PhaseNet workflow boosts seismic wave detection accuracy

Researchers have developed a new workflow using the PhaseNet machine learning model to improve seismic wave detection on teleseismic data. This workflow, implemented with MsPASS, significantly enhances the recall of P-wave picks by over 700% compared to models trained on regional data. While increasing model size improved accuracy, it drastically reduced inference speed, suggesting GPUs are more suitable than CPUs for scaling this application. AI

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IMPACT Improves seismic data analysis accuracy, potentially aiding in earthquake detection and research.

RANK_REASON The cluster contains an academic paper detailing a new methodology and benchmark results for a machine learning model. [lever_c_demoted from research: ic=1 ai=1.0]

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• MsPASS
• NVIDIA A100 GPU
• PhaseNet
• USArray Array Network Facility (ANF)

• paper
• other