GPGPU-Aided 3D Staggered-grid Finite-difference Seismic Wave Modeling

Finite difference is a simple, fast and effective numerical method for seismic wave modeling, and has been widely used in forward waveform inversion and reverse time migration. However, intensive calculation of three-dimensional seismic forward modeling has been restricting the industrial application of 3D pre-stack reverse time migration and inversion. Aiming at this problem, in this paper, a parallelized 3D Staggered-grid Finite-difference has been developed using General-purpose computing on the graphics processing unit (GPGPU), namely G-3DFD, since the emergence of graphic processing units (GPU) as an effective alternative to traditional general purpose processors has become increasingly capable in accelerating large-scale scientific computing. We analyze three-dimensional staggered grid finite difference method for the implementation on GPU, making possible the industrial application of 3D pre-stack reverse time migration and inversion. Experiments show that G-3DFD has dramatically improved the runtime performance 88 times on modern GPGPU platforms comparing to the original CPU implementation methods.