Title: Machine Learning for Earthquake Monitoring: From Land to Ocean<\/p>\n
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Abstract:<\/p>\n
In recent years, machine learning-based arrival time picking has demonstrated remarkable accuracy and efficiency in monitoring earthquakes both on land and at sea. It has been widely applied to the rapid construction of high-precision earthquake catalogs, which contribute to a better understanding of detailed earthquake source processes, as well as their associated seismogenic mechanisms. In this talk, I will present our recently developed seamless, machine learning-based earthquake detection and location package \u2014 LOC-FLOW \u2014 as well as the OBS phase picker \u2014 OBSTransformer \u2014 and their applications. Examples include earthquake swarms, hydraulic fracturing-induced earthquakes, and marine earthquakes offshore the Cascadia region.<\/p>\n","protected":false},"excerpt":{"rendered":"