城镇地区短期同步-异步背景噪声层析成像——岩溶调查中的应用

Ya Liu, Jianghai Xia, Bo Guan, Chaoqiang Xi, Ling Ning, Hao Zhang

工程(英文) ›› 2025, Vol. 48 ›› Issue (5) : 292-308.

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工程(英文) ›› 2025, Vol. 48 ›› Issue (5) : 292-308. DOI: 10.1016/j.eng.2025.02.001
Article

 城镇地区短期同步-异步背景噪声层析成像——岩溶调查中的应用

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Short-Term Synchronous and Asynchronous Ambient Noise Tomography in Urban Areas: Application to Karst Investigation

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Abstract

Dense-array ambient noise tomography is a powerful tool for achieving high-resolution subsurface imaging, significantly impacting geohazard prevention and control. Conventional dense-array studies, however, require simultaneous observations of numerous stations for extensive coverage. To conduct a comprehensive karst feature investigation with limited stations, we designed a new synchronous–asynchronous observation system that facilitates dense array observations. We conducted two rounds of asynchronous observations, each lasting approximately 24 h, in combination with synchronous backbone stations. We achieved wide-ranging coverage of the study area utilizing 197 nodal receivers, with an average station spacing of 7 m. The beamforming results revealed distinct variations in the noise source distributions between day and night. We estimated the source strength in the stationary phase zone and used a weighting scheme for stacking the cross-correlation functions (C1 functions) to suppress the influence of nonuniform noise source distributions. The weights were derived from the similarity coefficients between multicomponent C1 functions related to Rayleigh waves. We employed the cross-correlation of C1 functions (C2 methods) to obtain the empirical Green’s functions between asynchronous stations. To eliminate artifacts in C2 functions from higher-mode surface waves in C1 functions, we filtered the C1 functions on the basis of different particle motions linked to multimode Rayleigh waves. The dispersion measurements of Rayleigh waves obtained from both the C1 and C2 functions were utilized in surface wave tomography. The inverted three-dimensional (3D) shear-wave (S-wave) velocity model reveals two significant low-velocity zones at depths ranging from 40 to 60 m, which align well with the karst caves found in the drilling data. The method of short-term synchronous–asynchronous ambient noise tomography shows promise as a cost-effective and efficient approach for urban geohazard investigations.

Keywords

Seismic interferometry / Surface wave tomography / Asynchronous ambient noise / Geohazards / Seismic ambient noise

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Ya Liu, Jianghai Xia, Bo Guan. . Engineering. 2025, 48(5): 292-308 https://doi.org/10.1016/j.eng.2025.02.001

