Performance of Automatic Detector & Locator Tested on Synthetic Seismograms
Case Study from Litoměřice in Czech Republic
DOI:
https://doi.org/10.26443/seismica.v4i1.1373Keywords:
Induced seismicity, synthetic seismograms, Synthetic Waveforms, local magnitude, Microseismicity, Microseismic Monitoring, Earthquake detection, automatic detection and location, magnitude of completeness, Seismic Networks, seismic network sensitivity, geothermalAbstract
Seismic network sensitivity and event detection performance are critical for assessing earthquake risks, particularly in regions susceptible to induced seismicity. In seismically inactive zones, the network monitoring presents unique challenges, even when adapting automated detection and location systems originally designed for active zones.
In this study, we evaluate the capabilities of the seismic network deployed in the Litoměřice region of the Czech Republic, where a geothermal project is underway and no seismicity was recorded in years of monitoring. Using synthetic seismograms, we simulate a potential earthquake in the geothermal well to assess the network's detection efficiency at the most exposed area. PEPiN, an automated earthquake picker and locator which was originally designed for the West Bohemia region, is employed to analyze the synthetic dataset with real background seismicity.
Our results demonstrate that PEPiN detects and localizes 82% of the synthetic events with magnitude of completeness ML-0.5, slightly above the value predicted by our previous research. Overall, our findings provide valuable insights into the seismic monitoring capabilities of the Litoměřice network, shedding light on the potential strengths and limitations of seismic surveillance systems in similar geothermal and underground operation settings.
References
Allen, R. (1982). Automatic phase pickers: Their present use and future prospects. Bulletin of the Seismological Society of America, 72(6B), S225–S242. https://doi.org/10.1785/BSSA07206B0225
Allen, R. V. (1978). Automatic earthquake recognition and timing from single traces. Bulletin of the Seismological Society of America, 68(5), 1521–1532. https://doi.org/10.1785/BSSA0680051521
Bachura, M. (2017). The Structure of the West Bohemian Earthquake Swarm Source Zone [PhD thesis]. Institute of Hydrogeology, Engineering Geology.
Burda, J., Lojka, R., Mlčoch, B., Valečka, J., & Žáček, V. (2008). Závěrečná zpráva za léta 2006-2007 geologické a hydrogeologické poměry ověřovacího vrtu pvgt-lt 1 v geotermální struktuře litoměřice pro energetické využití (Techreport ČGS-Geofond: GF P123196). Česká geologická služba.
Cajz, V., Rapprich, V., Erban, Z., V. and Pécskay, & Radoň, M. (2009). Late Miocene volcanic activity in the České středohoří Mountains (Ohře/Eger Graben, northern Bohemia). Geologica Carpathica, 60(6), 519–533. https://doi.org/10.2478/v10096-009-0038-8
Čermáková, H., & Horálek, J. (2015). The 2011 West Bohemia (Central Europe) earthquake swarm compared with the previous swarms of 2000 and 2008. Journal of Seismology, 19(4), 899–913. https://doi.org/10.1007/s10950-015-9502-3
Chamberlain, C. J., & Townend, J. (2018). Detecting Real Earthquakes Using Artificial Earthquakes: On the Use of Synthetic Waveforms in Matched-Filter Earthquake Detection. Geophysical Research Letters, 45(21), 11,641-11,649. https://doi.org/10.1029/2018GL079872
Clarke, H., Eisner, L., Styles, P., & Turner, P. (2014). Felt seismicity associated with shale gas hydraulic fracturing: The first documented example in Europe. Geophysical Research Letters, 41(23), 8308–8314. https://doi.org/10.1002/2014GL062047
D’Alessandro, A., Luzio, D., D’Anna, G., & Mangano, G. (2011). Seismic Network Evaluation through Simulation: An Application to the Italian National Seismic Network. Bulletin of the Seismological Society of America, 101(3), 1213–1232. https://doi.org/10.1785/0120100066
Deichmann, N., & Giardini, D. (2009). Earthquakes Induced by the Stimulation of an Enhanced Geothermal System below Basel (Switzerland). Seismological Research Letters, 80(5), 784–798. https://doi.org/10.1785/gssrl.80.5.784
