Boundary Conditions for Seismic Imaging: Computational and Geophysical Points of View

Theoretically, waves propagate their to infinity or continue until vanishing. This is not applicable in modelling a seismic imaging since we truncate model to a computational grid; modelling a region of interest. So, absorbing all incoming energy at the boundaries of a grid mimics a real-life infinite media. Many approaches attempt to mimic different kinds of boundary conditioning e.g. Sponge, PML, random boundaries, etc. The objective of this study is to find the best compromise between geophysical and computational standpoint and find the best quality of the attenuation with a minimum number of additional grid points. We reviewed 2 RTM implementations; the conventional RTM with Sponge and CPML and a 3-prop random velocity RTM. Our findings show that applying IPP ZFP AVX512 compression to the conventional RTM yields a speedup of around ~5.3x, run on 3DNAND P4600x SSD. Although RTM with random boundaries gives a speedup in excess of ~7x relative to the conventional RTM, it faces geological limitations due to the reflected noises. On the other hand, CPML is the best for geophysical standpoint with extra computations, going beyond 16 CPML grid points adds significant computation time. While Sponge is based on simple exponential decaying function with low computational overhead, cannot easily reach the average CPML damping.