Seismic Waveform Data from Greece and Cyprus: Integration, Archival, and Open Access

2021 ◽  
Author(s):  
Christos P. Evangelidis ◽  
Nikolaos Triantafyllis ◽  
Michalis Samios ◽  
Kostas Boukouras ◽  
Kyriakos Kontakos ◽  
...  
Keyword(s):  
Seismic Data ◽  
Data Center ◽  
Ambient Noise ◽  
Strong Motion ◽  
Data Availability ◽  
Data Archive ◽  
Waveform Data ◽  
The Balkans ◽  
Seismic Waveform ◽  
Data Archives

Abstract The National Observatory of Athens data center for the European Integrated Data Archive (EIDA@NOA) is the national and regional node that supports International Federation of Digital Seismograph Networks and related webservices for seismic waveform data coming from the southeastern Mediterranean and the Balkans. At present, it serves data from eight permanent broadband and strong-motion networks from Greece and Cyprus, individual stations from the Balkans, temporary networks and aftershock deployments, and earthquake engineering experimental facilities. EIDA@NOA provides open and unlimited access from redundant node end points, intended mainly for research purposes (see Data and Resources). Analysis and quality control of the complete seismic data archive is performed initially by calculating waveform metrics and data availability. Seismic ambient noise metrics are estimated based on power spectral densities, and an assessment of each station’s statistical mode is achieved within each network and across networks. Moreover, the minimum ambient noise level expected for strong-motion installations is defined. Sensor orientation is estimated using surface-wave polarization methods to detect stations with misalignment on particular epochs. A single data center that hosts the complete seismic data archives with their respective metadata from networks covering similar geographical areas allows coordination between network operators and facilitates the adhesion to widely used best practices regarding station installation, data curation, and metadata definition. The overall achievement is harmonization among all contributing networks and a wider usage of all data archives, ultimately strengthening seismological research efforts in the region.

The EIDA federator – a one-stop access to EIDA seismic data holdings

2021 ◽  
Author(s):  
Philipp Kaestli ◽  
Daniel Armbruster ◽  
The EIDA Technical Committee
Keyword(s):  
Data Center ◽  
Data Centers ◽  
Data Access ◽  
Distributed Data ◽  
Data Archive ◽  
Waveform Data ◽  
Seismic Waveform ◽  
One Stop ◽  
Single Data ◽  
Seismic Networks

<p>With the setup of EIDA (the European Integrated Data Archive https://www.orfeus-eu.org/data/eida/) in the framework of ORFEUS, and the implementation of FDSN-standardized web services, seismic waveform data and instrumentation metadata of most seismic networks and data centers in Europe became accessible in a homogeneous way. EIDA has augmented this with the WFcatalog service for waveform quality metadata, and a routing service to find out which data center offers data of which network, region, and type. However, while a distributed data archive has clear advantages for maintenance and quality control of the holdings, it complicates the life of researchers who wish to collect data archived across different data centers. To tackle this, EIDA has implemented the “federator” as a one-stop transparent gateway service to access the entire data holdings of EIDA.</p><p>To its users the federator acts just like a standard FDSN dataselect, station, or EIDA WFcatalog service, except for the fact that it can (due to a fully qualified internal routing cache) directly answer data requests on virtual networks.</p><p>Technically, the federator fulfills a user request by decomposing it into single stream epoch requests targeted at a single data center, collecting them, and re-assemble them to a single result.</p><p>This implementation has several technical advantages:</p><ul><li>It avoids response size limitations of EIDA member services, reducing limitations to those imposed by assembling cache space of the federator instance itself.</li> <li>It allows easy merging of partial responses using request sorting and concatenation, and reducing needs to interpret them. This reduces computational needs of the federator and allows high throughput of parallel user requests.</li> <li>It reduces the variability of requests to end member services. Thus, the federator can implement a reverse loopback cache and protect end node services from delivering redundant information and reducing their load.</li> <li>As partial results are quick, and delivered in small subunits, they can be streamed to the user more or less continuously, avoiding both service timeouts and throughput bottlenecks.</li> </ul><p>The advantage of having a one-stop data access for entire EIDA still comes with some limitations and shortcomings. Having requests which ultimately map to a single data center performed by the federator can be slower by that data center directly. FDSN-defined standard error codes sent by end member services have limited utility as they refer to a part of the request only. Finally, the federator currently does not provide access to restricted data.</p><p>Nevertheless, we believe that the one-stop data access compensates these shortcomings in many use cases.</p><p>Further documentation of the service is available with ORFEUS at http://www.orfeus-eu.org/data/eida/nodes/FEDERATOR/</p>

