Abstract:

Reverse-time migration is the most accurate seismic data prestack depth migration method, but the computing needs of its highintensity limit its largescale computing applications. The development of programmable Graphics Processing Unit（GPU） provides an alternative method for rapid calculation of the reverse-time migration. In this paper, we focus on the main steps using GPU to calculate the reverse time migration. We summarize the key points in GPU code optimization, and highlight two optimized components: one is the application of random boundary conditions. The data transmission between the host and GPU is reduced. The second is the application of shared memory to store the forward wave field. Compared to the global memory, data reading band widths increase greatly. Finally, we use the Marmousi data to test our code, and the results show that the reverse-time migration program running on GPU has been well optimized to improve the computational efficiency.

Key words: Graphic Processing Unit, reverse time migration, random boundary condition, share memory