Local station correlation: large N-arrays and DAS
DOI:
https://doi.org/10.26443/seismica.v2i2.389Keywords:
Correlations, Large-N arrays, Distributed acoustic sensing, surface wave dispersion, array condfigurationsAbstract
The use of cross-correlation between seismic stations has had widespread applications particularly in the exploitation of ambient seismic noise. We here show how the effects of a non-ideal noise distribution can be understood by looking directly at correlation properties and show how the behaviour can be readily visualised for both seismometer and DAS configurations, taking into account directivity effects. For sources lying in a relatively narrow cone around the extension of the inter-station path, the dispersion properties of the correlation relate directly to the zone between the stations. We illustrate the successful use of correlation analysis for both a large-N array perpendicular to a major highway and DAS cable along a busy road. For correlation work, the co-array consisting of the ensemble of inter-station vectors provides an effective means of assessing the behaviour of array layouts, supplementing the standard plane-wave array response. When combined with knowledge of the suitable correlation zones for noise sources, the co-array concept provides a useful way to design array configurations for both seismometer arrays and DAS.
References
Bensen, G. D., Ritzwoller, M. H., Barmin, M. P., Levshin, A. L., Lin, F., Moschetti, M. P., Shapiro, N. M., & Yang, Y. (2007). Processing seismic ambient noise data to obtain reliable broad-band surface wave dispersion measurements. Geophysical Journal International, 169(3), 1239–1260. https://doi.org/10.1111/j.1365-246X.2007.03374.x DOI: https://doi.org/10.1111/j.1365-246X.2007.03374.x
Cheng, F., Xia, J., Zhang, K., Zhou, C., & Ajo-Franklin, J. B. (2021). Phase-weighted slant stacking for surface wave dispersion measurement. Geophysical Journal International, 226(1), 256–269. https://doi.org/10.1093/gji/ggab101 DOI: https://doi.org/10.1093/gji/ggab101
Chmiel, M., Mordret, A., Boué, P., Brenguier, F., Lecocq, T., Courbis, R., Hollis, D., Campman, X., Romijn, R., & Van der Veen, W. (2019). Ambient noise multimode Rayleigh and Love wave tomography to determine the shear velocity structure above the Groningen gas field. Geophysical Journal International, 218(3), 1781–1795. https://doi.org/10.1093/gji/ggz237 DOI: https://doi.org/10.1093/gji/ggz237
Dou, S., Lindsey, N., Wagner, A. M., Daley, T. M., Freifeld, B., Robertson, M., Peterson, J., Ulrich, C., Martin, E. R., & Ajo-Franklin, J. B. (2017–9). Distributed Acoustic Sensing for Seismic Monitoring of The Near Surface: A Traffic-Noise Interferometry Case Study. Scientific Reports, 7(1), 11620. https://doi.org/10.1038/s41598-017-11986-4 DOI: https://doi.org/10.1038/s41598-017-11986-4
Dougherty, S. L., Cochran, E. S., & Harrington, R. M. (2019). The LArge‐n Seismic Survey in Oklahoma (LASSO) Experiment. Seismological Research Letters, 90(5), 2051–2057. https://doi.org/10.1785/0220190094 DOI: https://doi.org/10.1785/0220190094
Fang, J., Yang, Y., Shen, Z., Biondi, E., Wang, X., Williams, E. F., Becker, M. W., Eslamian, D., & Zhan, Z. (2022). Directional Sensitivity of DAS and Its Effect on Rayleigh‐Wave Tomography: A Case Study in Oxnard, California. Seismological Research Letters, 94(2A), 887–897. https://doi.org/10.1785/0220220235 DOI: https://doi.org/10.1785/0220220235
Fichtner, A., & Tsai, V. (2019). Theoretical Foundations of Noise Interferometry. In Seismic Ambient Noise (pp. 109–143). Cambridge University Press. https://doi.org/10.1017/9781108264808.006 DOI: https://doi.org/10.1017/9781108264808.006
Gribler, G., & Mikesell, T. D. (2019). Methods to isolate retrograde and prograde Rayleigh-wave signals. Geophysical Journal International, 219(2), 975–994. https://doi.org/10.1093/gji/ggz341 DOI: https://doi.org/10.1093/gji/ggz341