scholarly journals Batch seismic inversion using the iterative ensemble Kalman smoother

2021 ◽  
Author(s):  
Michael Gineste ◽  
Jo Eidsvik
Keyword(s):  
Seismic Data ◽  
Time Windows ◽  
Seismic Inversion ◽  
Efficient Estimation ◽  
Solution Strategy ◽  
Adaptive Procedure ◽  
Waveform Data ◽  
Kalman Smoother ◽  
Seismic Waveform ◽  
Single Batch

AbstractAn ensemble-based method for seismic inversion to estimate elastic attributes is considered, namely the iterative ensemble Kalman smoother. The main focus of this work is the challenge associated with ensemble-based inversion of seismic waveform data. The amount of seismic data is large and, depending on ensemble size, it cannot be processed in a single batch. Instead a solution strategy of partitioning the data recordings in time windows and processing these sequentially is suggested. This work demonstrates how this partitioning can be done adaptively, with a focus on reliable and efficient estimation. The adaptivity relies on an analysis of the update direction used in the iterative procedure, and an interpretation of contributions from prior and likelihood to this update. The idea is that these must balance; if the prior dominates, the estimation process is inefficient while the estimation is likely to overfit and diverge if data dominates. Two approaches to meet this balance are formulated and evaluated. One is based on an interpretation of eigenvalue distributions and how this enters and affects weighting of prior and likelihood contributions. The other is based on balancing the norm magnitude of prior and likelihood vector components in the update. Only the latter is found to sufficiently regularize the data window. Although no guarantees for avoiding ensemble divergence are provided in the paper, the results of the adaptive procedure indicate that robust estimation performance can be achieved for ensemble-based inversion of seismic waveform data.

Evolution of the Kandilli Observatory and Earthquake Research Institute (KOERI) Seismic Network and the Data Center Facilities as a Primary Node of EIDA

2021 ◽  
Author(s):  
Musavver Didem Cambaz ◽  
Mehmet Özer ◽  
Yavuz Güneş ◽  
Tuğçe Ergün ◽  
Zafer Öğütcü ◽  
...  
Keyword(s):  
Data Center ◽  
Strong Motion ◽  
Seismic Network ◽  
Data Archive ◽  
Seismic Stations ◽  
Earthquake Research ◽  
Earthquake Research Institute ◽  
Research Facilities ◽  
Research Institute

Abstract As the earliest institute in Turkey dedicated to locating, recording, and archiving earthquakes in the region, the Kandilli Observatory and Earthquake Research Institute (KOERI) has a long history in seismic observation, which dates back to the installation of its first seismometers soon after the devastating Istanbul earthquake of 10 July 1894. For over a century, since the deployment of its first seismometer, the KOERI seismic network has grown steadily in time. In this article, we present the KOERI seismic network facilities as a data center for the seismological community, providing data and services through the European Integrated Data Archive (EIDA) and the Rapid Raw Strong-Motion (RRSM) database, both integrated in the Observatories and Research Facilities for European Seismology (ORFEUS). The objective of this article is to provide an overview of the KOERI seismic services within ORFEUS and to introduce some of the procedures that allow to check the health of the seismic network and the quality of the data recorded at KOERI seismic stations, which are shared through EIDA and RRSM.

