The most popular hardware used for parallel depth migration is the PC-Cluster but its application is limited due to large space occupation and high power consumption. In this paper, we introduce a new hardware architecture, based on which the finite difference （FD） wavefield-continuation depth migration can be conducted using the Graphics Processing Unit （GPU） as a CPU coprocessor. We demonstrate the program module and three key optimization steps for implementing FD depth migration： memory, thread structure, and instruction optimizations and consider evaluation methods for the amount of optimization. 2D and 3D models are used to test depth migration on the GPU. The tested results show that the depth migration computational efficiency greatly increased using the general-purpose GPU, increasing by at least 25 times compared to the AMD 2.5 GHz CPU.
