Vibroseis Data

Vibroseis data, acquired using seismic vibrators, is crucial in geophysical exploration but suffers from artifacts like "ringing," which obscures subsurface features. Current research focuses on improving data quality through advanced signal processing techniques, employing deep learning architectures such as convolutional neural networks (CNNs) and InceptionTime networks to attenuate ringing and enhance signal clarity for improved interpretation. These advancements lead to more accurate seismic imaging and better subsurface characterization, impacting hydrocarbon exploration, geological mapping, and other earth science applications.