Identification of Rare Multiple Core-Mantle Boundary Reflections PmKP Up To P7KP With Deep Learning

Abstract

The core-mantle boundary (CMB) marks the most dramatic changes in physical properties within the Earth, and plays a critical role in the understanding of the Earth's dynamics. PmKP waves are seismic phases that reflect (m − 1) times under the CMB and are useful for studying the complex CMB structure. We present an automated workflow for detecting PmKP phases using multi-station records from global seismic stations. We employ a novel sampling method to extract PmKP waveforms into a 2-D matrix. Two deep neural networks are then utilized for initial phase detections and subsequent slowness validations. Numerous PmKPab (3 ≤ m ≤ 7) and their CMB diffracted signals were identified for deep earthquakes (magnitude >6) occurred from 2000 to 2020, including diffracted P7KPab waves with diffraction lengths of nearly 20°. Our approach significantly improves the efficiency of PmKP phase identification and holds the capability to detect other weak core phases, such as PKiKP.