Predicting Subsurface Layer Thickness and Seismic Wave Velocity Using Deep Learning: Knowledge Distillation Approach
TL;DR
This study uses deep learning with knowledge distillation to predict subsurface layer thickness and seismic wave velocity, overcoming computational limits of traditional methods. It enhances seismic interpretation by reducing complexity and handling noisy data.
Predicting Subsurface Layer Thickness and Seismic Wave Velocity Using Deep Learning: Knowledge Distillation Approach
Amir Moslemi; Anna Briskina; Jason Li; Zubeka Dang; Peyman Moghaddam
https://doi.org/10.1109/ACCESS.2024.3521895
Volume 13
Seismic interpretation is a crucial task in geophysics, requiring accurate prediction of subsurface layer thickness and seismic wave velocity. Traditional methods are computationally intensive and often hindered by noise in seismic data. Deep learning offers a promising solution to analyze complex geographical structures, but its computational complexity can be a barrier for deployment. This study...