Statistical analysis of the 2012–2013 Torreperogil–Sabiote seismic series, Spain

Yazdi, Pouye; Hainzl, Sebastian; Gaspar‐Escribano, Jorge M.

doi:10.1007/s10950-016-9630-4

Cited by 7 publications

(4 citation statements)

References 28 publications

(33 reference statements)

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“…To balance the increasing degree of freedom for decreasing nvalues and the increasing fit quality, the Akaike Information Criterion (AIC) is used (Helmstetter & Sornette 2003;Marsan et al 2013;Yazdi et al 2017).…”

Section: Time Dependent Background Etas Modelmentioning

confidence: 99%

Time-dependent and spatiotemporal statistical analysis of intraplate anomalous seismicity: Sarria-Triacastela-Becerreá (NW Iberian Peninsula, Spain)

Crespo-Martín

Martín-González

Yazdi

et al. 2021

Geophysical Journal International

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Summary The Sarria-Triacastela-Becerreá seismicity is located in an intraplate region considered seismically stable, but in 1995 started an unprecedented earthquake activity in the area. Since then an anomalous long-term continuous seismicity remains until now in the same location. Despite the long-term seismicity and the large magnitudes for the region standards (5.1 Mw), the origin and mechanisms of this seismicity remains unclear. The isolation of background from the mainshock-aftershock contribution by means of the application of the Epidemic Type Aftershock Sequences (ETAS) model, the spatial depiction, and the resemblance to near seismic regions allow us to identify several seismicity behaviours. From 1995 to 1998/99, the seismicity in this location mainly consists of intensive and deeper earthquake sequences linked to the 1995 and 1997 mainshocks. Our results suggest that the mainshocks triggered aftershocks and additionally initiated or facilitated aseismic processes. A likely scenario is that the mainshocks broke a sealed source at depth allowing a subsequent intrusion of high-pressurized fluids from depth. The resemblance of this period with Zamora seismic characteristics proposes that Triacastela seismicity was also initiated by tectonic activity. From 1998/99 to 2018, a change in seismicity is observed, the background contribution took control and swarm-type activity is predominant. While the earthquake rate decreases, the relative background contribution goes up. Actually, after 2013 the clusters almost disappear and background contribution achieves 55 per cent of the total activity. The spatial migration to the southeast and the upward trend to shallower depth support fluid migration as possible driving mechanism responsible for the transient seismicity in this period. The swarm-type activity in Triacastela in later periods and the resemblance of b-values with Ponte Caldelas and Ventaniella seismicity suggest that the seismicity in Triacastela is related to fluid migration and the reactivation of fractured areas. We propose that the mechanism of this anomalous and long-term seismicity in Triacastela is the mix of different mechanisms, starting with the tectonic seismicity, generated during the 1995 and 1997 seismic sequences, which initiated a fluid upward migration through fractured crustal fault patches, observed after 1998–99, and responsible for the seismicity during the following 20 years.

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Section: Time Dependent Background Etas Modelmentioning

confidence: 99%

Time-dependent and spatiotemporal statistical analysis of intraplate anomalous seismicity: Sarria-Triacastela-Becerreá (NW Iberian Peninsula, Spain)

Crespo-Martín

Martín-González

Yazdi

et al. 2021

Geophysical Journal International

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“…To ensure homogeneity and to be able to compare the results of Automatic seismic swarm analyzer 13 the program between both data sets, we have used the same criteria to select the templates. Previous studies have evaluated the completeness magnitude of the IGN catalog for both swarms, obtaining a value of 1.2 mbLg (González 2017) for the pre-eruptive phase of El Hierro and 1.5 mbLg (Yazdi et al 2017) for Torreperogil. Accordingly to this values, we have selected as templates those earthquakes from both catalogs that have a magnitude equal to or greater than 1.5 mbLg.…”

Section: Datamentioning

confidence: 99%

Automatic seismic swarm analyzer system based on template matching algorithms and Master-Cluster relative location methods

