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Volume 18, Issue 5
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

ABSTRACT

The use of surface wave testing for near‐surface engineering applications has increased in recent years. Typical surface wave analysis is based on the dispersion of surface waves in one‐dimensional layered models. One‐dimensional models are inappropriate for measurements at sites with appreciable lateral variability, a likely scenario in many engineering applications. Use of such models can subsequently undermine the reliability and accuracy of the surface wave results. Full waveform inversion (FWI) is a high‐resolution imaging technique that is proven to outperform the conventional dispersion‐based analysis of surface waves. Much of the near‐surface literature has focused on full waveform inversion of Rayleigh waves developed by the interaction of primary‐ and vertically polarized shear waves (P‐SV), and the capabilities of surface waves generated by horizontally polarized shear waves (Love waves) in mapping near‐surface spatial variabilities have not been fully explored. In this numerical study, full waveform inversion of Rayleigh and Love waves was performed on two different spatially correlated Gaussian random fields (mean of 200 and 500 m/s) to mimic the natural spatial variability of geologic materials. Each soil structure was produced at a low and high level of stiffness variability. Two sources with different frequency contents, 25 and 50 Hz, were used to evaluate the effects of source characteristics on the resolution of Rayleigh and Love waveform inversions. The inverted results from the high‐velocity domain demonstrated that Love waveform inversion using high‐frequency seismic sources outperforms Rayleigh full waveform inversion in detecting the shape and the velocities of horizontally deposited geologic materials. Results from the low‐velocity domain also confirmed that Love full waveform inversion was comparable or superior to Rayleigh full waveform inversion, though the performance difference was less significant. However, the 25‐Hz frequency inversions yielded superior results than the 50‐Hz frequency inversions for the low‐velocity domain because the dominant wavelength of the high‐frequency signals becomes so small that it offers an impractically small investigation depth.

© 2020 European Association of Geoscientists & Engineers © 2020 European Association of Geoscientists & Engineers
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2020-06-15
2024-04-26

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References

  1. Achenbach, J.D. (1984) Wave Propagation in Elastic Solids. Amsterdam, the Netherlands: North‐Holland Publishing.
     [Google Scholar]
  2. Akkaya, A. and Vanmarcke, E.H. (2003) Estimation of spatial correlation of soil parameters based on data from the Texas A&M University NGES. In: Vanmarcke, E. and Fenton, G.A. (Eds.) Probabilistic Site Characterization at the National Geotechnical Experimental Sites. Reston, VA: ASCE, pp. 29–40.
     [Google Scholar]
  3. Asaoka, A. and A‐Grivas, D. (1982) Spatial variability of the undrained strength of clays. Journal of Geotechnical Engineering, 108, 743–756.
     [Google Scholar]
  4. Bergamo, P., Boiero, D. and Socco, L.V. (2012) Retrieving 2D structures from surface‐wave data by means of space‐varying spatial windowing. Geophysics, 77, EN39–EN51.
     [Google Scholar]
  5. Beydoun, W.B. and Tarantola, A. (1988) First Born and Rytov approximation: Modeling and inversion conditions in a canonical example. Journal of the Acoustical Society of America, 83, 1045–1055.
     [Google Scholar]
  6. Bong, T. and StuedleinA.W. (2017) Spatial variability of CPT parameters and silty fines in liquefiable beach sands. Journal of Geotechnical and Geoenvironmental Engineering, 143(12)
     [Google Scholar]
  7. Constantine, P.G. and Wang, Q. (2012) Random field simulation.
  8. Courant, R., Friedrichs, K. and Lewy, H. (1928) Über die partiellen Differenzengleichungen der mathematischen Physik. Mathematische Annalen, 100, 32–74.
     [Google Scholar]
  9. Clayton, R. and Engquist, B. (1977) Absorbing boundary conditions for acoustic and elastic wave equations. Bulletin of the Seismological Society of America, 67, 1529–1540.
     [Google Scholar]
  10. Dal Moro, G. (2015) Surface Wave Analysis for Near Surface Applications, p. 244. Elsevier.
     [Google Scholar]
  11. Di Giulio, G., Punzo, M., Bruno, P.P., Cara, F. and Rovelli, A. (2019) Using a vibratory source at Mt. Etna (Italy) to investigate the wavefield polarization at Pernicana Fault. Near Surface Geophysics, 17, 313–329.