参考文献

[1]
Weaver RL, Lobkis OI.Ultrasonics without a source: thermal fluctuation correlations at MHz frequencies.Phys Rev Lett 2001; 87(13):134301.
[2]
Campillo M, Paul A.Long-range correlations in the diffuse seismic coda.Science 2003; 299(5606):547-549.
[3]
Snieder R.Extracting the Green’s function from the correlation of coda waves: a derivation based on stationary phase.Phys Rev E Stat Nonlin Soft Matter Phys 2004; 69(4):046610.
[4]
Sabra KG, Gerstoft P, Roux P, Kuperman WA, Fehler MC.Extracting time-domain Green’s function estimates from ambient seismic noise.Geophys Res Lett 2005; 32(3):L03310.
[5]
Shapiro NM, Campillo M, Stehly L, Ritzwoller MH.High-resolution surface-wave tomography from ambient seismic noise.Science 2005; 307(5715):1615-1618.
[6]
Wapenaar K, Draganov D, Snieder R, Campman X, Verdel A.Tutorial on seismic interferometry: part 1—basic principles and applications.Geophysics 2010; 75(5):75A195-209.
[7]
Yao H, van RD der Hilst, de MV Hoop.Surface-wave array tomography in southeast Xizang from ambient seismic noise and two-station analysis—I.Phase velocity maps. Geophys J Int 2006; 166(2):732-744.
[8]
Yang Y, Ritzwoller MH, Levshin AL, Shapiro NM.Ambient noise Rayleigh wave tomography across Europe.Geophys J Int 2007; 168(1):259-274.
[9]
Rawlinson N, Salmon M, Kennett BLN.Transportable seismic array tomography in southeast Australia: illuminating the transition from Proterozoic to Phanerozoic lithosphere.Lithos 2014; 189:65-76.
[10]
Bao X, Song X, Li J.High-resolution lithospheric structure beneath China’s mainland from ambient noise and earthquake surface-wave tomography.Earth Planet Sci Lett 2015; 417:132-141.
[11]
Luo S, Yao H, Li Q, Wang W, Wan K, Meng Y, et al.High-resolution 3D crustal S-wave velocity structure of the Middle-Lower Yangtze River metallogenic belt and implications for its deep geodynamic setting.Sci China Earth Sci 2019; 62(9):1361-1378.
[12]
Nimiya H, Ikeda T, Tsuji T.Three-dimensional s wave velocity structure of central Japan estimated by surface-wave tomography using ambient noise.J GeophysRes Solid Earth 2020; 125:e2019JB019043.
[13]
Gaite B, Iglesias A, Villaseñor A, Herraiz M, Pacheco JF.Crustal structure of Mexico and surrounding regions from seismic ambient noise tomography.Geophys J Int 2012; 188(3):1413-1424.
[14]
Haned A, Stutzmann E, Schimmel M, Kiselev S, Davaille A, Yelles-Chaouche A.Global tomography using seismic hum.Geophys J Int 2016; 204(2):1222-1236.
[15]
Li C, Yao H, Fang H, Huang X, Wan K, Zhang H, et al.3D near‐surface shear‐wave velocity structure from ambient‐noise tomography and borehole data in the Hefei urban area.China. Seismol Res Lett 2016; 87(4):882-892.
[16]
Sun R, Li J, Yan Y, Liu H, Bai L, Chen Y.Three-dimensional urban subsurface space tomography with dense ambient noise seismic array.Surv Geophys 2024; 45(3):819-843.
[17]
Nakata N.Near-surface S-wave velocities estimated from traffic-induced Love waves using seismic interferometry with double beamforming.
[18]
Xia S, Zhang C, Cao J.Ambient noise tomography for coral islands.
[19]
Carvalho J, Silveira G, Dumont S, Ramalho R.3D-ambient noise surface wave tomography of Fogo volcano.Cape Verde. J Volcanol Geotherm Res 2022; 432:107702.
[20]
Lehujeur M, Vergne J, Schmittbuhl J, Zigone D, LeChenadec A.EstOF Team. Reservoir imaging using ambient noise correlation from a dense seismic network.J Geophys Res Solid Earth 2018; 123(8):6671-6686.
[21]
Cheng F, Xia J, Ajo-Franklin JB, Behm M, Zhou C, Dai T, et al.High‐resolution ambient noise imaging of geothermal reservoir using 3C dense seismic nodal array and ultra‐short observation.
[22]
