  Seismic imaging is a computationally demanding and data-intensive activity in
the oil and gas industry. Reverse Time Migration (RTM) used in seismic
applications needs to store the forward-propagated wavefield (or source
wavefield) on disk. Aiming to mitigate the storage demand, we develop an RTM
that implements the source wavefield reconstruction by introducing a new wave
equation to the problem. We adjust the initial and boundary conditions to take
advantage of the properties of random boundary conditions (RBC). The RBC does
not suppress unwanted waves coming from the artificial boundary enabling the
full wavefield recovery. Besides, it explores low correlations with
non-coherent signals due to the random velocities in the boundary. We also
develop compiler-guided implementations on a vector processor for seismic
modeling and RTM, essential for Least-square Migration, Full Waveform
Inversion, and Uncertainty Quantification applications. We test the seismic
modeling and RTM on the 2-D Marmousi benchmark and 3-D HPC4E Seismic Test
Suite. The numerical experiments show that the RTM which implements the
wavefield reconstruction presents the best results in terms of execution time
and hard disk demand. Lastly, the vector processor implementation is the one
that requires fewer code modifications compared to the optimized baseline
versions of the seismic modeling and RTM and GPU implementations, particularly
for large 3D grids.