Doubravová, J., & Horálek, J. (2019). Single Layer Recurrent Neural Network for detection of local swarm-like earthquakes—the application. Geophysical Journal International, 219(1), 672–689. https://doi.org/10.1093/gji/ggz321
Dubiński, J., Stec, K., & Bukowska, M. (2019). Geomechanical and tectonophysical conditions of mining-induced seismicity in the Upper Silesian Coal Basin in Poland: a case study [Artykuły / Articles]. Archives of Mining Sciences, 64(No 1), 163–180. https://doi.org/10.24425/ams.2019.126278
Fischer, T., Hrubcová, P., Salama, A., Doubravová, J., Ágústsdóttir, T., Gudnason, E. Á., Horálek, J., & Hersir, G. P. (2022). Swarm seismicity illuminates stress transfer prior to the 2021 Fagradalsfjall eruption in Iceland. Earth and Planetary Science Letters, 594, 117685. https://doi.org/10.1016/j.epsl.2022.117685
Fischer, Tomáš. (2003a). Automatic location of swarm earthquakes from local network data. Studia Geophysica et Geodaetica, 47, 83–98. https://doi.org/10.1023/A:1022251605990
Fischer, Tomáš. (2003b). The August–December 2000 earthquake swarm in NW Bohemia: the first results based on automatic processing of seismograms. Journal of Geodynamics, 35(1), 59–81. https://doi.org/10.1016/S0264-3707(02)00054-6
Geffers, G.-M., Main, I. G., & Naylor, M. (2022). Biases in estimating b-values from small earthquake catalogues: how high are high b-values? Geophysical Journal International, 229(3), 1840–1855. https://doi.org/10.1093/gji/ggac028
Gibbons, S. J., & Ringdal, F. (2006). The detection of low magnitude seismic events using array-based waveform correlation. Geophysical Journal International, 165(1), 149–166. https://doi.org/10.1111/j.1365-246X.2006.02865.x
Giudicepietro, F., Esposito, A. M., & Ricciolino, P. (2017). Fast Discrimination of Local Earthquakes Using a Neural Approach. Seismological Research Letters, 88(4), 1089–1096. https://doi.org/10.1785/0220160222
Grigoli, F., Cesca, S., Rinaldi, A. P., Manconi, A., López-Comino, J. A., Clinton, J. F., Westaway, R., Cauzzi, C., Dahm, T., & S. Wiemer. (2018). The November 2017 Mw 5.5 Pohang earthquake: A possible case of induced seismicity in South Korea. Science, 360(6392), 1003–1006. https://doi.org/10.1126/science.aat2010
Hallo, M. (2012). Microseismic Surface Monitoring Network Design - Sensitivity and Accuracy. ecp-293-00307. https://doi.org/10.3997/2214-4609.20148336
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
Heimann, S., Kriegerowski, M., Isken, M., Vasyura-Bathke, H., Cesca, S., Nooshiri, N., Petersen, G., Metz, M., Steinberg, A., Sudhaus, H., & and Dahm, T. (2020). Pyrocko - A Versatile Software Framework for Seismology. EGU General Assembly 2020, Online, EGU2020-18734. https://doi.org/10.5194/egusphere-egu2020-18734, 2020
Heimann, S., Vasyura-Bathke, H., Sudhaus, H., Isken, M. P., Kriegerowski, M., Steinberg, A., & Dahm, T. (2019). A Python framework for efficient use of pre-computed Green’s functions in seismological and other physical forward and inverse source problems. Solid Earth, 10(6), 1921–1935. https://doi.org/10.5194/se-10-1921-2019
Heimann, Sebastian, Kriegerowski, M., Isken, M. P., Cesca, S., Daout, S., Grigoli, F., Juretzek, C., Megies, T., Nooshiri, N., Steinberg, A., Sudhaus, H., Vasyura-Bathke, H., Willey, T., & Dahm, T. (2017). Pyrocko - An open-source seismology toolbox and library. Potsdam : GFZ Data Services. https://doi.org/10.5880/GFZ.2.1.2017.001
Horálek, J., & Šílený, J. (2013). Source mechanisms of the 2000 earthquake swarm in the West Bohemia/Vogtland region (Central Europe). Geophysical Journal International, 194(2), 979–999. https://doi.org/10.1093/gji/ggt138
Institute of Geophysics, Academy of Sciences of the Czech Republic. (1991). West Bohemia Local Seismic Network. International Federation of Digital Seismograph Networks. https://doi.org/10.7914/SN/WB
Jakoubková, H. (2018). Earthquake swarms in diverse tectonic environments: West Bohemia and Southwest Iceland [PhD thesis]. Institute of Hydrogeology, Engineering Geology.