Zhou C, Xia J, Pang J, Cheng F, Chen X, Xi C, et al.Near-surface geothermal reservoir imaging based on the customized dense seismic network.Surv Geophys 2021; 42(3):673-697.
[23]
Gu N, Wang K, Gao J, Ding N, Yao H, Zhang H.Shallow crustal structure of the Tanlu fault zone near Chao Lake in eastern China by direct surface wave tomography from local dense array ambient noise analysis.Pure Appl Geophys 2019; 176(3):1193-1206.
[24]
Guan B, Mi B, Zhang H, Liu Y, Xi C, Zhou C.Selection of noise sources and short-time passive surface wave imaging—a case study on fault investigation.J Appl Geophys 2021; 194:104437.
[25]
Ning L, Dai T, Liu Y, Xi C, Zhang H, Zhou C.Application of multichannel analysis of passive surface waves method for fault investigation.J Appl Geophys 2021; 192:104382.
[26]
Park CB, Miller RD.Roadside passive multichannel analysis of surface waves (MASW).J Eng Environ Geophys 2008; 13(1):1-11.
[27]
Nakata N, Snieder R, Tsuji T, Larner K, Matsuoka T.Shear wave imaging from traffic noise using seismic interferometry by cross-coherence.
[28]
Cheng F, Xia J, Xu Z, Hu Y, Mi B.Frequency–wavenumber (FK)-based data selection in high-frequency passive surface wave survey.Surv Geophys 2018; 39(4):661-682.
[29]
Liu Y, Xia J, Xi C, Dai T, Ning L.Improving the retrieval of high-frequency surface waves from ambient noise through multichannel-coherency-weighted stack.Geophys J Int 2021; 227(2):776-785.
[30]
Mi B, Xia J, Tian G, Shi Z, Xing H, Chang X, et al.Near-surface imaging from traffic-induced surface waves with dense linear arrays: an application in the urban area of Hangzhou.China. Geophysics 2022; 87(2):B145-B158.
[31]
Cheng F, Xia J, Shen C, Hu Y, Xu Z, Mi B.Imposing active sources during high-frequency passive surface-wave measurement.Engineering 2018; 4(5):685-693.
[32]
Waltham T, Bell FG, Culshaw MG, Knez M, Slabe T.Sinkholes and subsidence: karst and cavernous rocks in engineering and construction.
[33]
Weary D.The cost of karst subsidence and sinkhole collapse in the United States compared with other natural hazards.In: Proceedings of the Fourteenth Multidisciplinary Conference; 2015 Oct 5–6; Rochester, M N, US A. Tampa: University of South Florida Tampa Library; 2015. p. 433–46.
[34]
Zhang R, Ai T, Ren L, Li G.Failure characterization of three typical coal-bearing formation rocks using acoustic emission monitoring and X-ray computed tomography techniques.Rock Mech Rock Eng 2019; 52(6):1945-1958.
[35]
Dong L, Tong X, Ma J.Quantitative investigation of tomographic effects in abnormal regions of complex structures.Engineering 2021; 7(7):1011-1022.
[36]
Dong L, Pei Z, Xie X, Zhang Y, Yan X.Early identification of abnormal regions in rock-mass using traveltime tomography.Engineering 2023; 22(3):191-200.
[37]
Hiltunen DR, Cramer BJ.Application of seismic refraction tomography in karst terrane.J Geotech Geoenviron Eng 2008; 134(7):938-948.
[38]
Aati AHA, Shabaan SH.Detection of karstic limestone bedrock by shallow seismic refraction in an area west of Assiut, middle Egypt.Leading Edge (Tulsa Okla) 2013; 32(3):316-322.
[39]
Peng D, Cheng F, Liu J, Zong Y, Yu M, Hu G, et al.Joint tomography of multi-cross-hole and borehole-to-surface seismic data for karst detection.J Appl Geophys 2021; 184:104252.
[40]
Zhang J, Liu S, Chen Q, Wang B, Ren C.Application of cross-borehole integrated geophysical methods for the detailed investigation of karst in urban metro construction.JEEG 2019; 24(4):525-536.
[41]
Shangxin F, Yufei Z, Yujie W, Shanyong W, Ruilang C.A comprehensive approach to karst identification and groutability evaluation—a case study of the Dehou reservoir.SW China. Eng Geol 2020; 269:105529.
