AN IMPROVED 1-D SEISMIC VELOCITY MODEL FOR THE ACTIVE TECTONIC DEFORMATION AREA OF THE SOUTH WESTERN CARPATHIAN BEND ZONE (ROMANIA)

Book Chapter in INSIGHTS OF GEOSCIENCES FOR NATURAL HAZARDS AND CULTURAL HERITAGE, Editor: Florina CHITE

The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase

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Automatic full waveform-based monitoring of induced microseismicity at Garpenberg mine, Sweden

Multiple studies have demonstrated the efficiency of automatic full waveform-based detection and localization approaches. Application of these techniques has shown significant improvement in detection capacity compared to the triggered-based system. The increased number of detected events allows to perform detailed statistical analysis of seismicity in space and time (i.e. b-value of the Gutenberg Richter law, p-exponent of the Omori law and gamma value of the inter-event times). This may permit identification of potential nucleation phases of large events using dense space-time event clusters which can provide information about stress transfer and dynamic rupture characteristics. However, real-time automatic monitoring of microseismicity in mining application is non-trivial. The two main challenges to be considered here are: high sampling rate of recorded seismic data ( kHz) and a wide range of microseismic sources (i.e. machine noise, blasts, induced seismicity). In this study, we propose an automatic full waveform-based microseismic event detection and location workflow for near-real-time seismic monitoring. We implemented and test the method on a study case of deep metal mine ( > 1km in depth) at Lappberget district of the Garpenberg mine, Sweden. The proposed method consists of two steps: event extraction and preliminary location (step 1) and relocation (step 2). Step 1 is based on multiband frequency detection and first-order amplitude ratio location. Whereas, step 2 uses backprojection technique (BacktrackBB) estimating a better constrained space-time location of hypocenters. Step 1 targets reduction of transferred 8 kHz sampled seismic data ( 60GB per day) and provides an energy-ratio-based classification of events that allows to remove machinery noise detections. We estimated that detection capacity compared to conventional triggering-based monitoring system is improved by at least a factor of 50. This increased number of detected events permits to investigate migration pattern of microseismic activity in response to production blast. The method has been implemented in a local seismic monitoring system of Ineris (France) and is consistently improved to ensure a reliable real-time detection and location

Imaging different components of a tectonic tremor sequence in southwestern Japan using an automatic statistical detection and location method

International audienceIn this study, we demonstrate the capability of an automatic network-based detection and location method to extract and analyse different components of tectonic tremor activity by analysing a 9-day energetic tectonic tremor sequence occurring at the downdip extension of the subducting slab in southwestern Japan. The applied method exploits the coherency of multiscale, frequency-selective characteristics of non-stationary signals recorded across the seismic network. Use of different characteristic functions, in the signal processing step of the method, allows to extract and locate the sources of short-duration impulsive signal transients associated with low-frequency earthquakes and of longer-duration energy transients during the tectonic tremor sequence. Frequency-dependent characteristic functions, based on higher-order statistics' properties of the seismic signals, are used for the detection and location of low-frequency earthquakes. This allows extracting a more complete (∼6.5 times more events) and time-resolved catalogue of low-frequency earthquakes than the routine catalogue provided by the Japan Meteorological Agency. As such, this catalogue allows resolving the space-time evolution of the low-frequency earthquakes activity in great detail, unravelling spatial and temporal clustering, modulation in response to tide, and different scales of space-time migration patterns. In the second part of the study, the detection and source location of longer-duration signal energy transients within the tectonic tremor sequence is performed using characteristic functions built from smoothed frequency-dependent energy envelopes. This leads to a catalogue of longer-duration energy sources during the tectonic tremor sequence, characterized by their durations and 3-D spatial likelihood maps of the energy-release source regions. The summary 3-D likelihood map for the 9-day tectonic tremor sequence, built from this catalogue, exhibits an along-strike spatial segmentation of the long-duration energy-release regions, matching the large-scale clustering features evidenced from the low-frequency earthquake's activity analysis. Further examination of the two catalogues showed that the extracted short-duration low-frequency earthquakes activity coincides in space, within about 10-15 km distance, with the longer-duration energy sources during the tectonic tremor sequence. This observation provides a potential constraint on the size of the longer-duration energy-radiating source region in relation with the clustering of low-frequency earthquakes activity during the analysed tectonic tremor sequence. We show that advanced statistical network-based methods offer new capabilities for automatic high-resolution detection, location and monitoring of different scale-components of tectonic tremor activity, enriching existing slow earthquakes catalogues. Systematic application of such methods to large continuous data sets will allow imaging the slow transient seismic energy-release activity at higher resolution, and therefore, provide new insights into the underlying multiscale mechanisms of slow earthquakes generation

Multiband array detection and location of seismic sources recorded by dense seismic networks

International audienceWe present a new methodology for detection and space-time location of seismic sources based on multiscale, frequency-selective coherence of the wave field recorded by dense large-scale seismic networks and local antennas. The method is designed to enhance coherence of the signal statistical features across the array of sensors and consists of three steps: signal processing, space-time imaging, and detection and location. The first step provides, for each station, a simplified representation of seismic signal by extracting multiscale non-stationary statistical characteristics, through multiband higher-order statistics or envelopes. This signal processing scheme is designed to account for a priori unknown transients, potentially associated with a variety of sources (e.g. earthquakes, tremors), and to prepare data for a better performance in posterior steps. Following space-time imaging is carried through 3-D spatial mapping and summation of station-pair time-delay estimate functions. This step produces time-series of 3-D spatial images representing the likelihood that each pixel makes part of a source. Detection and location is performed in the final step by extracting the local maxima from the 3-D spatial images. We demonstrate the efficiency of the method in detecting and locating seismic sources associated with low signal-to-noise ratio on an example of the aftershock earthquake records from local stations of International Maule Aftershock Deployment in Central Chile. The performance and potential of the method to detect, locate and characterize the energy release associated with possibly mixed seismic radiation from earthquakes and low-frequency tectonic tremors is further tested on continuous data from southwestern Japan

