15 citations · 16 across the 2 of their papers we have counts for
3 papers
physics.geo-ph2026
Real-world application of deep learning in large-scale seismic interference attenuation: A case study in the Camie field of Angola
Jing Sun, Song Hou
In marine seismic acquisition, seismic interference (SI) occurs when energy from nearby external seismic source(s) is captured. It typically appears as coherent noise with linear o…
physics.geo-ph2024★ 15 cited
Deep learning-based shot-domain seismic deblending
Jing Sun, Song Hou, Vetle Vinje +2
To streamline fast-track processing of large data volumes, we have developed a deep learning approach to deblend seismic data in the shot domain based on a practical strategy for g…
physics.geo-ph2024★ 1 cited
DNN-based workflow for attenuating seismic interference noise and its application to marine towed streamer data from the Northern Viking Graben
Jing Sun, Song Hou, Alaa Triki
To separate seismic interference (SI) noise while ensuring high signal fidelity, we propose a deep neural network (DNN)-based workflow applied to common shot gathers (CSGs). In our…