JpGU Meeting 2019
Session outline| Solid Earth Sciences (S) | ||
|---|---|---|
| Session Sub-category | Seismology (SS) | |
| Session ID | S-SS04 | |
| Title | New methods for seismicity characterization | |
| Short Title | New seismic analysis methods | |
| Main Convener | Name | Francesco Grigoli |
| Affiliation | ETH-Zurich, Swiss Seismological Service | |
| Co-Convener 1 | Name | Aitaro Kato |
| Affiliation | Earthquake Research Institute, the University of Tokyo | |
| Co-Convener 2 | Name | Yosuke Aoki |
| Affiliation | Earthquake Research Institute, University of Tokyo | |
| Co-Convener 3 | Name | Claudio Satriano |
| Affiliation | Institut de Physique du Globe de Paris | |
| Session Language | E | |
| Scope | In the last two decades the number of high quality seismic instruments being installed around the world has grown exponentially and probably will continue to grow in the coming decades. This data explosion has shown the limits of the current standard routine seismic analysis, often performed manually by seismologists. Exploiting the massive amount of data is a challenge that can be overcome by using new generation, fully automated and noise robust seismic processing techniques. In the last years waveform-based detection and location methods have grown in popularity and their application have dramatically improved seismic monitoring capability. More recently, Machine Learning techniques, which are a perfect playground for data-intensive applications, are showing promising results in seismicity characterization applications opening new horizons for the development of innovative, fully automated and noise robust seismic analysis methods. Such techniques are particularly useful when working with datasets characterised by a massive number of weak events with low signal-to-noise ratio, such as those collected in induced seismicity and volcanic monitoring operations. This session aims to bring to light new methods that can be applied to large datasets, either retro-actively or in near-real time, to characterize seismicity (i.e. detection, location, magnitude and source mechanisms estimation) at different scales and in different environments. We thus encourage contributions that demonstrate how the proposed methods helps improve our understanding of earthquake and/or volcanic processes. | |
| Presentation Format | Oral and Poster presentation | |
| Invited Authors | Hilary Chang (Memorial University of Newfoundland) Marius Kriegerowski (German Research Centre for Geosciences Potsdam, Germany) Natalia Poiata (Institut de Physique du Globe de Paris) | |
| Time | Presentation No | Title | Presenter | Abstract |
|---|---|---|---|---|
| Oral Presentation May 26 AM2 | ||||
| 10:45 - 11:00 | SSS04-01 | MyShake: A global smartphone seismic network to characterize urban earthquakes | Richard M Allen | |
| 11:00 - 11:15 | SSS04-02 | Full waveform-based automatic monitoring of microseismic activity using high sampling rate records: application to Garpenberg mine (Sweden) | Natalia Poiata | |
| 11:15 - 11:30 | SSS04-03 | A deep convolutional neural network for localizing and detecting earthquake swarm activity based on full waveforms: Chances, challenges and questions | Marius Kriegerowski | |
| 11:30 - 11:45 | SSS04-04 | Fast Location Parameters Determination of Seismic Events from Few Seconds of P Wave Recorded at a Single Seismological Station Using Support Vector Machine Regression | Luis Hernan Ochoa Gutierrez | |
| 11:45 - 12:00 | SSS04-05 | Foreshock activity detection by a threshold-free matched-filter technique | Shiro Hirano | |
| 12:00 - 12:15 | SSS04-06 | Automated seismic event detection and localization: An application to long-period seismicity at Aso Volcano influenced by large earthquake | Andri Hendriyana | |
| Presentation No | Title | Presenter | Abstract |
|---|---|---|---|
| Poster Presentation May 26 PM2 | |||
| SSS04-P01 | Constraint of focal mechanisms of induced seismicity by using misfit angles based on known in-situ stress | Yusuke Mukuhira | |
| SSS04-P02 | Kinematic slip imaging of the Mw 3.3 earthquake in the St. Gallen 2013 geothermal reservoir, Switzerland, using an isochrone back projection approach | Claudio Satriano | |
| SSS04-P03 | Monitoring induced seismicity with a single seismic station by combining coda wave interferometry with distance geometry solvers | Francesco Grigoli | |
| SSS04-P04 | Automatic Earthquake Locating by Stacking Characteristic Functions in a Source Scanning Method | Hilary Chang | |
| SSS04-P05 | Earthquake nowcasting: further development and application to Japan | Kazuyoshi Nanjo | |