This talk presents a serverless approach to seismic imaging in the cloud based on high-throughput containerized batch processing, event-driven computations and a domain-specific language compiler for solving the underlying wave equations. A 3D case study on Azure demonstrates that this approach allows reducing the operating cost of up to a factor of 6, making the cloud a viable alternative to on-premise HPC clusters for seismic imaging.

We apply Full Waveform Inversion (FWI) to narrow azimuth (NAZ) towed streamer data acquired in the Barents Sea. This study is over the Samson Dome region and the aim of the FWI is to resolve the velocity field, which is known for its geological and structural complexity in this area. The FWI result shows a spatial consistency that was unexpected from the standard 3D NAZ dataset and demonstrates the potential use of FWI velocity models in geological interpretation and shallow geohazard detection, even if the FWI result is effectively driven by the combination of velocity, anisotropy and density, rather than just P-wave velocity. Finally, as one would expect, the dramatic improvement in the accuracy and resolution of the velocity model gives rise to improved seismic imaging.

No abstract

No abstract

No abstract