016GL071363
    [Google Scholar]
  23. Schuster, G.T. (2009) Seismic interferometry. Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511581557
    [Google Scholar]
  24. Sekine, R., Izawa, E. & Watanabe, K. (2002) Timing of fracture formation and duration of mineralization at the Hishikari deposit, Southern Kyushu, Japan. Resource Geology, 52(4), 395–404.
    [Google Scholar]
  25. Suemoto, Y., Ikeda, T. & Tsuji, T. (2020) Temporal variation and frequency dependence of seismic ambient noise on Mars from polarization analysis. Geophysical Research Letters, 47(13), e2020GL087123. https://doi.org/10.1029/2020GL087123
    [Google Scholar]
  26. Taylor, G., Rost, S. & Houseman, G. (2016) Crustal imaging across the North Anatolian Fault Zone from the autocorrelation of ambient seismic noise. Geophysical Research Letters, 43(6), 2502–2509. https://doi.org/10.1002/2016GL067715
    [Google Scholar]
  27. Tibuleac, I.M. & von Seggern, D. (2012) Crust‐mantle boundary reflectors in Nevada from ambient seismic noise autocorrelations. Geophysical Journal International, 189(1), 493–500. https://doi.org/10.1111/j.1365‐246X.2011.05336.x
    [Google Scholar]
  28. Uto, T., Imai, A. & Yamato, Y. (2001) Horizontal strain rate in relation to vein formation of the Hishikari gold deposits, Southern Kyushu, Japan. Resource Geology, 51(1), 7–18. https://doi.org/10.1111/j.1751‐3928.2001.tb00077.x
    [Google Scholar]
  29. Wang, C., Tauzin, T., Pham, T.‐S. & Tkalčić, H. (2020) On the efficiency of P‐Wave coda autocorrelation in recovering crustal structure: examples from dense arrays in the Eastern United States. Journal of Geophysical Research: Solid Earth, 125(12), e2020JB020270. https://doi.org/10.1029/2020JB020270
    [Google Scholar]
  30. Wapenaar, K. (2004) Retrieving the Elastodynamic Green's function of an arbitrary inhomogeneous medium by cross correlation. Physical Review Letters, 93(25), 254301. https://doi.org/10.1103/PhysRevLett.93.254301
    [Google Scholar]
  31. Zhang, Y., Li, Y.E. & Ku, T. (2021) Soil/rock interface profiling using a new passive seismic survey: autocorrelation seismic interferometry. Tunnelling and Underground Space Technology, 115, 104045. https://doi.org/10.1016/j.tust.2021.104045
    [Google Scholar]
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  • Article Type: Research Article
Keyword(s): data processing; imaging; passive method; seismics; signal processing

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