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Earthquakes preceding large events are commonly referred to as foreshocks. They are often considered as precursory phenomena reflecting the nucleation process of the main rupture. Such foreshock sequences may also be explained by cascades of triggered events. Recent advances in earthquake detection motivates a reevaluation of seismicity variations prior to mainshocks. Based on a highly complete earthquake catalog, previous studies suggested that mainshocks in Southern California are often preceded by anomalously elevated seismicity. In this study, we test the same catalog against the Epidemic Type Aftershock Sequence model that accounts for temporal clustering due to earthquake interactions. We find that 10/53 mainshocks are preceded by a significantly elevated seismic activity compared with our model. This shows that anomalous foreshock activity is relatively uncommon when tested against a model of earthquake interactions. Accounting for the recurrence of anomalies over time, only 3/10 mainshocks present a mainshock‐specific anomaly with a high predictive power., Key Points We further investigate previous claims of significantly elevated seismic activity prior to large earthquakes in Southern California10 out of 53 mainshocks are preceded by anomalously high seismicity, but only 3 of these anomalies are exclusively related to the mainshockThese selected foreshock sequences are likely due to additional pre‐slip, aseismic processes

Volcano‐tectonic seismicity has been recorded for decades on various volcanoes and is linked with the magma transport and reservoir pressurization. Yet earthquakes often appear broadly distributed such that magma movement is difficult to infer from its analysis. We explore the seismicity that occurred before eruptions at Piton de la Fournaise in the last 5 years. Using template matching and relocation techniques, we produce a refined image of the summit seismicity, demonstrating that most earthquakes are located on a ring structure. However, only a portion of this structure is activated before each eruption, which provides an indication as to the direction of the future eruptive site. Furthermore, we show that the delay between the pre‐eruptive swarm and the eruption onset is proportional to the distance of the eruptive fissures relative to the summit cone. This reveals that the beginning of the intrusion already bears information regarding the future eruption location., Key Points We use a template matching technique to detect and relocate earthquakes during the 13 last eruptive unrests at Piton de la Fournaise volcanoAlmost all detected events are located on a ring‐shaped structure, corresponding to an area of weakness in the upper edifice of the volcanoThe location and timing of pre‐eruptive seismic swarms on this ring‐shaped structure bring information on the future eruptive site

The development of the deep geothermal site at Rittershoffen (Alsace, France) was monitored continuously by different seismic networks covering various operational periods from September 2012 to October 2014, including the drilling of the well doubletGRT1/GRT2, the thermal, hydraulic and chemical stimulations of GRT1 and circulation tests between the two wells. The seismicity induced by these operations has the potential to give valuable insight into the geomechanical behaviour of the reservoir and the geometry of the underground fracture network. However, to conduct such studies a robust seismic database is needed. In this work the parameter set up for a template matching code which will be used to obtain seismic catalogues from continuous waveforms recorded by the seismic networks at Rittershoffen is described. Furthermore, a first overview of the amount of seismic events detected by this algorithm during different operational periods and detection statistics are presented.The basic concept of the template matching technique is to calculate the correlation coefficient between the waveform of a known event, the template, and the continuous waveform over the desired time period to detect additional seismic events with similar waveforms to the template. It outperforms conventional energy detectors in terms of sensitivity to events with low signal-to-noise ratio and picking consistency. As template database, we use a manually picked seismic catalogue covering the different stimulation periods of GRT1 and part of the drilling period of GRT2. This starting catalogue contains over 1300 events. Test runs of the template matching code on a sample of the Rittershoffen data has shown that there are two parameters which can potentially influence the results significantly. One is the detection threshold, which gives the value the correlation coefficient has to exceed in order to consider a new event detected, the other is the range of the bandpass filter used to optimize the signal to noise ratio of the signals. The distribution of the correlation coefficient proved to depend strongly on which templates and stations are used for detection. To ensure an objective choice of the threshold optimized for each chosen setting we decided to implement an adaptive threshold using the approach of Slinkard et al.,2014. To determine the optimal band pass filter range a frequency analysis for the different seismic stations was conducted by comparing the frequency spectrum of the noise to the frequency spectrum of the template signals. After the parameters are set the code is applied to the periods that were already picked manually to compare the amount and distribution of the detected seismicity between the two catalogues. Additionally, an evaluation of the detection statistics is presented to see for example which templates detected most events and whether templates detect primarily events with arrival times close to their own or across all time periods.

