1887
Volume 62, Issue 2
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

In regions where active source seismic exploration is constrained by limitations of energy penetration and recovery, cost and logistical concerns, or regulatory restrictions, analysis of natural source seismic data may provide an alternative. In this study, we investigate the feasibility of using locally‐generated seismic noise in the 2–6 Hz band to obtain a subsurface model via interferometric analysis. We apply this technique to three‐component data recorded during the La Barge Passive Seismic Experiment, a local deployment in south‐western Wyoming that recorded continuous seismic data between November 2008 and June 2009. We find traffic noise from a nearby state road to be the dominant source of surface waves recorded on the array and observe surface wave arrivals associated with this source up to distances of 5 kms. The orientation of the road with respect to the deployment ensures a large number of stationary points, leading to clear observations on both in‐line and cross‐line virtual source‐receiver pairs. This results in a large number of usable interferograms, which in turn enables the application of standard active source processing methods like signal processing, common offset stacking and traveltime inversion. We investigate the dependency of the interferograms on the amount of data, on a range of processing parameters and on the choice of the interferometry algorithm. The obtained interferograms exhibit a high signal‐to‐noise ratio on all three components. Rotation of the horizontal components to the radial/transverse direction facilitates the separation of Rayleigh and Love waves. Though the narrow frequency spectrum of the surface waves prevents the inversion for depth‐dependent shear‐wave velocities, we are able to map the arrival times of the surface waves to laterally varying group and phase velocities for both Rayleigh and Love waves. Our results correlate well with the known geological structure. We outline a scheme for obtaining localized surface wave velocities from local noise sources and show how the processing of passive data benefits from a combination with well‐established exploration seismology methods. We highlight the differences with interferometry applied to crustal scale data and conclude with recommendations for similar deployments.

Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.12080
2013-11-05
2024-03-28
Loading full text...

Full text loading...

