Backprojection (BP) methods are widely used for estimating the fault rupture processes; however, they are inherently susceptible to noise. Hence, noise suppression is an important research target. In this paper, we develop a fault rupture imaging method by combining beamforming-based BP and MUltiple Signal Classification (MUSIC), which realizes artificial noise suppression at a high spatial resolution. The stations are grouped into arrays according to the SH wave radiation coefficients, and MUSIC analysis is performed on each array. The MUSIC spectral images of these arrays are binarized and then multiplied by the BP images. Spatial filtering is also applied to the images based on the possible range of the rupture velocity and rise time. When tested using synthetic test data, the proposed method worked as expected. We then applied this method to the 2016 Kumamoto earthquake by interpolating the travel times from the observed travel times of relocated hypocenters using a 3-D velocity structure model. In the area of large slip and slip rate approximately 30–50 km from the hypocenter on the Futagawa fault, the spatiotemporal evolution of the fault ruptures and waveform inversion results were generally in harmony. The distributions of the low- and high-frequency seismic radiations are complementary, as is understood in the context of fault rupture physics. This method can aid in understanding and modeling the details of seismic radiation sources, enabling the accurate prediction of strong ground motion even in near-fault areas.
ASJC Scopus subject areas
- Geochemistry and Petrology
- Earth and Planetary Sciences (miscellaneous)
- Space and Planetary Science