Janská, E., & Leo Eisner. (2012). Ongoing seismicity in the Dallas-Fort Worth area. The Leading Edge, 31(12), 1462–1468. https://doi.org/10.1190/tle31121462.1
Káldy, E., & Fischer, T. (2023). Microseismic network sensitivity in case of no seismic activity. Journal of Seismology, 27(4), 627–641. https://doi.org/10.1007/s10950-023-10134-y
Kasza, Z., Tonka, P., Szucsi, P., Prohaszka, A., Szucsi, P., Meszaros, F., & Szongoth, G. (2007). Závěrečná zpráva za léta 2006-2007 geologické a hydrogeologické poměry ověřovacího vrtu pvgt-lt 1 v geotermální struktuře litoměřice pro energetické využití (Techreport No. 2007verb, , Litomericeverb, , Litomerice_1114fuzott.prj). Geo-Log Environmental Protection.
Kennett, B. L. N., & Furumura, T. (2019). Significant P wave conversions from upgoing S waves generated by very deep earthquakes around Japan. Progress in Earth and Planetary Science, 6(1), 49. https://doi.org/10.1186/s40645-019-0292-z
Kraft, T., & Deichmann, N. (2014). High-precision relocation and focal mechanism of the injection-induced seismicity at the Basel EGS. Geothermics, 52, 59–73. https://doi.org/10.1016/j.geothermics.2014.05.014
Kraft, T., Roth, P., & Wiemer, S. (2020). Good-Practice Guide for Managing Induced Seismicity in Deep Geothermal Energy Projects in Switzerland (Version 2). https://doi.org/10.3929/ethz-b-000453228
Leptokaropoulos, K. M., Adamaki, A. K., Roberts, R. G., Gkarlaouni, C. G., & Paradisopoulou, P. M. (2018). Impact of magnitude uncertainties on seismic catalogue properties. Geophysical Journal International, 213(2), 940–951. https://doi.org/10.1093/gji/ggy023
Leptokaropoulos, K. M., & Gkarlaouni, C. G. (2016). A magnitude independent space-time earthquake clustering algorithm (MISTIC). Bulletin of the Geological Society of Greece, 50(3), 1359–1368. https://doi.org/10.12681/bgsg.11849
Levin, B. V., Sasorova, E. V., Borisov, S. A., & Borisov, A. S. (2010). Estimating the parameters of small earthquakes and their signals. Journal of Volcanology and Seismology, 4(3), 203–212. https://doi.org/10.1134/S074204631003005X
Lomax, A., Michelini, A., & Curtis, A. (2009). EarthquakeEarthquakeLocationEarthquakelocation, Direct, Global-SearchGlobal-searchMethods. In R. A. Meyers (Ed.), Encyclopedia of Complexity and Systems Science (pp. 2449–2473). Springer New York. https://doi.org/10.1007/978-0-387-30440-3_150
López-Comino, J. A., Cesca, S., Kriegerowski, M., Heimann, S., Dahm, T., Mirek, J., & Lasocki, S. (2017). Monitoring performance using synthetic data for induced microseismicity by hydrofracking at the Wysin site (Poland). Geophysical Journal International, 210(1), 42–55. https://doi.org/10.1093/gji/ggx148
Magotra, N., Ahmed, N., & Chael, E. (1987). Seismic event detection and source location using single-station (three-component) data. Bulletin of the Seismological Society of America, 77(3), 958–971. https://doi.org/10.1785/BSSA0770030958
Magrini, F., Jozinović, D., Cammarano, F., Michelini, A., & Boschi, L. (2020). Local earthquakes detection: A benchmark dataset of 3-component seismograms built on a global scale. Artificial Intelligence in Geosciences, 1, 1–10. https://doi.org/10.1016/j.aiig.2020.04.001
Majer, E., Tait, A., & Wong, I. (2012). Protocol for addressing induced seismicity associated with enhanced geothermal systems (Techreport DOE/EE-0662). U.S. Department of Energy, Energy Efficiency & Renewable Energy. https://www.researchgate.net/publication/221678264_Protocol_for_addressing_induced_seismicity_associated_with_enhanced_geothermal_systems#fullTextFileContent
Muntendam-Bos, A. G., & Grobbe, N. (2022). Data-driven spatiotemporal assessment of the event-size distribution of the Groningen extraction-induced seismicity catalogue. Scientific Reports, 12, 10119. https://doi.org/10.1038/s41598-022-14451-z
Myslil, V., Karous, M., & Pačes, T. (2012). Geothermal project for the Litoměřice heating plant [Techreport]. Geotern s.r.o.
