Can I read Integrating U-nets into a Multi-scale Waveform Inversion for Salt Body Building on EtoBox?

Integrating U-nets into a Multi-scale Waveform Inversion for Salt Body Building by Alali, Abdullah; Alkhalifah, Tariq is a scholarly article available to read on EtoBox.

What is Integrating U-nets into a Multi-scale Waveform Inversion for Salt Body Building about?

In salt provinces, full-waveform inversion (FWI) is most likely to fail when starting with a poor initial model that lacks the salt information. Conventionally, salt bodies are included in the FWI starting model by interpreting the salt boundaries from seismic images, which is time-consuming and prone to error. Studies show that FWI can improve the interpreted salt provided that the data are recorded using long offsets, and contain low frequencies, which are not always available. Thus, we develop an approach to invert for the salt body starting from a poor initial model, limited data offsets, and the absence of low frequencies. We leverage deep learning to apply multi-stage flooding and unflooding of the velocity model. Specifically, we apply a multi-scale FWI using three frequency bandwidths. We apply a network after each frequency scale. After the first two bandwidths, the networks are trained to flood the salt, while the network after the last frequency bandwidth is trained to unflood it. We verify the method on the synthetic BP 2004 salt model benchmark. We only use the synthetic data of short offsets up to 6 km and remove frequencies below 3 Hz. We also apply the method to rea

Author

Alali, Abdullah; Alkhalifah, Tariq

Published

2023

Language

EN