Advances And Applications Of Passive Seismic Source Characterization

Source characterization is a fundamental task of passive seismic monitoring. Spatial-temporal evolution of both, point sources and finite-fault source, provides essential information for timely seismic hazard management and advanced analysis of the seismicity in the monitored areas. In the last few decades, the rise of dense seismic arrays, increase of high-performance computing resources, and development of advanced array-based techniques lead to studies using recorded wavefields in great detail. Full waveform inversion can invert passive seismic source parameters with an iterative framework, which connects the delay-and-sum imaging technique and kernel-based inversion strategy. Moreover, emerging technologies like distributed acoustic sensing and machine learning also have great potential in advancing passive seismic imaging and source characterization. Besides, non-earthquake sources and ambient noise, as unconventional and passive sources, are also undergoing rapid development in infrastructure monitoring and subsurface imaging, due to the emergence of sensitive sensors and modern techniques like seismic interferometry.