Myslil, V., Stibitz, M., Frydrych, V., & et al. (2007). Geotermální vrtné ověření struktury litoměřice pro energetické využití: Závěrečná zpráva o řešení projektu v programu trvalá prosperita mpo v roce 2006 - 2007 (Techreport Ev.č. projektu: 2A-1TP1/043). Geomedia.
Mysliveček, J., Rapprich, V., Kochergina, Y. V., Magna, T., Halodová, P., Pécskay, Z., & Poňavič, M. (2018). Petrology of weakly differentiated alkaline, high-level intrusive rocks in the Zahořany-Chotiněves Belt near Litoměřice (Czech Republic). Journal of Geosciences, 63(4), 317–331.
Nolte, K. A., & Tsoflias, G. P. (2021). Identifying Direct SP -Converted Waves Constrains Local Induced Earthquake Depths. Seismological Research Letters, 92(6). https://doi.org/10.1785/0220200385
Pavlenko, V. A., & Zavyalov, A. D. (2022). Comparative Analysis of the Methods for Estimating the Magnitude of Completeness of Earthquake Catalogs. Izvestiya, Physics of the Solid Earth, 58. https://doi.org/10.1134/S1069351322010062
Perol, T., Gharbi, M., & Marine Denolle. (2018). Convolutional neural network for earthquake detection and location. Science Advances, 4(2), e1700578. https://doi.org/10.1126/sciadv.1700578
Rosenberger, A. (2010). Real-Time Ground-Motion Analysis: Distinguishing P and S Arrivals in a Noisy Environment. Bulletin of the Seismological Society of America, 100(3), 1252–1262. https://doi.org/10.1785/0120090265
Šafanda, J., Verner, K., Franěk, J., Peřestý, V., Holeček, J., & Fischer, T. (2020). Geology and geothermal potential in the eastern flank of Eger Rift (Litoměřice area, Czech Republic). Geothermics, 86, 101808. https://doi.org/10.1016/j.geothermics.2020.101808
Shearer, P. M. (2009). Introduction to Seismology. Cambridge University Press.
Stepnov, A., Chernykh, V., & Konovalov, A. (2021). The Seismo-Performer: A Novel Machine Learning Approach for General and Efficient Seismic Phase Recognition from Local Earthquakes in Real Time. Sensors, 21(18). https://doi.org/10.3390/s21186290
Uličný, D., Laurin, J., & Čech, S. (2009). Controls on clastic sequence geometries in a shallow-marine, transtensional basin: the Bohemian Cretaceous Basin, Czech Republic. Sedimentology, 56(4), 1077–1114. https://doi.org/10.1111/j.1365-3091.2008.01021.x
Velasco, A. A., Alfaro‐Diaz, R., Kilb, D., & Pankow, K. L. (2016). A Time‐Domain Detection Approach to Identify Small Earthquakes within the Continental United States Recorded by the USArray and Regional Networks. Bulletin of the Seismological Society of America, 106(2), 512–525. https://doi.org/10.1785/0120150156
Wang, R. (1999). A simple orthonormalization method for stable and efficient computation of Green’s functions. Bulletin of the Seismological Society of America, 89(3), 733–741. https://doi.org/10.1785/BSSA0890030733
Wang, R., Heimann, S., Zhang, Y., Wang, H., & Dahm, T. (2017). Complete synthetic seismograms based on a spherical self-gravitating Earth model with an atmosphere–ocean–mantle–core structure. Geophysical Journal International, 210(3), 1739–1764. https://doi.org/10.1093/gji/ggx259
White, J. A., & Foxall, W. (2016). Assessing induced seismicity risk at CO2 storage projects: Recent progress and remaining challenges. International Journal of Greenhouse Gas Control, 49, 413–424. https://doi.org/10.1016/j.ijggc.2016.03.021
Wiemer, S., & Wyss, M. (2000). Minimum Magnitude of Completeness in Earthquake Catalogs: Examples from Alaska, the Western United States, and Japan. Bulletin of the Seismological Society of America, 90(4), 859–869. https://doi.org/10.1785/0119990114
Wilson, D. C., Wolin, E., Yeck, W. L., Anthony, R. E., & Ringler A. T. (2021). Modeling seismic network detection thresholds using production picking algorithms. Seismological Research Letters, 93(1), 149–160. https://doi.org/10.1785/0220210192
Yang, W., Chen, G., Meng, L., Zang, Y., Zhang, H., & Li, J. (2021). Determination of the local magnitudes of small earthquakes using a dense seismic array in the Changning–Zhaotong Shale Gas Field, Southern Sichuan Basin. Earth and Planetary Physics, 5(6), eepp2021026. https://doi.org/10.26464/epp2021026
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