Abstract

It has been demonstrated both theoretically and experimentally that the Green's function between two receivers can be retrieved from the cross-correlation of isotropic noise records. Since surface waves dominate noise records in geophysics, tomographic inversion using noise correlation techniques have been performed from Rayleigh waves so far. However, very few numerical studies implying surface waves have been conducted to confirm the extraction of the true dispersion curves from noise correlation in a complicated soil structure. In this paper, synthetic noise has been generated in a small-scale (<1 km) numerical realistic environment and classical processing techniques are applied to retrieve the phase velocity dispersion curves, first step toward an inversion. We compare results obtained from spatial autocorrelation method (SPAC), high-resolution frequency-wavenumber method (HRFK) and noise correlation slantstack techniques on a 10-sensor array. Two cases are presented in the (1–20 Hz) frequency band that corresponds to an isotropic or a directional noise wavefield. Results show that noise correlation slantstack provides very accurate phase velocity estimates of Rayleigh waves within a wider frequency band than classical techniques and is also suitable for accurately retrieving Love waves dispersion curves.

Highlights

  • The Green’s function of a medium between two points A and B represents the record we would get at A if we put an impulse source at B

  • Despite convincing tomographic images of the subsurface shear velocity at large scales (Sabra et al 2005; Shapiro et al 2005) there is no study that confirms that the noise correlation process yields the true phase velocity dispersion curves in a realistic environment where several surface wave modes are present

  • Such a work would imply (1) the computation of the elastic field produced by multiple noise sources in a given subsurface model, (2) the recording of the numerical noise traces on a seismic array, (3) the computation of the noise-correlation function between each receiver pair and (4) the extraction of the phase–velocity dispersion curves from the noise-correlation process for a comparison to the actual dispersion curves directly obtained from the numerical model

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Summary

INTRODUCTION

The Green’s function of a medium between two points A and B represents the record we would get at A if we put an impulse source at B. Despite convincing tomographic images of the subsurface shear velocity at large scales (Sabra et al 2005; Shapiro et al 2005) there is no study that confirms that the noise correlation process yields the true phase velocity dispersion curves in a realistic environment where several surface wave modes are present Such a work would imply (1) the computation of the elastic field produced by multiple noise sources in a given subsurface model, (2) the recording of the numerical noise traces on a seismic array, (3) the computation of the noise-correlation function between each receiver pair and (4) the extraction of the phase–velocity dispersion curves from the noise-correlation process for a comparison to the actual dispersion curves directly obtained from the numerical model.

Ambient noise simulation
Choice of an optimized seismic array layout
Array response
Principle
Analysis of isotropic noise
Analysis of directional noise
R E S U LT S C O M PA RISON
Findings
CONCLUSION

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