The Modern Swedish National Seismic Network: Two Decades of Intraplate Microseismic Observation

2021 ◽  
Author(s):  
Björn Lund ◽  
Peter Schmidt ◽  
Zaher Hossein Shomali ◽  
Michael Roth
Keyword(s):  
Crisis Management ◽  
Automatic Detection ◽  
Seismic Network ◽  
Assessment System ◽  
Continuous Data ◽  
Seismic Events ◽  
Primary System ◽  
Individual Choice ◽  
Active Structures ◽  
Event Definition

Abstract The Swedish National Seismic Network (SNSN) was modernized and rapidly expanded during the period 1998–2012. The network currently operates 68 permanent seismic stations, all with broadband instruments supplying real-time continuous data at 100 samples per second. Continuous data from 10 stations are shared with the international community via Orfeus, and approximately 10 stations of their individual choice are shared with institutes in neighboring countries (Denmark, Finland, Norway, and Germany). The SNSN uses the South Iceland Lowland (SIL) system as the primary system for automatic detection and event definition. In addition, an in-house system based on migration and stacking is used for automatic detection of small events, and implementations of SeisComP (SC) and Earthworm are used primarily for rapid detection of larger regional events. Global monitoring is performed with SC, using approximately 250 global stations, and we operate a continuous rapid risk assessment system serving Swedish crisis management authorities. Since the start of automatic processing in August 2000, the SNSN has recorded and interactively analyzed more than 171,000 seismic events, of which 10,700 were earthquakes with local magnitudes ranging from around −1 to 4.3. The microearthquake activity detected in the last 20 yr has significantly improved the identification and understanding of seismically active structures in Sweden.

CONSTRUCTION OF RISK ASSESSMENT SYSTEM FOR ANTI- CRISIS MANAGEMENT OF TERRITORIAL COMMUNITIES

2017 ◽  
Author(s):  
Mariia Bondarchuk ◽  
◽  
Orysia Voloshyn ◽  
Iryna Skoropad ◽  
Oksana Chervinska ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Financial Crisis ◽  
Crisis Management ◽  
Early Warning ◽  
Government Regulation ◽  
Local Community ◽  
Assessment System ◽  
Influential Factor ◽  
Enterprise Development ◽  
Theoretical Foundations

The article further develops the system of early warning and response to crisis situations in the local community through the consideration of risks. At the same time, the list of external and internal risks for ensuring effective anti-crisis management at the enterprises of territorial communities is defined. The methods of prevention of internal risks of occurrence of financial crisis at participants of territorial community are offered. In this context, it is justified that the system of early warning and response to crises in the local community will include methods to prevent the risks of financial crisis in the members of the local community. The article presents theoretical aspects of taking into account the risk of investing funds of members of the territorial community in the enterprise, which is in danger of crisis, actualizes the assessment and analysis of the implementation of a new direction of enterprise development, which requires additional financial resources in adverse (crisis). In the study, effective methods of preventing external risks in members of the local community are substantiated. It is established that the external risks that affect the management of crisis phenomena in the territorial community will include: a) economic; b) political; c) social. It is established that diversification is reflected as an influential factor in crisis management. It is substantiated that effective regulation of external risks affecting the management of crisis phenomena includes government regulation. According to the authors, the study of the theoretical foundations for building a risk assessment system to ensure effective crisis management in the enterprises of territorial communities will ensure the effective functioning of various participants in territorial communities.

scholarly journals URAL

2019 ◽  
pp. 256-267 ◽  
Author(s):  
Aleksey Malovichko ◽  
Ruslan Dyagilev ◽  
F. Verkholantsev ◽  
I. Golubeva ◽  
T. Zlobina
Keyword(s):  
Seismic Activity ◽  
Wide Spectrum ◽  
Seismic Network ◽  
Seismic Events ◽  
Induced Earthquakes ◽  
Rock Falls ◽  
Seismic Regime ◽  
Seismic Stations ◽  
Chelyabinsk Meteorite ◽  
Tectonic Earthquakes

