Seismic Phase Identification with Speech Recognition Algorithms
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- ENSCO, Springfield, VA (United States)
Seismic signals are composed of the seismic waves (phases) that reach a sensor, similar to the way speech signals are composed of phonemes that reach a listener's ear. Large/small seismic events near/far from a sensor are similar to loud/quiet speakers with high/low-pitched voices. We leverage ideas from speech recognition for the classification of seismic phases at a seismic sensor. Seismic Phase ID is challenging due to the varying paths and distances an event takes to reach a sensor, but there is consistent structure of the makeup (e.g. ordering) of the different phases arriving at the sensor.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1474260
- Report Number(s):
- SAND--2018-10472R; 668163
- Country of Publication:
- United States
- Language:
- English
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