Speaker
Description
This paper summarizes the advances in the application of machine learning to seismic monitoring data processing. Then it focuses on our work including local events detection based on multi-task Convolutional neural network (CNN), Generative Adversarial Network - Long Short-Term Memory(GAN-LSTM) joint network applied to seismic noise signal recognition, the seismic phase sequence detection based on transformer, and seismic event association based on probabilistic models.
Finally, the trend of the development and potential challenges with machine learning applications are discussed.
Promotional text
The seismic monitoring data model was built using machine learning and deep learning. Phase picking, noise signal recognition, and event association methods were established to realize seismic event detection.
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