[42]
Gan F, Han K, Lan F, Chen Y, Zhang W.Multi-geophysical approaches to detect karst channels underground—a case study in Mengzi of Yunnan Province.China. J Appl Geophys 2017; 136:91-98.
[43]
Foudili D, Bouzid A, Berguig MC, Bougchiche SS, Abtout A, Guemache MA.Investigating karst collapse geohazards using magnetotellurics: a case study of M’rara basin.Algerian Sahara. J Appl Geophys 2019; 160:144-156.
[44]
Kiernan M, Jackson D, Montgomery J, Anderson JB, McDonald BW, Davis KC.Characterization of a karst site using electrical resistivity tomography and seismic full waveform inversion.JEEG 2021; 26(1):1-11.
[45]
Xia J, Chen C, Li P, Lewis M.Delineation of a collapse feature in a noisy environment using a multichannel surface wave technique.Geotechnique 2004; 54(1):17-27.
[46]
Parker EH Jr, Hawman RB.Multi-channel analysis of surface waves (MASW) in karst terrain, southwest Georgia: implications for detecting anomalous features and fracture zones.J Environ Eng Geophys 2012; 17(3):129-150.
[47]
Chang JP, de SAL Ridder, Biondi BL.High-frequency Rayleigh-wave tomography using traffic noise from Long Beach.California. Geophysics 2016; 81(2):B43-B53.
[48]
Wang Y, Lin FC, Schmandt B, Farrell J.Ambient noise tomography across Mount St. Helens using a dense seismic array.J Geophys Res Solid Earth 2017; 122(6):4492-4508.
[49]
Fu L, Pan L, Li Z, Dong S, Ma Q, Chen X.Improved high-resolution 3D vs model of Long Beach, CA: inversion of multimodal dispersion curves from ambient noise of a dense array.Geophys Res Lett 2022;49:e2021G L097619.
[50]
Stehly L, Campillo M, Froment B, Weaver RL.Reconstructing Green’s function by correlation of the coda of the correlation (C3) of ambient seismic noise.J Geophys Res 2008; 113(B11):B11306.
[51]
Curtis A, Halliday D.Source-receiver wave field interferometry.Phys Rev E Stat Nonlin Soft Matter Phys 2010; 81(4):046601.
[52]
Froment B, Campillo M, Roux P.Reconstructing the Green’s function through iteration of correlations.C R Geosci 2011; 343(8–9):623-632.
[53]
Spica Z, Perton M, Cal Mò, Legrand D, Córdoba-Montiel F, Iglesias A.3-D shear wave velocity model of Mexico and south US: bridging seismic networks with ambient noise cross-correlations (C1) and correlation of coda of correlations (C3).Geophys J Int 2016; 206(3):1795-1813.
[54]
Ansaripour M, Rezapour M, Saygin E.Shear wave velocity structure of Iranian plateau: using combination of ambient noise cross-correlations (C1) and correlation of coda of correlations (C3).Geophys J Int 2019; 218(3):1919-1938.
[55]
Chen Y, Saygin E.Empirical Green’s function retrieval using ambient noise source‐receiver interferometry.J Geophys Res Solid Earth 2020;125(2):e2019J B018261.
[56]
Zhang S, Feng L, Ritzwoller MH.Three-station interferometry and tomography: coda versus direct waves.Geophys J Int 2020; 221(1):521-541.
[57]
Rao H, Luo Y, Zhao K, Yang Y.Extracting surface wave dispersion curves from asynchronous seismic stations: method and application.Geophys J Int 2021; 226(2):1148-1158.
[58]
Chen Y, Saygin E, Kennett B, Qashqai MT, Hauser J, Lumley D, et al.Next-generation seismic model of the Australian crust from synchronous and asynchronous ambient noise imaging.Nat Commun 2023; 14(1):1192.
[59]
Boschi L, Weemstra C.Stationary-phase integrals in the cross correlation of ambient noise.Rev Geophys 2015; 53(2):411-451.
[60]
Liu Y, Xia J, Cheng F, Xi C, Shen C, Zhou C.Pseudo-linear-array analysis of passive surface waves based on beamforming.Geophys J Int 2020; 221(1):640-650.
[61]
Cheng F, Xia J, Luo Y, Xu Z, Wang L, Shen C, et al.Multichannel analysis of passive surface waves based on crosscorrelations.
