The Development of a 2‐Dimensional Microtremor Survey Method Based on SPAC Method Using Sequential Linear Arrays

Kita, Takaho; Hayashi, Koichi; Bingol, Haldun; Karaoğlu, Hikmet; Duran, Kemal; Gümüş, Salim

doi:10.4133/1.3614262

Cited by 14 publications

(7 citation statements)

References 3 publications

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“…Hayashi & Kita (2010) showed, through a field experiment, that the linear array configuration can provide reliable phase velocities and almost identical dispersion curves as 2D array spreads when the propagation direction of the ambient vibration is distributed at a minimum range of 120º. Kita et al (2011) employed a linear roll along acquisition of passive recording of ambient vibration to obtain a pseudo-2D Vs model. Hayashi et al (2018) performed a comparison of dispersion curves calculated from passive records acquired using a linear array and a L-shaped array, obtaining similar dispersion trends.…”

Section: Assumptions Around the Spac Methodsmentioning

confidence: 99%

“…Park et al (2001) and Xia et al (2004) reported that the longer the geophone spread, the higher the resolution of the dispersion image. The goal of this approach is to obtain a pseudo-2D Vs model from the interpolation of horizontal aligned 1D models at every 10 m along the survey line which was addressed as Twodimensional Linear Array Microtremor Survey (2D-LAMS) by Kita et al (2011).…”

Section: Data Processingmentioning

confidence: 99%

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Spatial Autocorrelation of Passive Surface Wave Data for Assessment of an Earth Dam in Brasília, Brazil

et al. 2021

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ABSTRACT. Surface wave methods are commonly applied to engineering problems for S-wave velocity estimations. Conventional active Multichannel Analysis of Surface Waves (MASW) surveys for earth dam assessment suffer from limitations mainly associated to restrict depth of investigation and negative influences of near noise sources. In Brazil, the need to image around noisy sites over 30 m deep, which are non-ideal contexts for traditional active seismic data campaigns, is commonly in demand. We acquired ten minutes of ambient vibration data at the crest of a large earth dam in Brasília, Federal District. The Spatial Autocorrelation (SPAC) method was applied to develop a 2D S-wave model velocity using surface wave generated from passing vehicles on the adjacent road. A maximum depth of 42 m was achieved, and the model presented a S-wave velocity range from 274 m/s up to 713 m/s. The water level, foundation ground and possible low and high anomalous compaction zones were interpreted. Vs30 was found to vary from stiff to very dense soil along the profile, with higher values observed towards the left abutment.Keywords: earth dam; SPAC; MAM; S-wave; ambient noise. Autocorrelação Espacial de Dados Passivos de Ondas de Superfície para Avaliação de uma Barragem de Terra em Brasília, BrasilRESUMO. Métodos de onda de superfície são rotineiramente aplicados a problemas de engenharia para obtenção de estimativas de velocidade da onda S. A realização de levantamentos de Análise Multicanal de Ondas de Superfície (MASW) ativos convencionais para avaliação de barragens de terra sofrem limitações principalmente associadas à profundidade de investigação restrita e às influências negativas de fontes de ruído próximas. No Brasil, ocorre a necessidade de obter resultados em locais ruidosos com mais de 30 m de profundidade, que são contextos não ideais para as campanhas de sísmica ativa tradicionais. Dez minutos de dados de vibração ambiental foram registrados na crista de uma grande barragem de terra em Brasília, Distrito Federal. O método de Autocorrelação Espacial (SPAC) foi aplicado para desenvolver um modelo 2D da velocidade de onda S considerando ondas de superfície geradas a partir do tráfego de veículos na rodovia adjacente. Foi atingida uma profundidade máxima de 42 m e o modelo apresentou uma faixa de velocidade da onda S de 274 m/s a 713 m/s. Foram interpretados o nível freático, terreno de fundação e possíveis zonas anômalas de compactação baixa e mais elevada. Verificou-se que o Vs30 varia de solo rígido a muito denso ao longo do perfil, com valores mais altos observados em direção à ombreira esquerda.Palavras-chave: barragem de terra; SPAC; MAM; onda S; ruído ambiental.

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Section: Assumptions Around the Spac Methodsmentioning

confidence: 99%

Section: Data Processingmentioning

confidence: 99%

Spatial Autocorrelation of Passive Surface Wave Data for Assessment of an Earth Dam in Brasília, Brazil

et al. 2021

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“…Under the considering of 2D array, for example dense nodal array, SPAC method is flexible for various geometry configurations (Asten and Hayashi, 2018;Cho and Iwata, 2021) and can be extended to multicomponent recordings (Haney et al, 2012). Studies and applications also prove that SPAC method works for the linear array (Chávez-García et al, 2006;Margaryan et al, 2009;Kita et al, 2011), rather than the traditional SPAC (Aki, 1957) using a circle array or the two-station SPAC (Ekström et al, 2009;Hayashi et al, 2013), although they all share the same mathematical base of fitting the Bessel function (the function itself or the zero-crossing of the function) with the spatial autocorrelation coefficient. Recently, a similar technique, the frequency-Bessel (F-J) transform, attracts broad attentions from seismology and engineering communities due to the ability to improve higher modes with an appropriate spectral decomposition on the frequency-Bessel spectrogram (Forbriger, 2003;Wang et al, 2019;Hu et al, 2020;Wu et al, 2020;Xi et al, 2021).…”

