Automatic moment tensor determination for the Hellenic Unified Seismic Network.

Triantafyllis, Nikolaos; Sokos, Efthimios; Ilias, Aristidis

doi:10.12681/bgsg.10912

Cited by 4 publications

(4 citation statements)

References 17 publications

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“…Different research results conclude that an acceptable agreement between two FM solutions is given by angle differences of the order of a few tens of degrees, while a strong variance corresponds to an angle difference greater than 50 °(or 60 °) (Vannucci et al, 2004;Triantafyllis 2014;Triantafyllis et al, 2016). Triantafyllis et al (2013) found an average error between manual and the automatic FM solutions computed using Scisola of Φ ≈ 37 °. Moreover, based on heuristic analyses from our statistical results, in this work we assume a similarity threshold Φ th < 30 °.…”

Section: Minimum Rotated Angle Metric To Measure Similarity Between T...mentioning

confidence: 92%

“…In this work, we choose an MRA threshold value of Φ th = 30 °(Triantafyllis 2014; Kagan 2007), below which two FM solutions are deemed sufficiently similar, suggesting that the proposed one may indeed be used as a first guess for the new earthquake with unknown FM solution. This value is motivated by earlier studies on the similarity between FM solutions (Triantafyllis et al, 2013, Triantafyllis et al, 2016Altunel and Pinar 2021), and by the observation that differences between FM solutions for an earthquake provided by different agencies are typically below Φ = 30 °. From this point of view both methods described in the previous subsection can be considered supervised techniques, because the FM solution for the new-event is already known.…”

Section: Methodology Applicationmentioning

confidence: 99%

“…Figure 2 depicts some examples of different MRA values computed from the shown FM solutions.Different research results conclude that an acceptable agreement between two FM solutions is given by angle differences of the order of a few tens of degrees, while a strong variance corresponds to an angle difference greater than 50 °(or 60 °)(Vannucci et al, 2004;Triantafyllis 2014;Triantafyllis et al, 2016) Triantafyllis et al (2013). found an average error between manual and the automatic FM solutions computed using Scisola of Φ ≈ 37 °.…”

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confidence: 95%

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A Statistical Approach Towards Fast Estimates of Moderate-To-Large Earthquake Focal Mechanisms

et al. 2022

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Emerging high-performance computing systems, combined with increasingly detailed 3-D Earth models and physically consistent numerical wave propagation solvers, are opening up new opportunities for urgent seismic computing. This may help, for instance, to guide emergency response teams in the wake of large earthquakes. A key component of urgent seismic computing is the early availability of source mechanism estimates, well before conventional and time-consuming moment tensor inversions are carried out and published. Here, we introduce a methodology that rapidly estimates focal mechanisms (FM) for moderate and large earthquakes (Mw > 4.0) by means of statistical and clustering algorithms. The fundamental rationale behind the method is that events of a certain size tend to be similar to other events of similar size in similar locations. In this work, two different strategies are used to provide different FM solutions: the first is based only in spatial considerations including statistical analysis, and the other one is based on a data clustering algorithm. We exemplify our methodology with six different subsets of the open-access Global Centroid Moment Tensor (GCMT) catalog. Specifically, our study datasets include events from Japan, New Zealand, California, Mexico, Iceland, and Italy, which represent six seismically active regions, with a large FM variability. Our results show a 70–85% agreement between our fast FM estimates and inversion results, depending on the particular tectonic region, dataset size, and magnitude threshold. In addition, our FM estimation strategies only spend few seconds for processing, since they are totally independent of seismic record retrieval and inversion. Albeit not meant to be a substitute for CMT inversions, our methodologies can bridge the time gap between earthquake detection and FM inversion.

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Section: Minimum Rotated Angle Metric To Measure Similarity Between T...mentioning

confidence: 92%

Section: Methodology Applicationmentioning

confidence: 99%

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confidence: 95%

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A Statistical Approach Towards Fast Estimates of Moderate-To-Large Earthquake Focal Mechanisms

et al. 2022

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“…MT retrieval software packages for regional distances include FMNEAREG (Delouis et al, 2008) and (Maercklin et al, 2011), KIWI (Cesca et al, 2010;Yagi and Nishimura, 2011) and ISOLA Zahradník, 2008, 2013). The last one has been used for research applications, for example, (Agurto et al, 2012;Quintero et al, 2014) (Triantafyllis et al, 2013) combined with the rapid evolution of the widely known seismological software, SeisComP3 (http://www.seiscomp3.org) (Weber et al, 2007), paved the way for the scisola (Triantafyllis et al, 2015) software implementation; a free and open-source code for automatic and real-time MT monitoring based on the ISOLA code and tightly connected to SeisComP3. The source code and the user manual of scisola can be found at GitHub hyperlink (https://github.com/nikosT/scisola).…”

Section: Introductionmentioning

confidence: 99%