[62]
Zhang H, Mi B, Xi C, Liu Y, Guan B, Ning L.Extraction of surface-wave phase velocities from ambient noise in the presence of local noise sources based on matched-field processing.J Appl Geophys 2022; 204:104755.
[63]
Ning L, Xia J, Dai T, Liu Y, Zhang H, Xi C.High-frequency surface-wave imaging from traffic-induced noise by selecting in-line sources.Surv Geophys 2022; 43(6):1873-1899.
[64]
Liu Y, Xia J, Xi C, Zhang H, Guan B, Dai T, et al.Enhancing noise sources in stationary-phase zones for accurate phase-velocity estimation of high-frequency surface waves.Geophysics 2023; 88(1):L1-L9.
[65]
Nayak A, Thurber CH.Using multicomponent ambient seismic noise cross-correlations to identify higher mode Rayleigh waves and improve dispersion measurements.Geophys J Int 2020; 222(3):1590-1605.
[66]
Lin FC, Moschetti MP, Ritzwoller MH.Surface wave tomography of the western United States from ambient seismic noise: Rayleigh and Love wave phase velocity maps.Geophys J Int 2008; 173(1):281-298.
[67]
Gribler G, Mikesell TD.Methods to isolate retrograde and prograde Rayleigh-wave signals.Geophys J Int 2019; 219(2):975-994.
[68]
Herrmann RB.Computer programs in seismology: an evolving tool for instruction and research.Seismol Res Lett 2013; 84(6):1081-1088.
[69]
Bensen GD, Ritzwoller MH, Barmin MP, Levshin AL, Lin F, Moschetti MP, et al.Processing seismic ambient noise data to obtain reliable broad-band surface wave dispersion measurements.Geophys J Int 2007; 169(3):1239-1260.
[70]
Park CB, Miller RD, Xia J..
[71]
Gribler G, Liberty LM, Mikesell TD, Michaels P.Isolating retrograde and prograde Rayleigh-wave modes using a polarity mute.Geophysics 2016; 81(5):V379-V385.
[72]
Schimmel M, Paulssen H.Noise reduction and detection of weak, coherent signals through phase-weighted stacks.Geophys J Int 1997; 130(2):497-505.
[73]
Yao H, Gou Pédard, Collins JA, McGuire JJ, van RD der Hilst.Structure of young East Pacific rise lithosphere from ambient noise correlation analysis of fundamental- and higher-mode Scholte-Rayleigh waves.C R Geosci 2011; 343(8–9):571-583.
[74]
Luo Y, Yang Y, Xu Y, Xu H, Zhao K, Wang K.On the limitations of interstation distances in ambient noise tomography.Geophys J Int 2015; 201(2):652-661.
[75]
Fang H, Yao H, Zhang H, Huang YC, van RD der Hilst.Direct inversion of surface wave dispersion for three-dimensional shallow crustal structure based on ray tracing: methodology and application.Geophys J Int 2015; 201(3):1251-1263.
[76]
Luo Y, Xia J, Miller RD, Xu Y, Liu J, Liu Q.Rayleigh-wave mode separation by high-resolution linear Radon transform.Geophys J Int 2009; 179(1):254-264.
[77]
Brocher TM.Empirical relations between elastic wavespeeds and density in the earth’s crust.Bull Seismol Soc Am 2005; 95(6):2081-2092.
[78]
Li J, Feng Z, Schuster G.Wave-equation dispersion inversion.Geophys J Int 2017; 208(3):1567-1578.
[79]
Pan Y, Gao L, Bohlen T.Random-objective waveform inversion of 3D–9C shallow-seismic field data.J Geophys Res Solid Earth 2021; 126:e2021JB022036.
[80]
Xia J, Miller RD, Park CB, Tian G.Inversion of high frequency surface waves with fundamental and higher modes.J Appl Geophys 2003; 52(1):45-57.
[81]
Pan L, Chen X, Wang J, Yang Z, Zhang D.Sensitivity analysis of dispersion curves of Rayleigh waves with fundamental and higher modes.Geophys J Int 2019; 216(2):1276-1303.
[82]
Liu Q, Chen X, Gao L, Yu Z, Chen J.Direct image dissimilarity inversion of ambient noise multimodal dispersion spectrograms.Bull Seismol Soc Am 2023; 113(5):1960-1981.
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