Time-Reversal Imaging with Neural Operators for Real-time Earthquake Location

Hongyu Sun, Yan Yang, Kamyar Azizzadenesheli, Robert W. Clayton, & Zachary E. Ross

Submitted September 11, 2022, SCEC Contribution #12285, 2022 SCEC Annual Meeting Poster #042

Accurate and real-time determination of earthquake locations is an essential but still challenging problem. Pick-based earthquake location workflows rely on the accuracy of phase pickers and may be biased when dealing with complex earthquake sequences in complex media. Time-reversal imaging of passive seismic sources with the cross-correlation imaging condition has potential for earthquake location with high accuracy and high resolution, but carries a large computational cost. Here we present an alternative deep-learning approach for earthquake location by combining the benefits of neural operators for wave propagation and time-reversal imaging with multi-station waveform recordings. A U-shaped neural operator is trained to propagate seismic waves with various source time functions and thus can predict a back-propagated wavefield for each station within negligible time. These wavefields can be either stacked or correlated to locate earthquakes from the resulting source images. Compared with other waveform-based deep-learning location methods, time-reversal imaging accounts for physical laws of wave propagation and is expected to achieve accurate earthquake location. We demonstrate the method with the 2D acoustic wave equation on both synthetic and field data. The results show that our method can efficiently obtain high resolution and high accuracy correlation-based time-reversal imaging of earthquake sources. Moreover, our approach is flexible to the number and geometry of seismic stations, which opens new strategies for real-time earthquake location and monitoring with dense seismic networks.

Key Words
Time-reversal imaging, neural operators, earthquake location, wave propagation, correlation

Sun, H., Yang, Y., Azizzadenesheli, K., Clayton, R. W., & Ross, Z. E. (2022, 09). Time-Reversal Imaging with Neural Operators for Real-time Earthquake Location. Poster Presentation at 2022 SCEC Annual Meeting.

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