The deep geothermal project ECOGI at Rittershoffen, 6 km south-east of Soultz-sous-Forêts, in Northern Alsace was initiated at the end 2012. A first well GRT1 has been drilled up to 2580 m. Water injection has been carried out in June 2013 to enhance the connections between the well and the reservoir by inducing hydro-shearing along the pre-existing fracture network. The operation resulted in significant induced microseismicity that was recorded by a surface seismic network made of a permanent and a temporary surface seismic network composed of 18 surface stations in total (Stations sampling frequency ranging between 100 to 300 Hz). We computed a detection function based on the ratio of the signal averaged over long and short period and reviewed manually all detections to isolate only those corresponding to seismic events with clear arrival times visible at least at 6 stations. With this procedure we identified a total of 682 seismic events. Two periods of activity can be observed: a main swarm of two days (27 and 28 June) during the injection and a second swarm that occurred on 2 July, three days after water injection ended. The first swarm includes 82% of the events in the catalog. Interestingly we also noticed that when the second phase of the injection that took place between 11:00 and 17:00 PM on the 28th of June, no seismic event was observed. The absence of seismicity during this second injection at a lower rate than the preceding one the day before is characteristic of a Kaiser effect. The second noticeable feature of the seismicity is the complete absence of seismic events between the two swarms with no earthquake recorded during the 3 days time interval. We then performed a manual picking on compressive and shear phases (P and S) for all events. Location of seismic events shows that the second swarm is located around 500m away from the first one and relative relocation using the HypoDD software was performed in order to improve the resolution of the earthquake location. Earthquakes relative relocations enhanced the clustering of the seismicity observed previously and confirmed the spatial gap between the two swarms. Local magnitudes for all events of the sequence range between -0.9 and 1.3 and the estimated magnitude of completness is 0.1. We clearly observe larger magnitudes for events of the second swarm.

The 2011, Mw9.0 Tohoku earthquake was followed by an abundant amount of seismicity providing a unique opportunity to analyze the triggering mechanism of great earthquakes. Although the Tohoku earthquake occurred close to a dense seismic network, many aftershocks that occurred in the first few hours after the mainshock are not recorded in the earthquake catalogs. Here we use a template waveform approach to recover as many as possible missing events in the first 12 hours following the Tohoku mainshock. Our analysis is able to detect about 1.4 times more events than those listed in the High Sensitivity Seismograph Network earthquake catalog. Combining our new dataset with earthquakes that occurred at latter times, we are able to observe a continuous decay of the aftershock rate and along strike expansion of aftershock area. We relate the latter observation to the occurrence of post-seismic slip over the deep interface.

15p.; International audience; Most seismic eruption forerunners are described using Volcano-Tectonic earthquakes, seismic energy release, deformation rates or seismic noise analyses. Using the seismic data recorded at Ubinas volcano (Perú) between 2006 and 2008, we explore the time evolution of the Long Period (LP) seismicity rate prior to 143 explosions. We resolve an average acceleration of the LP rate above the background level during the 2-3 hours preceding the explosion onset. Such an average pattern, which emerges when stacking over LP time series, is robust and stable over all the 2006-2008 period, for which data is available. This accelerating pattern is also recovered when conditioning the LP rate on the occurrence of an other LP event, rather than on the explosion time. It supports a common mechanism for the generation of explosions and LP events, the magma conduit pressure increase being the most probable candidate. The average LP rate acceleration toward an explosion is highly significant prior to the higher energy explosions, supposedly the ones associated with the larger pressure increases. The dramatic decay of the LP activity following explosions, still reinforce the strong relationship between these two processes. We test and we quantify the retrospective forecasting power of these LP rate patterns to predict Ubinas explosions. The prediction quality of the forecasts (e.g. for 17% of alarm time, we predict 63% of Ubinas explosions, with 58% of false alarms) is evaluated using error diagrams. The prediction results are stable and the prediction algorithm validated, i.e. its performance is better than the random guess.