DL-fused elastic FWI: Application to marine streamer data

• DOI: 10.1190/image2022-3745846.1
• Publication Date: 2022-08-15T23:22:41Z
• Authors: Pavel Plotnitskii; Oleg Ovcharenko; Vladimir Kazei; Daniel Peter; Tariq Alkhalifah
• Keywords: 01 natural sciences; 0105 earth and related environmental sciences

Low-frequency data is crucial for successful retrieval of low-wavenumber model component in seismic full-waveform inversion (FWI), yet it often limited by hardware. Deep learning (DL) can fuse early high-wavenumber updates elastic FWI and map them into desired that would be available from low-frequency data. FusionNET-based convolutional neural network (CNN) trained on a synthetic dataset produces meaningful models taking initial iterations field as inputs. Elastic initiated "DL-fused" shows improved convergence generated unrelated to training real-world marine streamer