     [Google Scholar]
  12. Dokter, E., Köhn, D., Wilken, D., De Nil, D. and Rabbel, W. (2017) Full waveform inversion of SH‐ and Love‐wave data in near‐surface prospecting. Geophysical Prospecting, 65, 216–236.
     [Google Scholar]
  13. Fathi, A., Poursartip, B., Stokoe, K.H., II and Kallivokas, L.F. (2016) Three‐dimensional P‐ and S‐wave velocity profiling of geotechnical sites using full‐waveform inversion driven by field data. Soil Dynamics and Earthquake Engineering, 87, 63–81.
     [Google Scholar]
  14. Gelis, C., Virieux, J. and Grandjean, G. (2007) Two‐dimensional elastic waveform inversion using Born and Rytov formulations in the frequency domain. Geophysical Journal International, 168, 605–633.
     [Google Scholar]
  15. Groos, L., Schäfer, M., Forbriger, T. and Bohlen, T. (2017) Application of a complete workflow for 2D elastic full‐waveform inversion to recorded shallow‐seismic Rayleigh waves. Geophysics, 82, R109–R117.
     [Google Scholar]
  16. Hayashi, K. and Suzuki, H. (2004) CMP cross‐correlation analysis of multichannel surface‐wave data. Exploration Geophysics, 35, 7–13.
     [Google Scholar]
  17. Heisey, J.S., Stokoe, K.H., II and Meyer, A.H. (1982) Moduli of pavement systems from Spectral Analysis of Surface Waves. Transportation Research Record, 852, 22–31.
     [Google Scholar]
  18. Kallivokas, L.F., Fathi, A., Kucukcoban, S., Stokoe, K.H., Bielak, J. and Ghattas, O. (2013) Site characterization using full waveform inversion. Soil Dynamics and Earthquake Engineering, 47, 62–82.
     [Google Scholar]
  19. Kolda, T., O'Leary, D. and Nazareth, L. (1998) BFGS with update skipping and variable memory. SIAM Journal on Optimization, 8, 1060–1083.
     [Google Scholar]
  20. Kordjazi, A. (2019) Novel application of nondestructive testing to evaluate anomalous conditions in drilled shafts and the geologic materials underlying their excavations. Ph.D. dissertation, Temple University.
  21. Köhn, D., Wilken, D., Wunderlich, T., De Nil, D., Rabbel, W., Werther, L.et al. (2018) Seismic SH full waveform inversion as new prospection method in archaeogeophysics. 24th European Meeting of Environmental and Engineering Geophysics, Porto, Portugal.
  22. Lamert, A., Nguyen, L.T., Friederich, W. and Nestorović, T. (2018) Imaging disturbance zones ahead of a tunnel by elastic full‐waveform inversion: Adjoint gradient based inversion vs. parameter space reduction using a level‐set method. Underground Space, 3, 21–33.
     [Google Scholar]
  23. Liu, L., Ding, R., Liu, H. and Liu, H. (2015) 3D hybrid‐domain full waveform inversion on GPU. Computers & Geosciences, 83, 27–36.
     [Google Scholar]
  24. Liu, D. and Nocedal, J. (1989) On the limited memory BFGS method for large scale optimization. Mathematical Programming, 45, 504–528.
     [Google Scholar]
  25. Love, A.E. (1911) Some Problems of Geodynamics, Cambridge University Press.
     [Google Scholar]
  26. Mahvelati, S. and Coe, J.T. (2017) The use of two dimensional (2D) multichannel analysis of surface waves (MASW) testing to evaluate the geometry of an unknown bridge foundation. Proceedings of Geotechnical Frontiers, 2017, Orlando, 657–666.
     [Google Scholar]
  27. Mao, J., Wu, R.S. and Wang, B. (2012) Multiscale full waveform inversion using GPU. Proceedings of SEG Technical Program Expanded Abstracts, 2012, 1–7.