Suárez¹,

Cerdeña²,

Fresno³

2021

Preprint

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Seismic swarms may have periods of intense activity with a high number of earthquakes per hour, with overlapping events and/or low signal-to-noise ratio seismic records. During these intervals, the manual characterization of the activity can become very complex to perform by seismic or volcanic observatories, resulting in inhomogeneous seismic catalogs. In order to tackle this problem, we have developed a set of automatic algorithms capable of detecting earthquakes, picking their P and S arrivals and locating the events with absolute and relative methodologies. Detections are performed over the filtered seismic energy while phase picking is based in the correlation of new events with a set of previous well-characterized templates.Absolute locations are computed using traditional algorithms as Hypoellipse and for relative locations we introduce a novel technique Master-Cluster, which is a hybrid between the double differences and the master event.The algorithms have been tested on real data of two series corresponding to two different tectonic regimes: the volcanic pre-eruptive swarm of El Hierro, Spain (2011) and the tectonic seismic series of Torreperogil, Spain (2012. Both data sets are considerably different in terms of epicentral distances and distribution of the network varying from stations very close to the activity at El Hierro (5-20 km) to regional distances in the case of Torreperogil (10-180km). EAD Suarez et al.The templates were taken as a partial dataset of 3 600 (El Hierro) and 800 (Torreperogil) relocated earthquakes from the manual regional catalog. Based on these datasets, the algorithm was able to improve the number of events by a factor of 6 in El Hierro and 10 in Torreperogil, producing a seismic catalog between 3 and 4.5 times larger than the manually obtained one.An additional test was performed with the smaller earthquakes (local magnitude<1.5) which were not included in the set of templates, resulting not only in a good factor of success -larger than 65% of events were retrieved in both series-but also an enhancement in their automatic locations was observed with a more clustered seismicity than the previous catalog.

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“…According to the study by 17 , the ETAS model is the best model for describing short-term seismicity (see also 18 ). The ETAS model performed quite well in prospectively forecasting the seismicity within various operational frameworks in California, Greece, Italy, Japan, Spain, New Zealand, and Iceland 6,[18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33] . It has been employed for time-dependent seismic hazard 8,24,32,34,35 , and risk and loss forecasting 8,34,[36][37][38][39] .…”

Section: Introductionmentioning

confidence: 99%

Improvements to seismicity forecasting based on a Bayesian spatiotemporal ETAS model: Application to 2017-2019 Kermanshah seismic sequence in Western Iran

Ebrahimian

Jalayer

Asayesh

et al. 2022

Preprint

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The epidemic-type aftershock sequence (ETAS) model provides an effective tool for predicting the spatio-temporal evolution of aftershock clustering in short-term. Based on this model, a fully probabilistic procedure was previously proposed by the first two authors for providing spatio-temporal predictions of aftershock occurrence in a prescribed forecasting time interval. This procedure exploited the versatility of the Bayesian inference to adaptively update the forecasts based on the incoming information provided by the ongoing seismic sequence. In this work, this Bayesian procedure is improved: (1) the likelihood function for the sequence has been modified to properly consider the piecewise stationary integration of the seismicity rate; (2) the spatial integral of seismicity rate over the whole aftershock zone is calculated analytically; (3) background seismicity is explicitly considered within the forecasting procedure; (4) an adaptive kernel Markov Chain Monte Carlo simulation procedure is adopted; (5) leveraging the stochastic sequences generated by the procedure in the forecasting interval, the N-test and the S-test are adopted to verify the forecasts. This framework is demonstrated and verified through retrospective early forecasting of seismicity associated with the 2017-2019 Kermanshah seismic sequence activities in western Iran in two distinct phases following the main events with Mw7.3 and Mw6.3, respectively.

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Statistical analysis of the 2012–2013 Torreperogil–Sabiote seismic series, Spain

Cited by 7 publications

References 28 publications

Time-dependent and spatiotemporal statistical analysis of intraplate anomalous seismicity: Sarria-Triacastela-Becerreá (NW Iberian Peninsula, Spain)

Time-dependent and spatiotemporal statistical analysis of intraplate anomalous seismicity: Sarria-Triacastela-Becerreá (NW Iberian Peninsula, Spain)

Automatic seismic swarm analyzer system based on template matching algorithms and Master-Cluster relative location methods

Improvements to seismicity forecasting based on a Bayesian spatiotemporal ETAS model: Application to 2017-2019 Kermanshah seismic sequence in Western Iran

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