Acoustic and Elastic Full Waveform Tomography

Abstract

For a better estimation of subsurface parameters we develop imaging methods that can exploit the richness of full seismic waveforms. Full waveform tomography (FWT) is a powerful imaging method and emerges as an important procedure in hydrocarbon exploration and underground construction. It is able to recover high-resolution subsurface images from recorded seismic data. In this work, we demonstrate the performance of our parallel time-domain implementations applied to 2D and 3D problems. The results of synthetic feasibility studies—representing applications with a realistic background—illustrate the ability of FWT to reconstruct structures at small scale lengths. We also show first results of an FWT application to real seismic data recorded by a marine survey. Optimal parallelization strategies, such as domain decomposition and shot parallelization, are used in seismic modeling to exploit the possibilities of the high-performance computer HERMIT and to allow efficient FWT computations. FWT implementations show a convincing scaling behaviour. However, a competing benchmark of seismic modeling exhibits some performance drawbacks. Further software improvements of the modeling implementations might be necessary.