Learning to unflood the salt: Application on vintage GOM data (Alali, A.A., and Alkhalifah, T., 2022)
The GOM data below shows the challenges of having a limited offset of 4.8 and a minimum usable frequency of about ~6Hz. Next to the data is the legacy model with picked salt. The figures below illustrate the approach and the result of unflooding the GOM.
We start from a flooded version of the legacy model and then apply FWI. Finally, we use the network to unflood the salt. The result shows good potential of unflooding the salt and provides results similar to the legacy model except at the edges.
References
Alali, A.A., and Alkhalifah, T., 2022, "Learning to unflood the salt: Application on vintage GOM data", submitted to the 83rd EAGE Annual Conference and Exhibition.
Alali, A.A., and Alkhalifah, T., 2022, "Learning to unflood the salt: Application on vintage GOM data", submitted to the 83rd EAGE Annual Conference and Exhibition.