Introducing ISMDq—A Web Portal for Real-Time Quality Monitoring of Italian Strong-Motion Data

2021 ◽  
Author(s):  
Marco Massa ◽  
Davide Scafidi ◽  
Claudia Mascandola ◽  
Alessio Lorenzetti
Keyword(s):  
Data Quality ◽  
Ambient Noise ◽  
Strong Motion ◽  
Low Noise ◽  
Data Availability ◽  
Eurocode 8 ◽  
Strong Motion Data ◽  
Motion Data ◽  
Strong Motion Network ◽  
Quality Indexes

Abstract We present the Istituto Nazionale di Geofisica e Vulcanologia Strong-Motion Data-quality (ISMDq)—a new automatic system designed to check both continuous data stream and event strong-motion waveforms before online publication. The main purpose of ISMDq is to ensure accurate ground-motion data and derived products to be rapidly shared with monitoring authorities and the scientific community. ISMDq provides data-quality reports within minutes of the occurrence of Italian earthquakes with magnitude ≥3.0 and includes a detailed daily picture describing the performance of the target strong-motion networks. In this article, we describe and discuss the automatic procedures used by ISMDq to perform its data-quality check. Before an earthquake, ISMDq evaluates the selected waveforms through the estimation of quality indexes employed to reject bad data and/or to group approved data into classes of quality that are useful to quantify the level of reliability. The quality indexes are estimated based on comparisons with the background ambient noise level performed both in the time and frequency domains. As a consequence, new high- and low-noise reference levels are derived for the overall Italian strong-motion network, for each station, and for groups of stations in the same soil categories of the Eurocode 8 (Eurocode 8 [EC8], 2003). In absence of earthquakes, 24 hr streaming of ambient noise recordings are analyzed at each station to set an empirical threshold on selected data metrics and data availability, with the goal to build a station quality archive, which is daily updated in a time span of six months. The ISMDq is accessible online (see Data and Resources) from August 2020, providing rapid open access to ∼10,000 high-quality checked automatically processed strong-motion waveforms and metadata, relative to more than 160 Italian earthquakes with magnitude in the 3.0–5.2 range. Comparisons between selected strong-motion data automatically processed and then manually revised corroborate the reliability of the proposed procedures.

The Italian Node of the European Integrated Data Archive

2021 ◽  
Vol 92 (3) ◽  
pp. 1726-1737 ◽  
Author(s):  
Peter Danecek ◽  
Stefano Pintore ◽  
Salvatore Mazza ◽  
Alfonso Mandiello ◽  
Massimo Fares ◽  
...  
Keyword(s):  
Service Management ◽  
Open Data ◽  
Data Availability ◽  
Data Archive ◽  
Waveform Data ◽  
Data Archiving ◽  
Seismological Data ◽  
Fair Principles ◽  
Key Aspects ◽  
Management Capabilities

Abstract The Orfeus European Integrated Data Archive (EIDA) provides a federated approach to the dissemination of seismological waveform data and ensures access to 12 regional seismological data centers—the EIDA nodes. The Istituto Nazionale di Geofisica e Vulcanologia (INGV) is one of the founding partners of this EIDA federation and manages the EIDA data distribution node in Italy. INGV has actively managed the smaller MedNet archive since 1990 and adopted a more comprehensive and systematic approach to seismological data archiving since 2007. The Italian EIDA node data archive currently totals 90 TBytes of waveform data available for download, originating from 25 networks and 974 stations, provided by INGV, MedNet, or contributed by various partner institutions. Geographically, it covers mainly Italy and some stations from the Mediterranean region. The archive is currently growing at a rate of approximately 11 TB/yr. INGV recently strengthened its data management capabilities, resources, and infrastructure to effectively respond to the growing scale of station inventory, archive, and volumes of delivered data, and to acknowledge increasing attention toward open data sharing, appropriate attribution, and FAIR principles (Findability, Accessibility, Interoperability, and Reuse), as well as higher demands on data quality and expectations of the scientific user community. To this end, it established a dedicated internal unit in charge of all relevant activities related to the Italian EIDA node. In this article, we address key aspects of the EIDA node in Italy such as evolution and status of the seismological waveform archive, and we describe the technical, organizational, and operational setup of data and service management. We also outline ongoing activities and future evolutions aiming to further increase the quality of services, data availability, data and metadata quality, resilience, and sustainability.

