Online Earthquakes

Institute of Seismology, University of Helsinki, provides several online earthquake maps. EQ-Search Tool (http://www.seismo.helsinki.fi/EQs/query.php) is an online map service which allows the user to search for earthquakes within the North European earthquake catalogue (FENCAT). Data in the catalogue is further supplemented with more recent events found by seismic analysts during the daily processing of seismic events. ISUH also provides a global map of significant earthquakes from a Finnish perspective in the past 7 days. The map, LUOVA-järistyskartta (http://www.seismo.helsinki.fi/EQs/jaristyskartta.php), is based on LUOVAsystem, which is an official natural hazard alert program in Finland. Currently this map is available only in Finnish.Non peer reviewe

Tooling for interoperability and integrity between primary data sources and data infrastructures

In Geophysical Research Abstracts. Vol. 20.Peer reviewe

Array-derived peak ground rotation rate vs. peak ground acceleration : scaling relations from seismicity induced by the Espoo/Helsinki geothermal stimulation

In 2018 and 2020, two weeks-long geothermal reservoir stimulations were performed some 6 km below the Helsinki capital area, Finland. The seismic activity was recorded by a set of surface broadband sensors and 100 geophones installed by the Institute of Seismology, University of Helsinki, as well as Finnish National Seismic Network stations. The local magnitudes (ML) of the recorded earthquakes are estimated using a Finnish local magnitude scale and the local magnitude of the largest induced event was 1.8. We apply three different approaches for estimation of moment magnitudes (MW) to a data base of ~400 induced seismic events from the 2018 stimulation to explore the variability and sensitivity of the magnitude estimates. This is important for real-time monitoring and decision making when the induced event magnitudes approach the pre-defined magnitude limit, and to assess which trends can be robustly associated to earthquake source physics. (1) We employ a time-domain calculation of source parameters based on the application of Parseval's theorem to the integrals of the squared spectral displacement and velocity for the horizontal S-wave trains. The time window between the S-wave arrival time and twice the length of the S-wave travel time is considered for the S-wave train isolation. (2) We obtain moment magnitude estimates from an inversion of 50 s long three-component envelopes based on radiative transfer. (3) We apply a moment tensor inversion to 0.71 s long P and 0.81 s long S-wave signals. We fit a linear ML-MW conversion model to the values obtained from the different approaches. Considering the available local magnitude range between –0.5 and 1.8, a comparison of the linear conversion models shows that the moment magnitudes form the envelope inversion are systematically larger by ~0.2 units compared to those obtained from the moment tensor inversion. While the moment magnitudes determined by the time-domain calculation consistently exceed those of the envelope inversion for small local magnitudes (by ~0.2 units), they tend to yield similar estimates towards the larger local magnitudes. Other source parameter systematics include that the smallest seismic moment is obtained with the moment tensor inversion, and the largest with the time-domain equivalent of the spectral integrals. An initial extension of the analysis to 2020 data yields ML-MW as well as corner frequency-MW scaling relations that are, interestingly, different compared to the 2018 results; we will present updated results that inform about the reliability of these trends

Magnitude estimates of earthquakes induced by the geothermal stimulations in Espoo/Helsinki, southern Finland : a comparison of different approaches

In 2018 and 2020, two weeks-long geothermal reservoir stimulations were performed some 6 km below the Helsinki capital area, Finland. The seismic activity was recorded by a set of surface broadband sensors and 100 geophones installed by the Institute of Seismology, University of Helsinki, as well as Finnish National Seismic Network stations. The local magnitudes (ML) of the recorded earthquakes are estimated using a Finnish local magnitude scale and the local magnitude of the largest induced event was 1.8. We apply three different approaches for estimation of moment magnitudes (MW) to a data base of ~400 induced seismic events from the 2018 stimulation to explore the variability and sensitivity of the magnitude estimates. This is important for real-time monitoring and decision making when the induced event magnitudes approach the pre-defined magnitude limit, and to assess which trends can be robustly associated to earthquake source physics. (1) We employ a time-domain calculation of source parameters based on the application of Parseval's theorem to the integrals of the squared spectral displacement and velocity for the horizontal S-wave trains. The time window between the S-wave arrival time and twice the length of the S-wave travel time is considered for the S-wave train isolation. (2) We obtain moment magnitude estimates from an inversion of 50 s long three-component envelopes based on radiative transfer. (3) We apply a moment tensor inversion to 0.71 s long P and 0.81 s long S-wave signals. We fit a linear ML-MW conversion model to the values obtained from the different approaches. Considering the available local magnitude range between –0.5 and 1.8, a comparison of the linear conversion models shows that the moment magnitudes form the envelope inversion are systematically larger by ~0.2 units compared to those obtained from the moment tensor inversion. While the moment magnitudes determined by the time-domain calculation consistently exceed those of the envelope inversion for small local magnitudes (by ~0.2 units), they tend to yield similar estimates towards the larger local magnitudes. Other source parameter systematics include that the smallest seismic moment is obtained with the moment tensor inversion, and the largest with the time-domain equivalent of the spectral integrals. An initial extension of the analysis to 2020 data yields ML-MW as well as corner frequency-MW scaling relations that are, interestingly, different compared to the 2018 results; we will present updated results that inform about the reliability of these trends