Section: Introductionmentioning

confidence: 97%

Artifacts in high-frequency surface wave dispersion imaging

Cheng

Xia

2022

Preprint

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Surface wave methods are non-invasive, low-cost, and robust approaches to image near-surface S-wave velocity (Vs) structure.In terms of the energy source types, they can be classified in two groups: active-source surface wave methods and passive-source surface wave methods. A clean and high-resolution dispersion image is critical for the subsequent dispersion curve picking as well as Vs inversion for either the active-source surface wave methods or the passive-source surface wave methods. However, aliasing or other artifacts are almost inevitable in surface wave dispersion measurements in practice, and they can seriously pollute the measured dispersion spectra. It is significant to figure out how they are generated, how they affect the dispersion measurement, and how they can be attenuated. We provide the first comprehensive review on artifacts that are frequently observed in surface wave dispersion measurements, and summary them into three general types, including artifacts from spare spatial sampling, artifacts from array response, and artifacts from weak coherent signals. Both numerical and field examples, as well as mathematic derivations, are presented to help reader understand the generations of the various types artifacts and the way to attenuate them. This work will help us understand the complex components on the measured surface wave dispersion spectra, and lead to potential improvements on dispersion measurements.

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“…Park et al., 1999; Socco et al., 2010; Song et al., 1989; Xia et al., 1999); refraction microtremor—ReMi (Louie, 2001; Louie et al., 2021; Pancha et al., 2008), roadside passive multichannel analysis of surface wave‐PMASW (C. B. Park & Miller, 2008; C. Park et al., 2004), spatial autocorrelation‐SPAC (Aki, 1965; Chávez‐García et al., 2006; Hayashi et al., 2022; Kita et al., 2011; Margaryan et al., 2009; Okada & Suto, 2003), multichannel analysis of passive surface waves‐MAPS (Chen et al., 2022; Cheng et al., 2016; Dai et al., 2021; Y. Liu et al., 2020; Mi et al., 2022; Pang et al., 2019; Zhou et al., 2018). In the past two decades, the ambient noise interferometry technique has been widely employed for subsurface structure imaging using ambient seismic energy from natural or anthropogenic sources (e.g., Lehujeur et al., 2016; Lepore & Grad, 2020; F.‐C.…”

Section: Introductionmentioning

confidence: 99%

“…Park & Miller, 2008;C. Park et al, 2004), spatial autocorrelation-SPAC (Aki, 1965;Chávez-García et al, 2006;Hayashi et al, 2022;Kita et al, 2011;Margaryan et al, 2009;Okada & Suto, 2003), multichannel analysis of passive surface waves-MAPS (Chen et al, 2022;Cheng et al, 2016;Dai et al, 2021;Y. Liu et al, 2020;Mi et al, 2022;Pang et al, 2019;Zhou et al, 2018).…”

mentioning

confidence: 99%

High‐Resolution Near‐Surface Imaging at the Basin Scale Using Dark Fiber and Distributed Acoustic Sensing: Toward Site Effect Estimation in Urban Environments

Cheng,

Ajo‐Franklin,

Rodriguez Tribaldos

2023

JGR Solid Earth

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Near‐surface seismic structure, particularly the shear wave velocity (Vs), can strongly affect local site response, and should be accurately estimated for ground motion prediction during seismic hazard assessment. The Imperial Valley (California), occupying the southern end of the Salton Trough, is a seismically active basin with thick surficial lacustrine sedimentary deposits. In this study, we utilize ambient noise records and local earthquake events for high‐resolution near‐surface characterization and site effect estimation with an unlit fiber‐optic telecommunication infrastructure (dark fiber) in Imperial Valley by using the distributed acoustic sensing (DAS) technique. We apply ambient noise interferometry to retrieve coherent surface waves from DAS records, and evaluate performances of three different surface wave methods on DAS ambient noise dispersion imaging. We develop a quality control workflow to improve the dispersion measurement of noisy portions of the DAS dataset by using a data selection strategy. Using the joint inversion of both the fundamental mode and higher overtones of Rayleigh waves, a high resolution two‐dimensional (2D) Vs structure down to 70 m depth is obtained. We successfully achieve an improved Vs30 (the time‐averaged shear‐wave velocity in the top 30 m) model with higher spatial‐resolution and reliability compared to the existing community model for the area. We also explore the potential for utilizing DAS earthquake events for site amplification estimation. The preliminary results reveal a clear anti‐correlation between the approximated site response and the Vs30 profile. Our results indicate the potential utility of DAS deployed on dark fiber for near‐surface characterization in appropriate contexts.

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The Development of a 2‐Dimensional Microtremor Survey Method Based on SPAC Method Using Sequential Linear Arrays

Cited by 14 publications

References 3 publications

Spatial Autocorrelation of Passive Surface Wave Data for Assessment of an Earth Dam in Brasília, Brazil

Spatial Autocorrelation of Passive Surface Wave Data for Assessment of an Earth Dam in Brasília, Brazil

Artifacts in high-frequency surface wave dispersion imaging

High‐Resolution Near‐Surface Imaging at the Basin Scale Using Dark Fiber and Distributed Acoustic Sensing: Toward Site Effect Estimation in Urban Environments

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