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| Citation: | Jiang Ce, Lü Zuoyong, Fang Lihua, 2024. Earthquake Detection Model Trained on Velocity and Acceleration Records and Its Application in Xinfengjiang Reservoir. Earth Science, 49(2): 469-479. doi: 10.3799/dqkx.2023.186
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With the construction of the "National Seismic Intensity Rapid Reporting and Early Warning" project, acceleration records data will be increasingly applied in earthquake science research. However, most current earthquake detection models use velocity records for training, which results in poor detection performance for acceleration records. This study utilized seismic records from the Guangdong Earthquake Network to train the PhaseNet_GD model for detecting velocity records and the PhaseNet_ITS model for detecting acceleration records.Based on this, a new intelligent earthquake data processing system was developed by combining the GaMMA, phase association method, and the HYPOSAT, earthquake location method. This system was used to process the 2023 ML 4.8 earthquake sequence in XinfengjiangReservoir, Heyuan, and detected events 3.8 times more than the manual catalog, with a matching rate of 93.2% and a false detection rate of 0.38%. This system can provide technical support for reservoir seismic monitoring and real⁃time data processing of regional earthquake networks.
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