PROJECT TITLE :

Parallel Scalability of a Fine-Grain Prestack Reverse Time Migration Algorithm

ABSTRACT:

Seismic imaging has evolved considerably due to the high demand from the oil/gas trade for hardware technological advancements, boosting the event of more sophisticated algorithms. So as to deliver the quality and accuracy required, the execution of those algorithms might cause time infeasible solutions. Aiming at performance improvement, this work conducted the parallelization of the core of a reverse time migration (RTM) algorithm. Furthermore, analysis such as speedup and efficiency was performed so as to assess the scalability of the proposed method. Whereas the numerous parallelization efforts so way cope with coarse-grain approaches, this letter tackles the intrashot fine-grain parallelization of prestack RTM, that increases the concurrency degree of the algorithm. Results using a pair of-D synthetic information show that the proposed approach is scalable, that means that that an increase in hardware resources and/or in problem size can cause a proportional increase in speed and/or accuracy.