Exploration seismology uses reflected and refracted seismic waves, emitted from a
controlled (active) source into the ground, and recorded by an array of seismic sensors …

Noise suppression is an essential step in many seismic processing workflows. A portion of
this noise, particularly in land datasets, presents itself as random noise. In recent years …

Denoising is an indispensable step in seismic data processing. Deep-learning-based
seismic data denoising has been recently attracting attentions due to its outstanding …

Facies identification is a powerful means to predict reservoirs. We achieve facies
identification using a relevance vector machine (RVM) and develop a facies discriminant …

Seismic acquisition footprints appear as stably faint and dim structures and emerge fully
spatially coherent, causing inevitable damage to useful signals during the suppression …

We design a fully automated system for real‐time magnitude estimation based on a vision
transformer (ViT) network. ViT is an attention mechanisms, which guides the proposed …

Seismic random noise attenuation is a key step in seismic data processing. The random
seismic data recorded by the detector tends to have strong noise, and this noisy seismic …

For seismic random noise attenuation, deep learning has attracted much attention and
achieved promising performance. However, compared with conventional methods, the …

Deep-learning-based methods have been successfully applied to seismic data random
noise attenuation. Among them, the supervised deep-learning-based methods dominate the …

In microseismic monitoring, achieving an accurate and efficient first‐arrival picking is crucial
for improving the accuracy and efficiency of microseismic time‐difference source location. In …