The article shows the monitoring results of the Ural region seismic network in 2013. It describes the seismic stations and registration abilities of the network. The analysis of seismic activity in Ural in 2013 and infor-mation about changes of the regional seismic regime since 2006 are given. The seismicity in the Ural is unique as it is presented by a wide spectrum of natural earthquakes (tectonic, earthquakes due to collapse, impact) as well as induced earthquakes (explosions, rock falls, rockbursts). Whereby the number of explosions in the region predominates among other seismic events, the number of rockbursts is much more than tectonic earth-quakes. A structural ordering can be seen for tectonic earthquakes. They tend to the basic geologic structure of the region to the Main Ural Fault. The induced events tend to mining regions. Also, there is a weak scat-tered seismicity that is typical for platform territories. Acting since 1999 the regional seismic network pro-vides the representative registration on the magnitude level ML≥2.5. In general in 2013 in Ural it was regis-tered 173 seismic events, and their basic seismic parameters were determined. The common number of in-dustrial explosions was 173. The summarized seismic explosions energy was 3.99E+9 Joules. The number of rockbursts was 29; their seismic energy was 2.82E+9 Joules. The five tectonic earthquakes made the min-imal contribution to the seismicity of the region. The unique event registered by seismic network was the ex-plosion of Chelyabinsk meteorite, and its parameters are shown in the article. Parameters of all mentioned above seismic events are presented in catalogue. The strongest events with ML≥3.0 including Chelyabinsk meteorite explosion, are considered separately, including their seismograms and parameters provided by other international seismic centers. The article shows the map with the actual locations of regional seismic stations and event epicenters in 2013. Generally the seismic regime of the region in 2013 was quite calm; the summarized seismic explosions energy was low. The trend to the seismic activity decay continues since 2010. The location of the natural and induced seismic events in space confirms the active zones previously determined.

A satellite-based seismic and volcanic monitoring system for Colombia

1994 ◽  
Vol 84 (5) ◽  
pp. 1670-1674
Author(s):  
Goetz G. R. Buchbinder ◽  
Alberto Sarria
Keyword(s):  
Monitoring System ◽  
Volcanic Activity ◽  
Seismic Network ◽  
Continuous Data ◽  
Earthquake Catalogs ◽  
Short Period ◽  
Satellite Links ◽  
Volcanic Monitoring ◽  
Analysis System ◽  
Visual Record

Abstract A satellite-based seismic network with 13 sites has been installed in Colombia. Each site has one vertical short-period seismometer. The purpose of the network is 2-fold and complementary: a number of the sites are on or near active volcanoes in order to give warnings in case of recurring volcanic activity, and all the stations will create the foundation of a national Colombian Seismic Network. The satellite links have room to accommodate a future expansion to 24 sites. All the data are sent continuously to Bogota by satellite, for analysis. To aid in the volcano monitoring, a visual record is produced for each site. In addition, continuous data or optionally triggered events are stored on disks. An associated analysis system determines epicentral parameters for the earthquakes that are occurring in Colombia and then produces earthquake catalogs.

Joint detection and classification of rockfalls in a microseismic monitoring network

2020 ◽  
Vol 222 (3) ◽  
pp. 2108-2120 ◽  
Author(s):  
Liang Feng ◽  
Veronica Pazzi ◽  
Emanuele Intrieri ◽  
Teresa Gracchi ◽  
Giovanni Gigli
Keyword(s):  
Ad Hoc ◽  
Monitoring Network ◽  
Automatic Detection ◽  
Seismic Monitoring ◽  
Slope Instability ◽  
Seismic Events ◽  
Monitoring Period ◽  
Seismic Waveform ◽  
Time Average

SUMMARY A rockfall (RF) is a ubiquitous geohazard that is difficult to monitor or predict and poses a significant risk for people and transportation in several hilly and mountainous environments. The seismic signal generated by RF carries abundant physical and mechanical information. Thus, signals can be used by researchers to reconstruct the event location, onset time, volume and trajectory, and develop an efficient early warning system. Therefore, the precise automatic detection and classification of RF events are important objectives for scientists, especially in seismic monitoring arrays. An algorithm called DESTRO (DEtection and STorage of ROckfalls) aimed at combining seismic event automatic detection and classification was implemented ad hoc within the MATLAB environment. In event detection, the STA/LTA (short-time-average through long-time-average) method combined with other parameters, such as the minimum duration of an RF and the minimum interval time between two continuous seismic events is used. Furthermore, nine significant features based on the frequency, amplitude, seismic waveform, duration and multiple station attributes are newly proposed to classify seismic events in a RF environment. In particular, a three-step classification method is proposed for the discrimination of five different source types: RFs, earthquakes (EQs), tremors, multispike events (MSs) and subordinate MS events. Each component (vertical, east–west and north–south) at each station within the monitoring network is analysed, and a three-step classification is performed. At a given time, the event series detected from each component are integrated and reclassified component by component and station by station into a final event-type series as an output result. By this algorithm, a case study of the seven-month-long seismic monitoring of a former quarry in Central Italy was investigated by means of four triaxial velocimeters with continuous acquisition at a sampling rate of 200 Hz. During this monitoring period, a human-induced RF simulation was performed, releasing 95 blocks (in which 90 blocks validated) of different sizes from the benches of the quarry. Consequently, 64.9 per cent of EQs within 100 km were confirmed in a one-month monitoring period, 88 blocks in the RF simulation were classified correctly as RF events and 2 blocks were classified as MSs given their small energy. Finally, an ad hoc section of the algorithm was designed specifically for RF classification combined with EQ recognition. The algorithm could be applied in slope seismic monitoring to monitor the dynamic states of rock masses, as well as in slope instability forecasting and risk evaluation in EQ-prone areas.