The Finnish National Seismic Network : Toward Fully Automated Analysis of Low‐Magnitude Seismic Events

We present an overview of the seismic networks, products, and services in Finland, northern Europe, and the challenges and opportunities associated with the unique combination of prevailing crystalline bedrock, low natural intraplate seismic background activity, and a high level of anthropogenic seismicity. We introduce national and local seismic networks, explain the databases, analysis tools, and data management concepts, outline the Finnish macroseismic service, and showcase data from the 2017 M 3.3 Liminka earthquake in Ostrobothnia, Finland.Peer reviewe

The 2018 Geothermal Reservoir Stimulation in Espoo/Helsinki, Southern Finland: Seismic Network Anatomy and Data Features

A seismic network was installed in Helsinki, Finland to monitor the response to an similar to 6-kilometer-deep geothermal stimulation experiment in 2018. We present initial results of multiple induced earthquake seismogram and ambient wavefield analyses. The used data are from parts of the borehole network deployed by the operating St1 Deep Heat Company, from surface broadband sensors and 100 geophones installed by the Institute of Seismology, University of Helsinki, and from Finnish National Seismic Network stations. Records collected in the urban environment contain many signals associated with anthropogenic activity. This results in time- and frequency-dependent variations of the signal-to-noise ratio of earthquake records from a 260-meter-deep borehole sensor compared to the combined signals of 24 collocated surface array sensors. Manual relocations of similar to 500 events indicate three distinct zones of induced earthquake activity that are consistent with the three clusters of seismicity identified by the company. The fault-plane solutions of 14 selected ML 0.6-1.8 events indicate a dominant reverse-faulting style, and the associated SH radiation patterns appear to control the first-order features of the macroseismic report distribution. Beamforming of earthquake data from six arrays suggests heterogeneous medium properties, in particular between the injection site and two arrays to the west and southwest. Ambient-noise cross-correlation functions reconstruct regional surface-wave propagation and path-dependent body-wave propagation. A 1D inversion of the weakly dispersive surface waves reveals average shear-wave velocities around 3.3 km/s below 20 m depth. Consistent features observed in relative velocity change time series and in temporal variations of a proxy for wavefield partitioning likely reflect the medium response to the stimulation. The resolution properties of the obtained data can inform future monitoring strategies and network designs around natural laboratories.Peer reviewe

HelsinkiNet - a collaborative seismological research network of the Institute of Seismology, and the City of Helsinki

Non peer reviewe

HelsinkiNet - a collaborative seismological research network of the Institute of Seismology, and the City of Helsinki

Non peer reviewe

Helsingin seisminen asemaverkko ja seismisyys 2020

Seismologian instituutti perusti yhteistyössä Helsingin kaupungin kanssa vuosina 2019–2020 kolmesta seismisestä havaintoasemasta koostuvan HelsinkiNet-verkon. Verkon asemat toimivat Kuninkaantammessa (KUNI), Lauttasaaressa (LAUT) ja Vuosaaressa (VUOS) sekä valtakunnallisen että pääkaupunkiseudun asemaverkon automaattisten havaintojärjestelmien yhteydessä. Asemien kohinataso osoittautui sijaintiin nähden matalaksi ja pitkiä datakatkoja ei ollut. HelsinkiNet-asemien lisäksi pääkaupunkiseudun länsiosissa toimivat St1:n lämpövoimalahankkeen valvontaan perustetut asemat HEL1-HEL5. Vuonna 2020 vahvistettuja seismisiä tapauksia oli 30 km:n säteellä Rautatientorista 484. Suurin osa niistä oli räjäytyksiä. Indusoituja maanjäristyksiä tapahtui Espoossa erityisesti Otaniemessä mutta myös Koskelossa. Luonnollisia maanjäristyksiä oli kolme, niistä kaksi 0,7 magnitudin tapausta Hakunilassa ja yksi –0,5 magnitudin tapaus Laajarannassa. Vähintään 0,0 magnitudin indusoitujen ja luonnollisten maanjäristysten määrä oli 24. Suurin osa maanjäristysten kansalaishavainnoista liittyi St1:n Otaniemen hankkeeseen.In 2019–2020, the Institute of Seismology set up, in collaboration with the City of Helsinki, a seismic network, HelsinkiNet, consisting of three stations. The stations of the network were in operation in Kuninkaantammi (KUNI), Lauttasaari (LAUT), and Vuosaari (VUOS) in association with the automatic observation systems of Finland and the Helsinki region. The noise level of stations was low considering their locations, and no long interruptions to data delivery have taken place. In addition to HelsinkiNet, stations HEL1-HEL5 established for the monitoring of the St1 deep heat project were operational in the western part of Helsinki region. In 2020, the number of confirmed seismic events within 30 km from the Central Railway Station of Helsinki was 484, most of them explosions. Induced earthquakes happened in Espoo, particularly in Otaniemi, but also in Koskelo. Three natural earthquakes occurred, two of them were 0.7-magnitude events in Vantaa and one was a –0.5-magnitude event in Laajaranta. The number of natural and induced earthquakes of at least magnitude 0.0 was 24. Most of the macroseismic observations of earthquakes were associated with the St1 geothermal plant project in Otaniemi, Espoo