Halliday, D., & Curtis, A. (2008). Seismic interferometry, surface waves and source distribution. Geophysical Journal International, 175(3), 1067–1087. https://doi.org/10.1111/j.1365-246X.2008.03918.x DOI: https://doi.org/10.1111/j.1365-246X.2008.03918.x
Haubrich, R. A. (1968). Array design. Bulletin of the Seismological Society of America, 58(3), 977–991. https://doi.org/10.1785/BSSA0580030977 DOI: https://doi.org/10.1785/BSSA0580030977
Jiang, C., & Denolle, M. A. (2020). NoisePy: A New High‐Performance Python Tool for Ambient‐Noise Seismology. Seismological Research Letters, 91(3), 1853–1866. https://doi.org/10.1785/0220190364 DOI: https://doi.org/10.1785/0220190364
Jiang, C., & Denolle, M. A. (2022). Pronounced Seismic Anisotropy in Kanto Sedimentary Basin: A Case Study of Using Dense Arrays, Ambient Noise Seismology, and Multi-Modal Surface-Wave Imaging. Journal of Geophysical Research: Solid Earth, 127(8), e2022JB024613. https://doi.org/https://doi.org/10.1029/2022JB024613 DOI: https://doi.org/10.1029/2022JB024613
Kennett, B. L. N. (2022). The seismic wavefield as seen by distributed acoustic sensing arrays: local, regional and teleseismic sources. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 478(2258), 20210812. https://doi.org/10.1098/rspa.2021.0812 DOI: https://doi.org/10.1098/rspa.2021.0812
Kennett, B. L. N., Stipčević, J., & Gorbatov, A. (2015). Spiral‐Arm Seismic Arrays. Bulletin of the Seismological Society of America, 105(4), 2109–2116. https://doi.org/10.1785/0120140354 DOI: https://doi.org/10.1785/0120140354
Kennett, Brian L. N., & Fichtner, A. (2020). Exploiting Seismic Waveforms: Correlation, Heterogeneity and Inversion. Cambridge University Press. https://doi.org/10.1017/9781108903035 DOI: https://doi.org/10.1017/9781108903035
Ketterhals, P., Haefeli, C., & Staeger, D. (2000). Blatt 1166 Bern. Geologisches Atlas der Schweiz 1:25000, Karte 100. https://www.swisstopo.admin.ch/en/geodata/geology/maps/ga25/raster.html
Lancelle, C. E., Baldwin, J. A., Lord, N., Fratta, D., Chalari, A., & Wang, H. F. (2021). Using Distributed Acoustic Sensing (DAS) for Multichannel Analysis of Surface Waves (MASW). In Distributed Acoustic Sensing in Geophysics (pp. 213–228). American Geophysical Union (AGU). https://doi.org/10.1002/9781119521808.ch16 DOI: https://doi.org/10.1002/9781119521808.ch16
Lobkis, O. I., & Weaver, R. L. (2001). On the emergence of the Green’s function in the correlations of a diffuse field. The Journal of the Acoustical Society of America, 110(6), 3011–3017. https://doi.org/10.1121/1.1417528 DOI: https://doi.org/10.1121/1.1417528
Maranò, S., Fäh, D., & Lu, Y. M. (2014). Sensor placement for the analysis of seismic surface waves: sources of error, design criterion and array design algorithms. Geophysical Journal International, 197(3), 1566–1581. https://doi.org/10.1093/gji/ggt489 DOI: https://doi.org/10.1093/gji/ggt489
Martin, E. R., Lindsey, N. J., Ajo-Franklin, J. B., & Biondi, B. L. (2021). Introduction to Interferometry of Fiber-Optic Strain Measurements. In Distributed Acoustic Sensing in Geophysics (pp. 111–129). American Geophysical Union (AGU). https://doi.org/10.1002/9781119521808.ch9 DOI: https://doi.org/10.1002/9781119521808.ch9
Nakata, N., Gualtieri, L., & Fichtner, A. (Eds.). (2019). Seismic Ambient Noise. Cambridge University Press. https://doi.org/10.1017/9781108264808 DOI: https://doi.org/10.1017/9781108264808
Näsholm, S. P., Iranpour, K., Wuestefeld, A., Dando, B. D. E., Baird, A. F., & Oye, V. (2022). Array Signal Processing on Distributed Acoustic Sensing Data: Directivity Effects in Slowness Space. Journal of Geophysical Research: Solid Earth, 127(2), e2021JB023587. https://doi.org/10.1029/2021JB023587 DOI: https://doi.org/10.1029/2021JB023587