scholarly journals FILTRAGEM SVD APLICADA À MELHORIA DO RASTREAMENTO DE HORIZONTES SÍSMICOS

2011 ◽  
Vol 29 (3) ◽  
Author(s):  
Milton J. Porsani ◽  
Fredy A.V. Artola ◽  
Michelângelo G. da Silva ◽  
Paulo E.M. de Melo
Keyword(s):  
Singular Value Decomposition ◽  
Seismic Data ◽  
Automatic Detection ◽  
Singular Value ◽  
Seismic Events ◽  
Computationally Efficient ◽  
Automatic Mapping ◽  
Multichannel Filtering ◽  
Value Decomposition ◽  
Filtering Approach

No presente artigo apresentamos uma aplicação da filtragem SVD (Singular Value Decomposition) para o mapeamento automático de horizontes sísmicos. A filtragem SVD pode ser vista como um método de filtragem multicanal onde cada traço filtrado guarda certo grau de coerência com os traços imediatamente vizinhos. Esta filtragem preserva as relações de amplitude, fase e correlação espacial dos eventos sísmicos, ao tempo em que permite eliminar o ruído incoerente, normalmente associado aos últimos autovalores. A decomposição SVD é realizada sobre o subconjunto de traços vizinhos a cada traço da linha sísmica 2D ou de um volume 3D. O traço filtrado é obtido utilizando apenas alguns dos autovetores e autovalores associados. Ilustramos a aplicação do método sobre dados sísmicos terrestres. A melhoria da coerência dos eventos sísmicos permitiu maior robustez ao autotracking no mapeamento e interpretação automática dos horizontes sísmicos. A filtragem SVD é computacionalmente eficiente e tem o mérito de melhorar significativamente a coerência, a consistência e a continuidade dos eventos de reflexão facilitando muito o "trabalho", do tracker na busca de padrões no processo de autotracking.Keywords : mapeamento automático de horizontes; processamento sísmico; filtragem SVD; rastreamento de horizontes sísmicos.ABSTRACTWe present an application of a singular value decomposition (SVD) filtering approach to the automatic detection of seismic horizons. The SVD filtering approach may be seen as a multichannel filtering method where each filtered seismic trace retains the coherence of the neighbouring seismic traces. The SVD filtering preserves the amplitude and phase relations and reinforces the spacial correlation between seismic events, and at the same time it reduces the incoherent noise in data, which normally is associated to the last eigenvalues. The SVD decomposition is performed on each subset of traces around each trace of the original 2D or 3D seismic data. The filtered trace is obtained from the most important eigenvalues and eigenvectors. We illustrate the application of the new approach on 3D post-stack land seismic data. The improvement of the resultant coherence in the seismic reflected events allows for greater autotracking robustness during the automatic interpretation of the seismic horizons. The SVD filtering approach is computationally efficient and improves significantly the coherence, the consistency and the spacial continuity of the seismic events making easier the automatic detection of the commercial software in the search for patterns along the autotracking process.Keywords : automatic mapping of horizons; seismic processing; SVD filtering; tracking horizons seismic.

Unsupervised Large‐Scale Search for Similar Earthquake Signals

2019 ◽  
Vol 109 (4) ◽  
pp. 1451-1468 ◽  
Author(s):  
Clara E. Yoon ◽  
Karianne J. Bergen ◽  
Kexin Rong ◽  
Hashem Elezabi ◽  
William L. Ellsworth ◽  
...  
Keyword(s):  
Data Mining ◽  
Nuclear Power ◽  
Large Scale ◽  
Seismic Network ◽  
Continuous Data ◽  
Data Sets ◽  
Data Set ◽  
Data Mining Algorithms ◽  
Seismicity Rates ◽  
Unsupervised Data Mining

Abstract Seismology has continuously recorded ground‐motion spanning up to decades. Blind, uninformed search for similar‐signal waveforms within this continuous data can detect small earthquakes missing from earthquake catalogs, yet doing so with naive approaches is computationally infeasible. We present results from an improved version of the Fingerprint And Similarity Thresholding (FAST) algorithm, an unsupervised data‐mining approach to earthquake detection, now available as open‐source software. We use FAST to search for small earthquakes in 6–11 yr of continuous data from 27 channels over an 11‐station local seismic network near the Diablo Canyon nuclear power plant in central California. FAST detected 4554 earthquakes in this data set, with a 7.5% false detection rate: 4134 of the detected events were previously cataloged earthquakes located across California, and 420 were new local earthquake detections with magnitudes −0.3≤ML≤2.4, of which 224 events were located near the seismic network. Although seismicity rates are low, this study confirms that nearby faults are active. This example shows how seismology can leverage recent advances in data‐mining algorithms, along with improved computing power, to extract useful additional earthquake information from long‐duration continuous data sets.

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