An analysis of the dynamic range of Distributed Acoustic Sensing for Earthquake Early Warning
DOI:
https://doi.org/10.26443/seismica.v4i1.1371Keywords:
Distributed Acoustic Sensing, Earthquake Early WarningAbstract
Owing to its deployment and sensing characteristics, Distributed Acoustic Sensing (DAS) has been touted as a promising technology for low-cost and low-latency Earthquake Early Warning (EEW). While preliminary experiments conducted by several research groups have yielded encouraging results, it must be acknowledged that these EEW feasibility studies were performed only on low-magnitude events. When exposed to the wavefield of a large magnitude earthquake (being the prime subject of EEW), the DAS strain rate recordings are likely to become highly distorted ("saturated") due to cycle skipping of the optical phase measurements, to an extent that the recorded data start to degrade to uniform random noise. This clearly poses a major challenge to EEW, as neither amplitude nor phase information can be readily extracted from saturated DAS data. In this study, we perform a detailed analysis of the dynamic range of DAS, both from theoretical and practical perspectives. We offer a set of criteria that need to be met for matching the DAS dynamic range with EEW targets, and we propose a computationally convenient method to quantify the information content of saturated recordings. We apply these methods to DAS data recorded offshore Chile, and identify several avenues for future research to improve the feasibility of DAS for EEW.
References
Abukrat, Y., Sinitsyn, P., Reshef, M., & Lellouch, A. (2023). Applications and Limitations of Distributed Acoustic Sensing in Shallow Seismic Surveys and Monitoring. GEOPHYSICS, 88(6), WC1–WC12. https://doi.org/10.1190/geo2022-0574.1
Allen, R. M., & Melgar, D. (2019). Earthquake Early Warning: Advances, Scientific Challenges, and Societal Needs. Annual Review of Earth and Planetary Sciences, 47(1), 361–388. https://doi.org/10.1146/annurev-earth-053018-060457
Anderson, J. G., & Hough, S. E. (1984). A Model for the Shape of the Fourier Amplitude Spectrum of Acceleration at High Frequencies. Bulletin of the Seismological Society of America, 74(5), 1969–1993. https://doi.org/10.1785/BSSA0740051969
Bradbury, J., Frostig, R., Hawkins, P., Johnson, M. J., Leary, C., Maclaurin, D., Necula, G., Paszke, A., Van der Plas, J., Wanderman-Milne, S., & Zhang, Q. (2020). JAX: Composable Transformations of Python+NumPy Programs. http://github.com/jax-ml/jax
Brune, J. N. (1970). Tectonic Stress and the Spectra of Seismic Shear Waves from Earthquakes. Journal of Geophysical Research (1896-1977), 75(26), 4997–5009. https://doi.org/10.1029/JB075i026p04997
Crameri, F., Shephard, G. E., & Heron, P. J. (2020). The Misuse of Colour in Science Communication. Nature Communications, 11(1), 5444. https://doi.org/10.1038/s41467-020-19160-7
Cummins, P. R., & Kaneda, Y. (2000). Possible Splay Fault Slip during the 1946 Nankai Earthquake. Geophysical Research Letters, 27(17), 2725–2728. https://doi.org/10.1029/1999GL011139
Daley, T. M., Miller, D. E., Dodds, K., Cook, P., & Freifeld, B. M. (2016). Field Testing of Modular Borehole Monitoring with Simultaneous Distributed Acoustic Sensing and Geophone Vertical Seismic Profiles at Citronelle, Alabama. Geophysical Prospecting, 64(5), 1318–1334. https://doi.org/10.1111/1365-2478.12324