     [Google Scholar]
  28. Mavko, G., Mukerji, T. and Dvorkin, J. (1996) Rock Physics Handbook. Stanford University.
     [Google Scholar]
  29. Modrak, R.T., Borisov, D., Lefebvre, M. and Tromp, J. (2018) SeisFlows—Flexible waveform inversion software. Computers and Geosciences, 115, 88–95.
     [Google Scholar]
  30. Modrak, R.T. and Tromp, J. (2016) Seismic waveform inversion best practices: regional, global and exploration test cases. Geophysical Journal International, 206, 1864–1889.
     [Google Scholar]
  31. Montgomery, J. and Boulanger, R.W. (2016) Effects of spatial variability on liquefaction‐induced settlement and lateral spreading. Journal of Geotechnical and Geoenvironmental Engineering, 143, 0001584.
     [Google Scholar]
  32. Müller, T. (2001) Seismic pulse propagation in statistically heterogeneous geological structures. Ph.D. dissertation, Freie Universität Berlin.
  33. Neducza, B. (2007) Stacking of surface waves. Geophysics, 72, V51–V58.
     [Google Scholar]
  34. Nguyen, T.D., Tran, K.T. and McVay, M. (2016) Evaluation of unknown foundations using surface‐based full waveform tomography. Journal of Bridge Engineering, 21, 04016013.
     [Google Scholar]
  35. Nuber, A., Manukyan, E. and Maurer, H. (2015) Enhancement of near surface elastic full waveform inversion results in regions of low sensitivities. Journal of Applied Geophysics, 122, 192–201.
     [Google Scholar]
  36. Pan, Y., Xia, J., Xu, Y., Gao, L. and Xu, Z. (2016) Love‐wave waveform inversion in time domain for shallow shear‐wave velocity. Geophysics, 81, R1–R14.
     [Google Scholar]
  37. Park, C.B. (2005) MASW‐horizontal resolution in 2D shear‐velocity (Vs) mapping. KGS Open‐File Report 2005‐4. Kansas Geological Survey, University of Kansas.
  38. Park, C.B., Miller, R.D. and Xia, J. (1999) Multichannel analysis of surface waves. Geophysics, 64, 800–808.
     [Google Scholar]
  39. Phoon, K.K. and Kulhawy, F.H. (1999) Characterization of geotechnical variability. Canadian Geotechnical Journal, 36, 612–624.
     [Google Scholar]
  40. Romdhane, A., Grandjean, G., Brossier, R., Rejiba, F., Operto, S. and Virieux, J. (2011) Shallow‐structure characterization by 2D elastic full‐waveform inversion. Geophysics, 76, R81–R93.
     [Google Scholar]
  41. Roy, R., Kocel, E., Dyaur, N. and Stewart, R.R. (2013) Lateral heterogeneity and surface‐wave inversion (MASW). SEG Technical Program Expanded Abstracts, 2013, 1909–1913.
     [Google Scholar]
  42. Smith, J., Borisov, D., Modrak, R., Tromp, J., Cudney, H., Moran, M.et al. (2017) Near‐surface seismic imaging of tunnels using 3D elastic full‐waveform inversion. SEG Technical Program Expanded Abstracts, 2017, 2637–2641.
     [Google Scholar]
  43. Socco, L.V., Boiero, D., Foti, S. and Wisén, R. (2009) Laterally constrained inversion of ground roll from seismic reflection records. Geophysics, 74, G35–G45.
     [Google Scholar]
  44. Socco, L.V., Comina, C. and Khosro Anjom, F. (2017) Time‐average velocity estimation through surface‐wave analysis: part 1 – S‐wave velocity. Geophysics, 82, U49–U59.
     [Google Scholar]
  45. Song, Y., Castagna, J., Black, R. and Knapp, R. (1989) Sensitivity of near‐surface shear‐wave velocity determination from Rayleigh and Love waves. SEG Technical Program Expanded Abstracts, 1989, 509–512.
     [Google Scholar]
  46. Stacey, R. (1988) Improved transparent boundary formulations for the elastic‐wave equation. Bulletin of the Seismological Society of America, 78, 2089–2097.
     [Google Scholar]
  47. Stokoe, K.H., II,Wright, G.W., Bay, J.A. and Roesset, J.M. (1994) Characterization of geotechnical sites by SASW method. In: Woods, R.D. (Eds.) Geophysical Characterization of Sites. ISSMFE Tech. Committee #10. New Delhi, India: Oxford Publishers.
