Automatic detection of seismic event based on eXtreme gradient boosting
This paper presents an automatic seismic event detection method based on eXtreme gradient boosting(XGBoost)by integrating intelligent strategies and leveraging the similarity characteristics of adjacent traces in seismic data.The pro-posed method is validated through programming and testing on both simple layered and complex Marmousi models.The detec-tion tests conducted on noisy data and the real data demonstrate the method̍s robustness and adaptability,even in low signal-to-noise ratio(SNR)conditions(-6.98 dB),achieving a seismic event detection precision of 90%.Additionally,single channel contrast quantitative analysis and comparison of algorithm prediction accuracy under various SNR conditions further confirm the method̍s feasibility and applicability.
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