Dual-band learning for improved knowledge transfer applied to land data (Ovcharenko, O., et al, 2021)

We propose the concept of generative dual-band learning to facilitate the knowledge transfer between synthetic and field seismic data applications of low-frequency data extrapolation. We first explain the two-step procedure for the training of a generative adversarial network (GAN) that extrapolates low frequencies. Then we describe the workflow for synthetic dataset generation. Finally, we explore the feasibility of the dual-band learning concept on real near-surface land data acquired in Saudi Arabia.

References