OBSU: a deep-learning seismic phase picker for OBS data using transfer learning and Unet

Yi Xie. Yongming Huang.

DOI: https://doi.org/10.70114/acmsr.2024.1.1.P75

Keywords:

Deep learning, Transfer learning, Ocean bottom seismometer, Seismic phase picking

Abstract:

Seismic phase identification and ariivals picking are two essential steps in the processing of seismic monitoring data. We propose OBSU, a transfer learning and Unet-based seismic phase picker for ocean earthquakes with multimodal inputs, using the land seismic dataset INSTANCE for pre-training to enhance performance. We test it using the ocean bottom seismometer (OBS) dataset and achieve mean absolute deviations of 0.17 s and 0.23 s for P-wave and S-wave, respectively. Meanwhile, the model results after using transfer learning are significantly better than before using it.