Complexity of Deep Low‐Frequency Earthquake Activity in Shikoku (Japan) Imaged From the Analysis of Continuous Seismic Data

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The effect of 2020 COVID-19 lockdown measures on seismic noise recorded in Romania

International audienceAfter the World Health Organization declared COVID-19 a pandemic in March 2020, Romania followed the example of many other countries and imposed a series of restrictive measures, including restricting people's mobility and closing social, cultural, and industrial activities to prevent the spread of the disease. In this study, we analyze continuous vertical component recordings from the stations of the Romanian Seismic Network - one of the largest networks in Europe, consisting of 148 stations - to explore the seismic noise variation associated with the reduced human mobility and activity due to the Romanian measures against COVID-19 in detail. We focused our investigation on four frequency bands - 2-8, 4-14, 15-25 and 25-40 Hz - and found that the largest reductions in seismic noise associated with the lockdown correspond to the high-frequency range of 15-40 Hz. We found that all the stations with large reductions in seismic noise (>∼ 40 %) are located inside and near schools or in buildings, indicating that at these frequencies the drop is related to the drastic reduction of human activity in these edifices. In the lower-frequency range (2-8 and 4-14 Hz) the variability of the noise reduction among the stations is lower than in the high-frequency range, corresponding to about 35 % on average. This drop is due to reduced traffic during the lockdown, as most of the stations showing such changes in seismic noise in these bands are located within cities and near main or side streets. In addition to the noise reduction observed at stations located in populated areas, we also found seismic noise lockdown-related changes at several stations located far from urban areas, with movement of people in the vicinity of the station explaining the noise reductions

Full wave-form, automatic real-time monitoring of high sampling seismic data in a metal mine: detection, location, event classification and seismic repeater matching

Full-waveform based, automatic real-time seismic monitoring tools are becoming more and more standard in seismological surveys of natural earthquakes. These methods demonstrate significant improvement in the detection capacity of microseismic events and precursors of potential larger earthquakes. In mines, the implementation of such approaches is challenging due to the presence of a wide range of seismic noises related to mining activities with signatures similar to microseismic events. In addition, high sampling frequencies of seismic data (several kHz) used in these environments pose problems for real-time data transfer and processing. Here, we propose an adapted, full-waveform based automatic processing workflow for the Ineris seismic network located at the deep levels (> 1 km depth) of the Garpenberg metal mine (Sweden). To deal with high frequency sampling (8 kHz) we designed a pre-processing step based on a multi-frequency event detection scheme and first-order amplitude-based location. Final source location is then obtained by applying an array coherency based back-projection approach (BacktrackBB) on the preselected and reduced data set. We estimate that detection capacity compared to a usual triggered monitoring system is increased by at least a factor 100. Automatic event classification is achieved (at least for the strongest events) using several standard signal parameters based on shape, location, size and frequency content. Ongoing investigations aim to build an automatic identification and classification scheme for multiplet families with highly similar wave forms using cross-correlation and template matching techniques. Results from source mechanism and parameter analysis, relocation and spatio-temporal statistics have shown that multiplet families can be interpreted as classical seismic repeaters that repetitively slip over time periods of weeks to several months after certain production blasts. Following this hypothesis, an advanced repeater monitoring approach may allow to measure indirectly aseismic slip in the mining area and to provide criteria for seismic hazard evaluation such as asperity density and dynamic rupture potential

Methodology for Full Waveform Near Real-Time Automatic Detection and Localization of Microseismic Events Using High (8 kHz) Sampling Rate Records in Mines : Application to the Garpenberg Mine (Sweden)

Recent studies have demonstrated the success of automatic full-waveform detection and location methods in analyzing and monitoring natural and induced seismicity. These approaches have been shown to provide a significant improvement in events detectability, increasing the significance of statistical analysis that permits to identify small changes of seismicity rates in space and time. Although currently nontrivial and by far nonstandard, application of such methods to seismic monitoring of active mines could significantly improve forecasting of potential destructive rockburst events. The main challenges of such applications are related to the presence of a wide range of seismic noise sources that have to do with mining activity and a high sampling rate of recorded data (several kHz), posing problems for real-time data transfer and processing. In this study, we propose an adapted full-waveform-based automatic method for the detection and location of microseismic events that makes use of continuous seismic records from an in-mine seismic network and can be adjusted to a near-real-time monitoring scheme. The method consists of two steps: (1) event extraction and amplitude ratio-based preliminary location and (2) event relocation using a coherency-based backprojection approach. The event extraction, based on multiband signal characterization implemented in the first step, allows us to overcome the challenge of high sampling rate data (8 kHz), reducing the overall volume of transferred data and providing an energy-based signal classification scheme. This allows us to remove a significant number of machinery noise sources. The technique is developed and tested on the case study of the Garpenberg mine (Sweden) monitored by a local seismic network that is maintained by Ineris. We demonstrate the improvement in event detection capacity by a factor of 50, compared with the standard triggered-based monitoring schemes. This increased number of detected microseismic events permits us to investigate the migration pattern of induced microseismicity that is generated in response to production blast