A deep-neural-network-based phase picker, PhaseNet, was used to pick the arrival times of the P and S waves during the earthquake sequence in Cotabato and Davao del Sur, Philippines, which occurred from October to December 2019, involving five M~6 inland earthquakes with magnitudes MW 6.4, 6.6, 5.9, 6.5 and 6.7. In this study, we utilized 80 days of seismic data from stations located within 200 km of the event area and input them into PhaseNet for analysis.
The phase picks, the output of PhaseNet, were first associated and initially located using Rapid Earthquake Association and Location (REAL). Subsequently, the earthquakes were relocated using VELEST. The hypocenters were further refined using the relative location method called HypoDD.
Using these
methods, we successfully created an earthquake catalog comprising 5,017
earthquakes, which is more than those on the list by the Department of Science
and Technology – Philippine Institute of Volcanology and Seismology
(DOST-PHIVOLCS) on their website. This catalog reveals the spatial and temporal
changes in seismicity following each significant event. It also uncovers
detailed patterns in aftershock clustering, which are likely linked to complex
fault system structures that may have contributed to the seismic activity.