USTC-Pickers: a Unified Set of seismic phase pickers Transfer learned for China

Current popular deep learning seismic phase pickers like PhaseNet and EQTransformer suffer from performance drop in China. To mitigate this problem, we build a unified set of customized seismic phase pickers for different levels of use in China. We first train a base picker with the recently released DiTing dataset using the same U-Net architecture as PhaseNet. This base picker significantly outperforms the original PhaseNet and is generally suitable for entire China. Then, using different subsets of the DiTing data, we fine-tune the base picker to better adapt to different regions. In total, we provide 5 pickers for major tectonic blocks in China, 33 pickers for provincial-level administrative regions, and 2 special pickers for the Capital area and the China Seismic Experimental Site. These pickers show improved performance in respective regions which they are customized for. They can be either directly integrated into national or regional seismic network operation or used as base models for further refinement for specific datasets. We anticipate that this picker set will facilitate earthquake monitoring in China.

Automated summary

To address the performance drop of current popular deep learning seismic phase pickers in China, we have developed a unified set of customized pickers for different levels of use. A base picker trained with the DiTing dataset using the same U-Net architecture as PhaseNet outperforms the original model and is suitable for the entire country. Fine-tuning of the base picker using subsets of the DiTing data enables better adaptation to different regions. We provide specific pickers for major tectonic blocks, provincial-level administrative regions, the Capital area, and the China Seismic Experimental Site, all showing improved performance in their respective regions.