On the estimation of attenuation from the ambient seismic field: inferences from distributions of isotropic point scatterers

Weemstra, Cornelis; Snieder, Roel; Boschi, Lapo

doi:10.1093/gji/ggv311

Cited by 12 publications

(10 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is inferred by comparing eqs. 5and 7that the expression (6) is still a solution of (7), if the real ratio ω/c in its argument is replaced by the complex number Kinsler et al, 1999;Snieder , 2007;Tsai , 2011;Weemstra et al, 2015]; the two-dimensional, damped…”

Section: Theory 21 Green's Problem For a Lossy Membranementioning

confidence: 99%

On seismic ambient noise cross-correlation and surface-wave attenuation

Boschi

Magrini

Cammarano

et al. 2019

Geophysical Journal International

Self Cite

View full text Add to dashboard Cite

SUMMARY We derive a theoretical relationship between the cross correlation of ambient Rayleigh waves (seismic ambient noise) and the attenuation parameter α associated with Rayleigh-wave propagation. In particular, we derive a mathematical expression for the multiplicative factor relating normalized cross correlation to the Rayleigh-wave Green’s function. Based on this expression, we formulate an inverse problem to determine α from cross correlations of recorded ambient signal. We conduct a preliminary application of our algorithm to a relatively small instrument array, conveniently deployed on an island. In our setup, the mentioned multiplicative factor has values of about 2.5–3, which, if neglected, could result in a significant underestimate of α. We find that our inferred values of α are reasonable, in comparison with independently obtained estimates found in the literature. Allowing α to vary with respect to frequency results in a reduction of misfit between observed and predicted cross correlations.

show abstract

Section: Theory 21 Green's Problem For a Lossy Membranementioning

confidence: 99%

On seismic ambient noise cross-correlation and surface-wave attenuation

Boschi

Magrini

Cammarano

et al. 2019

Geophysical Journal International

Self Cite

View full text Add to dashboard Cite

show abstract

“…These spurious peaks in the cross-correlation are generally referred to as 'cross-terms' (e.g. Weemstra et al 2015). Assuming the behaviour of different sources is uncorrelated, however, stacking over time renders these cross-terms negligible.…”

Section: Vertical Component (Rayleigh Waves)mentioning

confidence: 99%

Two-receiver measurements of phase velocity: cross-validation of ambient-noise and earthquake-based observations

Kästle¹,

Soomro

Weemstra

et al. 2016

Geophys. J. Int.

Self Cite

View full text Add to dashboard Cite

S U M M A R YPhase velocities derived from ambient-noise cross-correlation are compared with phase velocities calculated from cross-correlations of waveform recordings of teleseismic earthquakes whose epicentres are approximately on the station-station great circle. The comparison is conducted both for Rayleigh and Love waves using over 1000 station pairs in central Europe. We describe in detail our signal-processing method which allows for automated processing of large amounts of data. Ambient-noise data are collected in the 5-80 s period range, whereas teleseismic data are available between about 8 and 250 s, resulting in a broad common period range between 8 and 80 s. At intermediate periods around 30 s and for shorter interstation distances, phase velocities measured from ambient noise are on average between 0.5 per cent and 1.5 per cent lower than those observed via the earthquake-based method. This discrepancy is small compared to typical phase-velocity heterogeneities (10 per cent peak-to-peak or more) observed in this period range.We nevertheless conduct a suite of synthetic tests to evaluate whether known biases in ambient-noise cross-correlation measurements could account for this discrepancy; we specifically evaluate the effects of heterogeneities in source distribution, of azimuthal anisotropy in surface-wave velocity and of the presence of near-field, rather than far-field only, sources of seismic noise. We find that these effects can be quite important comparing individual station pairs. The systematic discrepancy is presumably due to a combination of factors, related to differences in sensitivity of earthquake versus noise data to lateral heterogeneity. The data sets from both methods are used to create some preliminary tomographic maps that are characterized by velocity heterogeneities of similar amplitude and pattern, confirming the overall agreement between the two measurement methods.

show abstract

“…For values of α that are small in the sense that α ω/c, the complex wavenumber can be approximated by (ωr/c) 1 − (2iαc/ω) (Weemstra et al 2015). The Hankel function may in that case be approximated by H (2) 0 (ωr/c(ω))e −αr (Tsai 2011).…”

Section: Estimating Phase Velocitymentioning

confidence: 99%

Application of seismic interferometry by multidimensional deconvolution to ambient seismic noise recorded in Malargüe, Argentina

Weemstra

Draganov²,

Ruigrok

et al. 2016

Geophys. J. Int.

Self Cite

View full text Add to dashboard Cite

S U M M A R YObtaining new seismic responses from existing recordings is generally referred to as seismic interferometry (SI). Conventionally, the SI responses are retrieved by simple crosscorrelation of recordings made by separate receivers: one of the receivers acts as a 'virtual source' whose response is retrieved at the other receivers. When SI is applied to recordings of ambient seismic noise, mostly surface waves are retrieved. The newly retrieved surface wave responses can be used to extract receiver-receiver phase velocities. These phase velocities often serve as input parameters for tomographic inverse problems. Another application of SI exploits the temporal stability of the multiply scattered arrivals of the newly retrieved surface wave responses. Temporal variations in the stability and/or arrival time of these multiply scattered arrivals can often be linked to temporally varying parameters such as hydrocarbon production and precipitation. For all applications, however, the accuracy of the retrieved responses is paramount. Correct response retrieval relies on a uniform illumination of the receivers: irregularities in the illumination pattern degrade the accuracy of the newly retrieved responses. In practice, the illumination pattern is often far from uniform. In that case, simple crosscorrelation of separate receiver recordings only yields an estimate of the actual, correct virtual-source response. Reformulating the theory underlying SI by crosscorrelation as a multidimensional deconvolution (MDD) process, allows this estimate to be improved. SI by MDD corrects for the non-uniform illumination pattern by means of a so-called point-spread function (PSF), which captures the irregularities in the illumination pattern. Deconvolution by this PSF removes the imprint of the irregularities on the responses obtained through simple crosscorrelation. We apply SI by MDD to surface wave data recorded by the Malargüe seismic array in western Argentina. The aperture of the array is approximately 60 km and it is located on a plateau just east of the Andean mountain range. The array has a T-shape: the receivers along one of the two lines act as virtual sources whose responses are recorded by the receivers along the other (perpendicular) line. We select time windows dominated by surface wave noise travelling in a favourable direction, that is, traversing the line of virtual sources before arriving at the receivers at which we aim to retrieve the virtual-source responses. These time windows are selected through a frequency-dependent slowness analysis along the two receiver lines. From the selected time windows, estimates of virtual-source responses are retrieved by means of crosscorrelations. Similarly, crosscorrelations between the positions of the virtual sources are computed to build C The

show abstract

On the estimation of attenuation from the ambient seismic field: inferences from distributions of isotropic point scatterers

Cited by 12 publications

References 53 publications

On seismic ambient noise cross-correlation and surface-wave attenuation

On seismic ambient noise cross-correlation and surface-wave attenuation

Two-receiver measurements of phase velocity: cross-validation of ambient-noise and earthquake-based observations

Application of seismic interferometry by multidimensional deconvolution to ambient seismic noise recorded in Malargüe, Argentina

Contact Info

Product

Resources

About