First-arrival picking with a U-net convolutional network

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. U45-U57 ◽  
Author(s):  
Lianlian Hu ◽  
Xiaodong Zheng ◽  
Yanting Duan ◽  
Xinfei Yan ◽  
Ying Hu ◽  
...  
Keyword(s):  
Seismic Data ◽  
Synthetic Data ◽  
Training Data ◽  
Convolutional Network ◽  
Data Set ◽  
Waveform Data ◽  
Near Surface ◽  
Arrival Times ◽  
Seismic Waveform ◽  
First Arrival

In exploration geophysics, the first arrivals on data acquired under complicated near-surface conditions are often characterized by significant static corrections, weak energy, low signal-to-noise ratio, and dramatic phase change, and they are difficult to pick accurately with traditional automatic procedures. We have approached this problem by using a U-shaped fully convolutional network (U-net) to first-arrival picking, which is formulated as a binary segmentation problem. U-net has the ability to recognize inherent patterns of the first arrivals by combining attributes of arrivals in space and time on data of varying quality. An effective workflow based on U-net is presented for fast and accurate picking. A set of seismic waveform data and their corresponding first-arrival times are used to train the network in a supervised learning approach, then the trained model is used to detect the first arrivals for other seismic data. Our method is applied on one synthetic data set and three field data sets of low quality to identify the first arrivals. Results indicate that U-net only needs a few annotated samples for learning and is able to efficiently detect first-arrival times with high precision on complicated seismic data from a large survey. With the increasing training data of various first arrivals, a trained U-net has the potential to directly identify the first arrivals on new seismic data.

Frequency and spatial sampling strategies for crosshole seismic waveform spectral inversion experiments

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCC79-WCC89 ◽  
Author(s):  
Hansruedi Maurer ◽  
Stewart Greenhalgh ◽  
Sabine Latzel
Keyword(s):  
Information Content ◽  
Seismic Data ◽  
Velocity Model ◽  
Similar Amount ◽  
Data Sets ◽  
Data Set ◽  
Waveform Data ◽  
Velocity Models ◽  
Seismic Waveform ◽  
Iterative Inversion

Analyses of synthetic frequency-domain acoustic waveform data provide new insights into the design and imaging capability of crosshole surveys. The full complex Fourier spectral data offer significantly more information than other data representations such as the amplitude, phase, or Hartley spectrum. Extensive eigenvalue analyses are used for further inspection of the information content offered by the seismic data. The goodness of different experimental configurations is investigated by varying the choice of (1) the frequencies, (2) the source and receiver spacings along the boreholes, and (3) the borehole separation. With only a few carefully chosen frequencies, a similar amount of information can be extracted from the seismic data as can be extracted with a much larger suite of equally spaced frequencies. Optimized data sets should include at least one very low frequencycomponent. The remaining frequencies should be chosen fromthe upper end of the spectrum available. This strategy proved to be applicable to a simple homogeneous and a very complex velocity model. Further tests are required, but it appears on the available evidence to be model independent. Source and receiver spacings also have an effect on the goodness of an experimental setup, but there are only minor benefits to denser sampling when the increment is much smaller than the shortest wavelength included in a data set. If the borehole separation becomes unfavorably large, the information content of the data is degraded, even when many frequencies and small source and receiver spacings are considered. The findings are based on eigenvalue analyses using the true velocity models. Because under realistic conditions the true model is not known, it is shown that the optimized data sets are sufficiently robust to allow the iterative inversion schemes to converge to the global minimum. This is demonstrated by means of tomographic inversions of several optimized data sets.