Nayak, A., & Thurber, C. H. (2020). Using multicomponent ambient seismic noise cross-correlations to identify higher mode Rayleigh waves and improve dispersion measurements. Geophysical Journal International, 222(3), 1590–1605. https://doi.org/10.1093/gji/ggaa270 DOI: https://doi.org/10.1093/gji/ggaa270
Park, Choon B., Miller, R. D., & Xia, J. (1999). Multichannel analysis of surface waves. Geophysics, 64(3), 800–808. https://doi.org/10.1190/1.1444590 DOI: https://doi.org/10.1190/1.1444590
Park, Choon Byong, Miller, R. D., & Xia, J. (1998). Imaging dispersion curves of surface waves on multi‐channel record. In SEG Technical Program Expanded Abstracts 1998 (pp. 1377–1380). Society of Exploration Geophysicists. https://doi.org/10.1190/1.1820161 DOI: https://doi.org/10.1190/1.1820161
Quiros, D. A., Brown, L. D., & Kim, D. (2016). Seismic interferometry of railroad induced ground motions: body and surface wave imaging. Geophysical Journal International, 205(1), 301–313. https://doi.org/10.1093/gji/ggw033 DOI: https://doi.org/10.1093/gji/ggw033
Sager, K., Ermert, L., Boehm, C., & Fichtner, A. (2017). Towards full waveform ambient noise inversion. Geophysical Journal International, 212(1), 566–590. https://doi.org/10.1093/gji/ggx429 DOI: https://doi.org/10.1093/gji/ggx429
Snieder, R. (2004). Extracting the Green’s function from the correlation of coda waves: A derivation based on stationary phase. Phys. Rev. E, 69(4), 046610. https://doi.org/10.1103/PhysRevE.69.046610 DOI: https://doi.org/10.1103/PhysRevE.69.046610
Takagi, R., Nakahara, H., Kono, T., & Okada, T. (2014). Separating body and Rayleigh waves with cross terms of the cross-correlation tensor of ambient noise. Journal of Geophysical Research: Solid Earth, 119(3), 2005–2018. https://doi.org/10.1002/2013JB010824 DOI: https://doi.org/10.1002/2013JB010824
van den Ende, M. P. A., & Ampuero, J.-P. (2021). Evaluating seismic beamforming capabilities of distributed acoustic sensing arrays. Solid Earth, 12(4), 915–934. https://doi.org/10.5194/se-12-915-2021 DOI: https://doi.org/10.5194/se-12-915-2021
van Wijk, K., Mikesell, T. D., Schulte-Pelkum, V., & Stachnik, J. (2011). Estimating the Rayleigh-wave impulse response between seismic stations with the cross terms of the Green tensor. Geophysical Research Letters, 38(16). https://doi.org/10.1029/2011GL047442 DOI: https://doi.org/10.1029/2011GL047442
Wapenaar, K. (2004). Retrieving the Elastodynamic Green’s Function of an Arbitrary Inhomogeneous Medium by Cross Correlation. Phys. Rev. Lett., 93(25), 254301. https://doi.org/10.1103/PhysRevLett.93.254301 DOI: https://doi.org/10.1103/PhysRevLett.93.254301
Wapenaar, K., & Fokkema, J. (2006). Green’s function representations for seismic interferometry. Geophysics, 71(4), SI33–SI46. https://doi.org/10.1190/1.2213955 DOI: https://doi.org/10.1190/1.2213955
Weaver, R. L. (2010–10). Equipartition and retrieval of Green’s function. Earthquake Science, 23(5), 397–402. https://doi.org/10.1007/s11589-010-0738-2 DOI: https://doi.org/10.1007/s11589-010-0738-2
Yang, Y., Atterholt, J. W., Shen, Z., Muir, J. B., Williams, E. F., & Zhan, Z. (2022). Sub-Kilometer Correlation Between Near-Surface Structure and Ground Motion Measured With Distributed Acoustic Sensing. Geophysical Research Letters, 49(1), e2021GL096503. https://doi.org/10.1029/2021GL096503 DOI: https://doi.org/10.1029/2021GL096503
Zhang, K., Li, H., Wang, X., & Wang, K. (2020). Retrieval of shallow S-wave profiles from seismic reflection surveying and traffic-induced noise. Geophysics, 85(6), EN105–EN117. https://doi.org/10.1190/geo2019-0845.1 DOI: https://doi.org/10.1190/geo2019-0845.1
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Copyright (c) 2023 Brian Kennett, Chengxin Jiang, Krystyna Smolinski
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Australian Research Council
Grant numbers DE220100907 -
Horizon 2020
Grant numbers 821115