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Seismic Phase Picking

Yuchen Wang, Ruihuan Wang

Abstract

Seismic phase picking, which aims to determine the arrival time of P- and S-waves according to seismic waveforms, is fundamental to earthquake monitoring. Generally, manual phase picking is trustworthy, but with the increasing number of worldwide stations and seismic monitors, it becomes more challenging for human to complete the task comprehensively. In this work, we explore multiple ways to do automatic phase picking, including traditional and learning-based methods.

Seismic Phase Picking

Abstract

Seismic phase picking, which aims to determine the arrival time of P- and S-waves according to seismic waveforms, is fundamental to earthquake monitoring. Generally, manual phase picking is trustworthy, but with the increasing number of worldwide stations and seismic monitors, it becomes more challenging for human to complete the task comprehensively. In this work, we explore multiple ways to do automatic phase picking, including traditional and learning-based methods.

Paper Structure

This paper contains 15 sections, 3 equations, 6 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Dataset
  3. Basic information
  4. Features
  5. Traditional method
  6. Learning-based method
  7. Data preprocessing and label designing
  8. Models
  9. CNN-based model: PhaseNet
  10. Attention-based model: EQTransformer
  11. Loss
  12. Experiment
  13. Discussion
  14. Ideas on single-trace phase picking
  15. Ideas on multi-trace phase picking

Figures (6)

  • Figure 1: A glance into distributional features of the INSTANCE dataset.
  • Figure 2: An example of data and labeling.
  • Figure 3: PhaseNet architecture (layer dimensions modified by us) from zhu2019phasenet.
  • Figure 4: EQTransformer architecture (taken from mousavi2020earthquake).
  • Figure 5: Strong noise, EQTransformer cannot find waves and AR Pick gives wrong predictions.
  • ...and 1 more figures