Diaz-Meza, S., Jousset, P., Currenti, G., Wollin, C., Krawczyk, C., Clarke, A., & Chalari, A. (2023). On the Comparison of Records from Standard and Engineered Fiber Optic Cables at Etna Volcano (Italy). Sensors, 23(7), 3735. https://doi.org/10.3390/s23073735
Farghal, N. S., Saunders, J. K., & Parker, G. A. (2022). The Potential of Using Fiber Optic Distributed Acoustic Sensing (DAS) in Earthquake Early Warning Applications. Bulletin of the Seismological Society of America, 112(3), 1416–1435. https://doi.org/10.1785/0120210214
Hananto, N. D., Leclerc, F., Li, L., Etchebes, M., Carton, H., Tapponnier, P., Qin, Y., Avianto, P., Singh, S. C., & Wei, S. (2020). Tsunami Earthquakes: Vertical Pop-up Expulsion at the Forefront of Subduction Megathrust. Earth and Planetary Science Letters, 538, 116197. https://doi.org/10.1016/j.epsl.2020.116197
Hanks, T. C., & Kanamori, H. (1979). A Moment Magnitude Scale. Journal of Geophysical Research: Solid Earth, 84(B5), 2348–2350. https://doi.org/10.1029/JB084iB05p02348
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río, J. F., Wiebe, M., Peterson, P., … Oliphant, T. E. (2020). Array Programming with NumPy. Nature, 585(7825), 357–362. https://doi.org/10.1038/s41586-020-2649-2
Hartog, A. H. (2017). An Introduction to Distributed Optical Fibre Sensors. CRC Press. https://doi.org/10.1201/9781315119014
Hunter, J. D. (2007). Matplotlib: A 2D Graphics Environment. Computing in Science & Engineering, 9(3), 90–95. https://doi.org/10.1109/MCSE.2007.55
Kong, L., Pan, X., Ren, Z., & Cui, K. (2022). Robust One-Dimensional Phase Unwrapping Algorithm Based on LSTM Network With Reduced Parameter Number. Journal of Lightwave Technology, 40(19), 6560–6567. https://doi.org/10.1109/JLT.2022.3195932
Li, J., Kim, T., Lapusta, N., Biondi, E., & Zhan, Z. (2023). The Break of Earthquake Asperities Imaged by Distributed Acoustic Sensing. Nature, 620(7975), 800–806. https://doi.org/10.1038/s41586-023-06227-w
Li, J., Zhu, W., Biondi, E., & Zhan, Z. (2023). Earthquake Focal Mechanisms with Distributed Acoustic Sensing. Nature Communications, 14(1), 4181. https://doi.org/10.1038/s41467-023-39639-3
Lindsey, N. J., Dawe, T. C., & Ajo-Franklin, J. B. (2019). Illuminating Seafloor Faults and Ocean Dynamics with Dark Fiber Distributed Acoustic Sensing. Science, 366(6469), 1103–1107. https://doi.org/10.1126/science.aay5881
Lindsey, N. J., Rademacher, H., & Ajo-Franklin, J. B. (2020). On the Broadband Instrument Response of Fiber-Optic DAS Arrays. Journal of Geophysical Research: Solid Earth, 125(2), e2019JB018145. https://doi.org/10.1029/2019JB018145
Lior, I., Rivet, D., Ampuero, J.-P., Sladen, A., Barrientos, S., Sánchez-Olavarría, R., Villarroel Opazo, G. A., & Bustamante Prado, J. A. (2023). Magnitude Estimation and Ground Motion Prediction to Harness Fiber Optic Distributed Acoustic Sensing for Earthquake Early Warning. Scientific Reports, 13(1), 424. https://doi.org/10.1038/s41598-023-27444-3
Lior, I., Sladen, A., Rivet, D., Ampuero, J.-P., Hello, Y., Becerril, C., Martins, H. F., Lamare, P., Jestin, C., Tsagkli, S., & Markou, C. (2021). On the Detection Capabilities of Underwater DAS. Journal of Geophysical Research: Solid Earth, n/a(n/a), e2020JB020925. https://doi.org/10.1029/2020JB020925
Lior, I., & Ziv, A. (2018). The Relation Between Ground Motion, Earthquake Source Parameters, and Attenuation: Implications for Source Parameter Inversion and Ground Motion Prediction Equations. Journal of Geophysical Research: Solid Earth, 123(7), 5886–5901. https://doi.org/10.1029/2018JB015504
Madariaga, R. (1976). Dynamics of an Expanding Circular Fault. Bull. Seismol. Soc. Am, 639–666.
