Extracting Seismic Body and Rayleigh Waves from the Ambient Seismic Noise Using the rms-Stacking Method

Shirzad, Taghi; Shomali, Zaher‐Hossein

doi:10.1785/0220140123

Cited by 17 publications

(6 citation statements)

References 38 publications

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“…There are several methods of stacking the cross-correlation functions in the time domain, for example, the root-meansquare method of Shirzad and Shomali (2015) and the weighted stack by Cheng et al (2015). We compare the SNR of EGFs estimated by our method for the Pyhäsalmi experiment to the SNR of EGFs estimated by root-mean-square and weighted stacking methods, respectively.…”

Section: Empirical Green's Functions Estimationmentioning

confidence: 99%

“…In this case, one would need to take into account this distribution, in order to satisfy the stationary phase condition. The other group of methods, such as "root mean square stacking" or weight stacking (Shirzad and Shomali, 2015;Nakata et al, 2015;Cheng et al, 2015;Li et al, 2018) are aiming mainly at increasing a signal-to-noise ratio of the resulting EGF, but they do not take into account the coherence of the cross-correlation functions in the stack. That is why incoherent cross-correlation functions are not totally excluded from the stack in these algorithms, and this can decrease the quality of evaluated EGFs.…”

Section: Introductionmentioning

confidence: 99%

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Improving the quality of empirical Green's functions, obtained by cross-correlation of high-frequency ambient seismic noise

et al. 2019

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Abstract. Studying the uppermost structure of the subsurface is a necessary part of solving many practical problems (exploration of minerals, groundwater studies, geoengineering, etc.). The practical application of active seismic methods for these purposes is not always possible for different reasons, such as logistical difficulties, high cost of work, and a high level of seismic and acoustic noise. That is why developing and improving passive seismic methods is one of the important problems in applied geophysics. In our study, we describe a way of improving the quality of empirical Green's functions (EGFs), evaluated from high-frequency ambient seismic noise, by using the advanced technique of cross-correlation function stacking in the time domain (in this paper we use term “high-frequency” for frequencies higher than 1 Hz). The technique is based on the global optimization algorithm, in which the optimized objective function is a signal-to-noise ratio of an EGF, retrieved at each iteration. In comparison to existing techniques, based, for example, on weight stacking of cross-correlation functions, our technique makes it possible to significantly increase the signal-to-noise ratio and, therefore, the quality of the EGFs. The technique has been tested with the field data acquired in an area with a high level of industrial noise (Pyhäsalmi Mine, Finland) and in an area with a low level of anthropogenic noise (Kuusamo Greenstone Belt, Finland). The results show that the proposed technique can be used for the extraction of EGFs from high-frequency seismic noise in practical problems of mapping of the shallow subsurface, both in areas with high and low levels of high-frequency seismic noise.

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Section: Empirical Green's Functions Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving the quality of empirical Green's functions, obtained by cross-correlation of high-frequency ambient seismic noise

et al. 2019

View full text Add to dashboard Cite

show abstract

Section: Empirical Green's Functions Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Replies to review of Michał Chamarczuk

Afonin¹

2019

Preprint

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“…При этом существенную роль играет процедура подготовки данных, направленная на снижение вклада землетрясений в итоговую ККФ, а также осреднение ККФ за длительный (как правило, не менее года) период времени, чтобы Причины артефактов в шумовой поверхностно-волновой томографии … 59 сделать распределение источников более равномерным. Для получения групповых скоростей, как правило, используется процедура, подробно описанная в работе [Bensen et al, 2007], включающая, помимо прочего, амплитудную нормализацию -однобитную [Campillo, Paul, 2003] или нормализацию путём деления на бегущее среднее значение, а также спектральное отбеливание, или модификации этой процедуры, например, использование более коротких (не 24-часовых, а четырёхчасовых) временных промежутков, за которые вычисляется ККФ [Poli et al, 2012], нелинейное суммирование, включающее вычисление производной по времени [Shirzad, Shomali, 2015], или дополнительную фильтрацию [Moreau et al, 2017]. Также было показано, что проблема неравномерного распределения источников частично решается использованием только волн коды [Froment et al, 2010].…”

Section: Introductionunclassified

Causes of artifacts in ambient noise surface wave tomography in mantle investigations and ways for their elimination

Koroleva

Lyskova

2020

RJS

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Ambient noise surface wave tomography is a widely used method for determining the velocity structure of the upper layers of the Earth. It is based on the fact that the cross-correlation function (CCF) of noise at two stations, averaged over a long time interval, determines the Green's function of the surface wave. This allows us to estimate the group and phase velocities of surface waves on the paths between stations, which are used in surface-wave tomography. This makes it possible to ultimately estimate the spatial distribution of the S-wave velocities. The method is well-grounded on the assumption that the “noise” is a result of the superposition of surface waves propagating from sources uniformly distributed over the surface. Therefore, the initial data, which are long-period seismic records, are subjected to preliminary processing, an important stage of which is normalization, which allows reducing the effect of earthquakes and averaging the resulting CCFs over a long time interval. At the same time, we have shown that earthquakes mainly contribute to noise at periods above 30-40 s, whose sources are distributed unevenly. Therefore, in cases of clustering of foci in a certain limited area, for example, because of aftershocks after a strong earthquake, the CCF maxima, which determines the dispersion curve of the surface wave, are shifted to shorter times, and the group velocities are correspondingly overestimated. In determining the dispersion of Love waves from the CCF transversal (T-T) noise component, the presence of clusters leads to an additional underestimation of the group velocity due to the superposition on the T component (perpendicular to the inter-station path) of the radial component of the Rayleigh wave having a velocity less than the Love wave velocity. Therefore, the anisotropy coefficient, determined from the noise, is underestimated as compared to that obtained from the records of earthquakes along nearby paths. Obviously, to obtain more correct dispersion curves of both Rayleigh and Love waves, it is necessary, for summing the CCFs, to use time intervals in which earthquake clusters would be absent as far as possible.

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Extracting Seismic Body and Rayleigh Waves from the Ambient Seismic Noise Using the rms-Stacking Method

Cited by 17 publications

References 38 publications

Improving the quality of empirical Green's functions, obtained by cross-correlation of high-frequency ambient seismic noise

Improving the quality of empirical Green's functions, obtained by cross-correlation of high-frequency ambient seismic noise

Replies to review of Michał Chamarczuk

Causes of artifacts in ambient noise surface wave tomography in mantle investigations and ways for their elimination

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