Automatic Time Picking for Weak Seismic Phase in the Strong Noise and Interference Environment: An Hybrid Method...

Area of Science:

• Seismology
• Geophysics
• Signal Processing

Background:

• Accurate seismic phase travel-time curve extraction is crucial for understanding underground structures.
• Increasing data volumes challenge manual processing, necessitating automated solutions.
• Traditional methods struggle with large datasets and outlier detection.

Purpose of the Study:

• To develop a novel, automated scheme for seismic arrival time picking.
• To improve the accuracy and efficiency of seismic data analysis.
• To address the limitations of manual processing in seismology.

Main Methods:

• An improved multi-channel cross-correlation method using L1 norm for preliminary results.
• A controllable measurement mode for enhanced signal similarity analysis.
• A post-correction step leveraging beamforming signal gain properties.

Main Results:

• Successful automatic detection of direct water waves, crustal refracted waves, and upper mantle reflected waves.
• Demonstrated effectiveness of the proposed two-step automated scheme on actual seismic data.
• Achieved superior overall performance compared to traditional methods.

Conclusions:

• The proposed automated arrival time picking scheme offers a robust and efficient solution for seismological analysis.
• The combined approach of L1 norm cross-correlation and beamforming provides accurate seismic wave detection.
• This method presents a cost-effective and high-performing alternative for processing large seismic datasets.