Martin, E. R., Lindsey, N. J., Ajo-Franklin, J. B., & Biondi, B. L. (2021). Introduction to Interferometry of Fiber-Optic Strain Measurements. In Y. Li, M. Karrenbach, & J. B. Ajo-Franklin (Eds.), Geophysical Monograph Series (1st ed., pp. 111–129). Wiley. https://doi.org/10.1002/9781119521808.ch9
Meier, M.-A., Ampuero, J. P., & Heaton, T. H. (2017). The Hidden Simplicity of Subduction Megathrust Earthquakes. Science, 357(6357), 1277–1281. https://doi.org/10.1126/science.aan5643
Met Office. (2015). Cartopy: A Cartographic Python Library with a Matplotlib Interface. https://scitools.org.uk/cartopy
Minson, S. E., Meier, M.-A., Baltay, A. S., Hanks, T. C., & Cochran, E. S. (2018). The Limits of Earthquake Early Warning: Timeliness of Ground Motion Estimates. Science Advances, 4(3), eaaq0504. https://doi.org/10.1126/sciadv.aaq0504
National Geophysical Data Center. (2023). Global Significant Earthquake Database. NOAA National Centers for Environmental Information. https://doi.org/10.7289/V5TD9V7K
Pandas Development Team, the. (2020). Pandas-Dev/Pandas: Pandas. Zenodo. https://doi.org/10.5281/ZENODO.3509134
Peng, C., Jiang, P., Ma, Q., Wu, P., Su, J., Zheng, Y., & Yang, J. (2021). Performance Evaluation of an Earthquake Early Warning System in the 2019–2020 M6.0 Changning, Sichuan, China, Seismic Sequence. Frontiers in Earth Science, 9. https://doi.org/10.3389/feart.2021.699941
Shearer, P. M. (2011). Introduction to Seismology (2. ed., repr. with corr). Cambridge Univ. Press.
Sladen, A., Rivet, D., Ampuero, J. P., De Barros, L., Hello, Y., Calbris, G., & Lamare, P. (2019). Distributed Sensing of Earthquakes and Ocean-Solid Earth Interactions on Seafloor Telecom Cables. Nature Communications, 10(1), 1–8. https://doi.org/10.1038/s41467-019-13793-z
Strumia, C., Trabattoni, A., Supino, M., Baillet, M., Rivet, D., & Festa, G. (2024). Sensing Optical Fibers for Earthquake Source Characterization Using Raw DAS Records. Journal of Geophysical Research: Solid Earth, 129(1), e2023JB027860. https://doi.org/10.1029/2023JB027860
Trabattoni, A., Biagioli, F., Strumia, C., van den Ende, M., Scotto di Uccio, F., Festa, G., Rivet, D., Sladen, A., Ampuero, J. P., Métaxian, J.-P., & Stutzmann, É. (2023). From Strain to Displacement: Using Deformation to Enhance Distributed Acoustic Sensing Applications. Geophysical Journal International, 235(3), 2372–2384. https://doi.org/10.1093/gji/ggad365
Trabattoni, A., Vernet, C., van den Ende, M., Baillet, M., Potin, B., & Rivet, D. (2024). Sediment Corrections for Distributed Acoustic Sensing. https://doi.org/10.31223/X5PX19
Universidad de Chile, the. (2012). Red Sismologica Nacional. International Federation of Digital Seismograph Networks. https://doi.org/10.7914/SN/C1
Viens, L., Bonilla, L. F., Spica, Z. J., Nishida, K., Yamada, T., & Shinohara, M. (2022). Nonlinear Earthquake Response of Marine Sediments With Distributed Acoustic Sensing. Geophysical Research Letters, 49(21), e2022GL100122. https://doi.org/10.1029/2022GL100122
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., … Contributors, S. 1 0. (2019). SciPy 1.0–Fundamental Algorithms for Scientific Computing in Python. ArXiv:1907.10121 [Physics].
Yin, J., Soto, M. A., Ramírez, J., Kamalov, V., Zhu, W., Husker, A., & Zhan, Z. (2023). Real-Data Testing of Distributed Acoustic Sensing for Offshore Earthquake Early Warning. The Seismic Record, 3(4), 269–277. https://doi.org/10.1785/0320230018
Yin, J., Zhu, W., Li, J., Biondi, E., Miao, Y., Spica, Z. J., Viens, L., Shinohara, M., Ide, S., Mochizuki, K., Husker, A. L., & Zhan, Z. (2023). Earthquake Magnitude With DAS: A Transferable Data-Based Scaling Relation. Geophysical Research Letters, 50(10), e2023GL103045. https://doi.org/10.1029/2023GL103045
Zhan, Z. (2020). Distributed Acoustic Sensing Turns Fiber-Optic Cables into Sensitive Seismic Antennas. Seismological Research Letters, 91(1), 1–15. https://doi.org/10.1785/0220190112
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Copyright (c) 2024 Martijn van den Ende, Alister Trabattoni, Marie Baillet, Diane Rivet
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HORIZON EUROPE European Research Council
Grant numbers 101041092 - ABYSS
