Seismic Data

Seismic data analysis focuses on extracting meaningful information from seismic waves, primarily for subsurface imaging and earthquake monitoring. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), transformers, and graph neural networks to address challenges like noise reduction, data interpolation, and feature extraction from complex time-series data. These advancements improve the accuracy and efficiency of seismic processing workflows, impacting fields such as resource exploration, carbon capture, and earthquake early warning systems. The development of foundation models and benchmark datasets further enhances the reproducibility and generalizability of these methods.