References

  1. AkiK.1957. Space and time spectra of stationary stochastic waves, with special reference to micro‐tremors. Bulletin of the Earthquake Research Institute35, 415–457.
    [Google Scholar]
  2. BakulinA. and CalvertR.2006. The virtual source method: Theory and case study. Geophysics71, SI139–SI150.
    [Google Scholar]
  3. BehmM., BrücklE., ChwatalW. and ThyboH.2007. Application of stacking and inversion techniques to three‐dimensional wide‐angle reflection and refraction seismic data of the Eastern Alps. Geophysical Journal International170,275–298.
    [Google Scholar]
  4. BenderC.M. and OrszagS.A.1978. Advanced Mathematical Methods for Scientists and Engineers. McGraw‐Hill. ISBN 0387989315.
    [Google Scholar]
  5. BensenG.D, RitzwollerM.H, BarminM.P., LevshinA.L, LinF., MoschettiM.P.et al. 2007. Processing seismic ambient noise data to obtain reliable broad‐band surface wave dispersion measurements. Geophysical Journal International169, 1239–1260.
    [Google Scholar]
  6. BleisteinN.1984. Mathematical Methods for Wave Phenomena. Academic Press. ISBN 0121056503.
    [Google Scholar]
  7. BooreD. and ToksözM.N.1969. Rayleigh wave particle motion and crustal structure. Bulletin of the seismological Society of America59, 331–346.
    [Google Scholar]
  8. BussatS. and KuglerS.2009. Feasibility of Offshore Ambient‐Noise Surface‐Wave Tomography on a Reservoir Scale. 79th International SEG Meeting, Houston, USA, Expanded Abstracts, 1627–1631.
  9. DenesV., StarrE.W. and KapoorJ.2009. Developing Earth models with full waveform inversion. The Leading Edge28, 432–435.
    [Google Scholar]
  10. DongS., HeR. and SchusterG.T.2006. Interferometric Prediction and Least Squares Subtraction of Surface Waves. 76th International SEG Meeting, New Orleans, USA, Expanded Abstracts, 2783–2786.
  11. DraganovD., CampmanX., ThorbeckeJ., VerdelA. and WapenaarK.2009. Reflection images from ambient seismic noise. Geophysics74, 63–67.
    [Google Scholar]
  12. DziewonskiA.M., BlochS. and LandismanM.1969. A technique for the analysis of transient seismic signals. Bulletin of the seismological Society of America59, 427–444.
    [Google Scholar]
  13. ForghaniF. and SniederR.2010. Underestimation of body waves and feasibility of surface‐wave reconstruction by seismic interferometry. The Leading Edge29, 790–794.
    [Google Scholar]
  14. HallidayD.F. and CurtisA.2008. Seismic interferometry, surface waves and source distribution. Geophysical Journal International175, 1067–1087.
    [Google Scholar]
  15. HallidayD.F., CurtisA., RobertssonJ.O.A. and van ManenD.‐J.2007. Interferometric surface‐wave isolation and removal. Geophysics72, A69–A73.
    [Google Scholar]
  16. IwasakiT.2002. Extended time‐term method for identifying lateral structural variations from seismic refraction data. Earth Planets Space54, 663–677.
    [Google Scholar]
  17. LakM.A., DegrandeG. and LombaertG.2011. The effect of road unevenness on the dynamic vehicle response and ground‐borne vibrations due to road traffic. Soil Dynamics and Earthquake Engineering31, 1357–1377.
    [Google Scholar]
  18. LevshinA.L., YanovskayaT.B., LanderA.V., BukchinB.G., BarminM.P., RatnikovaL.I. and ItsE.N.1989. Seismic Surface Waves in a Laterally Inhomogeneous Earth. Modern Approaches in Geophysiscs, Ed. Keilis‐Borok V.I. Kluwer. ISBN 0‐7923‐0044‐0.
    [Google Scholar]
  19. LinF., MoschettiM.P. and RitzwollerM.H.2008. Surface wave tomography of the western United States from ambient seismic noise: Rayleigh and Love wave phase velocity maps. Geophysical Journal International169, 1239–1260.
    [Google Scholar]
  20. MertlS. and HausmannH.2009. Seismon– A flexible seismic processing software. European Geosciences Union General Assembly 2009, Vienna, Austria. Geophysical Research Abstracts, EGU2009–4266.
  21. O'ConnellD.R.H.2007. Concrete dams as seismic imaging sources. Geophysical Research Letters34, 4–8.
    [Google Scholar]
  22. PaulA., CampilloM., MargerinL., LaroseE. and DerodeA.2005. Empirical synthesis of time‐asymmetrical Green functions from the correlation of coda waves. Journal of Geophysical Research110, B08302.
    [Google Scholar]
  23. PicozziM., ParolaiS., BindiD. and StrolloA.2009. Characterization of shallow geology by high‐frequency seismic noise tomography. Geophysical Journal International176, 164–174.
    [Google Scholar]
  24. PolettoF. and MirandaF.2004. Seismic while drilling: Fundamentals to drill‐bit seismic for exploration. Handbook of Geophysical Exploration 35. Pergamon Press. ISBN 0‐080‐43928‐4.
    [Google Scholar]
  25. PrietoG., LawrenceJ.F and BerozaG.C.2009. Anelastic Earth Structure from the Coherency of the Ambient Seismic Field. Journal of Geophysical Research114, B07303.
    [Google Scholar]
  26. RialJ.A1989. Seismic wave resonances in 3‐D sedimentary basins. Geophysical Journal International99, 81–90.
    [Google Scholar]
  27. de RidderS. and DellingerJ.2011. Ambient seismic noise eikonal tomography for near‐surface imaging at Valhall. The Leading Edge30, 1–7.
    [Google Scholar]
  28. SaltzerR., LeahyG.M., SchmedesJ., RothJ. and RumpfhuberE.2011. Earthquakes – A naturally occurring source of low frequency data. 81st International SEG Meeting, San Antonio, USA, Expanded Abstracts, 3689–3693.
  29. SeatsK., LawrenceJ.F. and PrietoG.A.2012. Improved ambient noise cross correlation functions using Welch's method. Geophysical Journal International188, 513–523.
    [Google Scholar]
  30. ShearerP.M.1999. Introduction to Seismology. Cambridge University Press. ISBN 0‐521‐66953‐7.
    [Google Scholar]
  31. SirgueL. and PrattR.G.2004. Efficient waveform inversion and imaging: A strategy for selecting temporal frequencies. Geophysics69, 231–248.
    [Google Scholar]
  32. van der SluisA. and van der VorstH.A.1987. Numerical solution of large, sparse linear algebraic systems arising from tomographic problems. In: Seismic Tomography (eds G.Nolet and D.Reidel ), pp. 49–83. Hingham. ISBN 9027725837.
    [Google Scholar]
  33. SniederR.2004. Extracting the Green's function from the correlation of coda waves: A derivation based on stationary phase. Physical Review E69, 046610.
    [Google Scholar]
  34. SniederR.2007. Extracting the Green's function of attenuating heterogeneous acoustic media from uncorrelated waves. Journal of the Acoustical Society of America121, 2637–2643.
    [Google Scholar]
  35. SniederR. and SafakE.2006. Extracting the Building Response Using Seismic Interferometry: Theory and Application to the Millikan Library in Pasadena, California. Bulletin of the Seismological Society of America96, 586–598.
    [Google Scholar]
  36. SniederR., WapenaarK. and LarnerK.2006. Spurious multiples in seismic interferometry of primaries. Geophysics71, SI111–SI124.
    [Google Scholar]
  37. SongL.‐P., KochM., KochK. and SchlittenhardtJ.2004. 2‐D anisotropic Pn‐velocity tomography underneath Germany using regional traveltimes. Geophysical Journal International157, 645–663.
    [Google Scholar]
  38. StehlyL., CampilloM. and ShapiroN.M.2006. A study of the seismic noise from its long‐range correlation properties. Journal of Geophysical Research111, B10306.
    [Google Scholar]
  39. SteinS. and WyssesionM.2003. An Introduction to Seismology, Earthquakes, and Earth Structure. Blackwell publishing. ISBN 0‐86542‐078‐5.
    [Google Scholar]
  40. TsaiV.2011. Understanding the amplitudes of noise correlation measurements. Journal of Geophysical Research116, B09311.
    [Google Scholar]
  41. VasconcelosI. and SniederR.2008. Interferometry by deconvolution, Part 1: Theory for acoustic waves and numerical examples. Geophysics73, S115–S128.
    [Google Scholar]
  42. WapenaarK., DraganovD., SniederR., CampmanX. and VerdelA.2010a. Tutorial on seismic interferometry: Part 1 – Basic principles and applications. Geophysics75, 75A195–75A209.
    [Google Scholar]
  43. WapenaarK. and FokkemaJ.2006. Green's function representations for seismic interferometry. Geophysics71, SI33–SI46.
    [Google Scholar]
  44. WapenaarK., SlobE., SniederR. and CurtisA.2010b. Tutorial on seismic interferometry: Part 2 – Underlying theory and advances. Geophysics75, 75A211–75A227.
    [Google Scholar]
  45. WebbS.C.1998. Broadband seismology and noise under the ocean. Reviews of Geophysics36, 105–142.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1111/1365-2478.12080
Loading
/content/journals/10.1111/1365-2478.12080
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): Interferometry; Seismology; Surface wave

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error