Earthquake Monitoring

Earthquake monitoring aims to accurately detect, locate, and characterize seismic events, improving hazard assessment and mitigation efforts. Current research emphasizes developing robust and efficient algorithms, including deep learning models like generative adversarial networks (GANs), transformers, and physics-informed neural networks (PINNs), to process seismic data from diverse sources, such as traditional seismic stations, distributed acoustic sensing (DAS) systems, and even smartphones. These advancements enhance the accuracy and speed of earthquake early warning systems, improve the resolution of subsurface imaging for applications like carbon capture monitoring, and enable more comprehensive analysis of seismic data in challenging environments. The resulting improvements in data processing and analysis are crucial for advancing our understanding of earthquake processes and for developing more effective strategies for risk reduction.