     [Google Scholar]
  48. Tarantola, A. (1984) Inversion of seismic reflection data in the acoustic approximation. Geophysics, 49, 1259–1266.
     [Google Scholar]
  49. Teodor, D., Comina, C., Khosro Anjom, F., Socco, L.V., Virieux, J., Trinh, P.et al. (2018) Building initial models for full‐waveform Inversion of shallow targets by surface‐waves dispersion curves clustering and data transform. SEG Technical Program Expanded Abstracts, 2018, 4738–4742.
     [Google Scholar]
  50. Tromp, J., Komatitsch, D. and Liu, Q. (2008) Spectral‐element and adjoint methods in seismology. Communications in Computational Physics, 3, 1–32.
     [Google Scholar]
  51. Vanmarcke, E.H. (1983) Random Fields: Analysis and Synthesis. Cambridge, MA: MIT Press.
     [Google Scholar]
  52. Vignoli, G. and Cassiani, G. (2009) Identification of lateral discontinuities via multi‐offset phase analysis of surface wave data. Geophysical Prospecting, 58, 389–413.
     [Google Scholar]
  53. Vignoli, G., Gervasio, I., Brancatelli, G., Boaga, J., Della Vedova, B. and Cassiani, G. (2015) Frequency‐dependent multi‐offset phase analysis of surface waves: an example of high‐resolution characterization of a riparian aquifer. Near Surface Geophysics, 64, 102–111.
     [Google Scholar]
  54. Vignoli, G., Strobbia, C., Cassiani, G. and Vermeer, P. (2011) Statistical multioffset phase analysis for surface‐wave processing in laterally varying media. Geophysics, 76, U1–U11.
     [Google Scholar]
  55. Virieux, J. and Operto, S. (2009) An overview of full‐waveform inversion in exploration geophysics. Geophysics, 74WCC1–WCC26.
     [Google Scholar]
  56. Wittkamp, F., Athanasopoulos, N. and Bohlen, T. (2019) Individual and joint 2‐D elastic full‐waveform inversion of Rayleigh and Love waves. Geophysical Journal International, 216, 350–364.
     [Google Scholar]
  57. Xia, J., Miller, R.D. and Park, C.B. (1999) Estimation of near‐surface shear‐wave velocity by inversion of Rayleigh wave. Geophysics, 64, 691–700.
     [Google Scholar]
  58. Xia, J., Xu, Y., Luo, Y., Miller, R.D., Cakir, R. and Zeng, C. (2012) Advantages of using Multichannel analysis of Love waves (MALW) to estimate near‐surface shear‐wave velocity. Surveys in Geophysics, 33, 841–860.
     [Google Scholar]
  59. Yang, P., Gao, J. and Wang, B. (2015) A graphics processing unit implementation of time‐domain full‐waveform inversion. Geophysics, 80, F31–F39.
     [Google Scholar]
  60. Yoon, M. (2005) Deep seismic imaging in the presence of a heterogeneous overburden: numerical modelling and case studies from the Central Andes and Southern Andes. Ph.D. dissertation, Freie Universität Berlin.
  61. Zeng, C., Xia, J., Liang, Q. and Chen, C. (2007) Comparative analysis on sensitivities of Love and Rayleigh waves. SEG Technical Program Expanded Abstracts, 2007, 1138–1141.
     [Google Scholar]
  62. Zeng, C., Xia, J., Miller, R.D. and Tsoflias, G.P. (2011) Feasibility of waveform inversion of Rayleigh waves for shallow shear‐wave velocity using genetic algorithm. Journal of Applied Geophysics, 75, 648–655.
     [Google Scholar]
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Numerical comparison of Rayleigh and Love full waveform inversion in characterizing soil spatial variability for near‐surface engineering applications
Near Surface Geophysics 18, 497 (2020); https://doi.org/10.1002/nsg.12103
/content/journals/10.1002/nsg.12103
/content/journals/10.1002/nsg.12103
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  • Article Type: Research Article
Keyword(s): Geotechnical; Inversion; Site Characterization; Surface Wave; Variability

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