EIDA: The European Integrated Data Archive and Service Infrastructure within ORFEUS

2021 ◽  
Author(s):  
Angelo Strollo ◽  
Didem Cambaz ◽  
John Clinton ◽  
Peter Danecek ◽  
Christos P. Evangelidis ◽  
...  
Keyword(s):  
Scale Up ◽  
Pressure Sensors ◽  
Current Data ◽  
Data Archive ◽  
Data Types ◽  
Seismic Waveform ◽  
Data Archives ◽  
Research Organizations ◽  
Service Portfolio ◽  
Management Approaches

Abstract The European Integrated Data Archive (EIDA) is the infrastructure that provides access to the seismic-waveform archives collected by European agencies. This distributed system is managed by Observatories and Research Facilities for European Seismology. EIDA provides seamless access to seismic data from 12 data archives across Europe by means of standard services, exposing data on behalf of hundreds of network operators and research organizations. More than 12,000 stations from permanent and temporary networks equipped with seismometers, accelerometers, pressure sensors, and other sensors are accessible through the EIDA federated services. A growing user base currently counting around 3000 unique users per year has been requesting data and using EIDA services. The EIDA system is designed to scale up to support additional new services, data types, and nodes. Data holdings, services, and user numbers have grown substantially since the establishment of EIDA in 2013. EIDA is currently active in developing suitable data management approaches for new emerging technologies (e.g., distributed acoustic sensing) and challenges related to big datasets. This article reviews the evolution of EIDA, the current data holdings, and service portfolio, and gives an outlook on the current developments and the future envisaged challenges.

Capturing, Preserving, and Digitizing Legacy Seismic Data from the Montserrat Volcano Observatory Analog Seismic Network, July 1995–December 2004

2020 ◽  
Vol 91 (4) ◽  
pp. 2127-2140 ◽  
Author(s):  
Glenn Thompson ◽  
John A. Power ◽  
Jochen Braunmiller ◽  
Andrew B. Lockhart ◽  
Lloyd Lynch ◽  
...  
Keyword(s):  
Real Time ◽  
Seismic Data ◽  
Original Data ◽  
South Florida ◽  
Seismic Network ◽  
Quality Data ◽  
Spectral Amplitude ◽  
Assistance Program ◽  
Waveform Data ◽  
Amplitude Measurement

Abstract An eruption of the Soufrière Hills Volcano (SHV) on the eastern Caribbean island of Montserrat began on 18 July 1995 and continued until February 2010. Within nine days of the eruption onset, an existing four-station analog seismic network (ASN) was expanded to 10 sites. Telemetered data from this network were recorded, processed, and archived locally using a system developed by scientists from the U.S. Geological Survey (USGS) Volcano Disaster Assistance Program (VDAP). In October 1996, a digital seismic network (DSN) was deployed with the ability to capture larger amplitude signals across a broader frequency range. These two networks operated in parallel until December 2004, with separate telemetry and acquisition systems (analysis systems were merged in March 2001). Although the DSN provided better quality data for research, the ASN featured superior real-time monitoring tools and captured valuable data including the only seismic data from the first 15 months of the eruption. These successes of the ASN have been rather overlooked. This article documents the evolution of the ASN, the VDAP system, the original data captured, and the recovery and conversion of more than 230,000 seismic events from legacy SUDS, Hypo71, and Seislog formats into Seisan database with waveform data in miniSEED format. No digital catalog existed for these events, but students at the University of South Florida have classified two-thirds of the 40,000 events that were captured between July 1995 and October 1996. Locations and magnitudes were recovered for ∼10,000 of these events. Real-time seismic amplitude measurement, seismic spectral amplitude measurement, and tiltmeter data were also captured. The result is that the ASN seismic dataset is now more discoverable, accessible, and reusable, in accordance with FAIR data principles. These efforts could catalyze new research on the 1995–2010 SHV eruption. Furthermore, many observatories have data in these same legacy data formats and might benefit from procedures and codes documented here.

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