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Published as Computers & Geosciences, 68, 64-72, (2014)

RTM using effective boundary saving: A staggered grid GPU implementation

Pengliang Yang% latex2html id marker 2440
\setcounter{footnote}{1}\fnsymbol{footnote}, Jinghuai Gao% latex2html id marker 2441
\setcounter{footnote}{1}\fnsymbol{footnote}, and Baoli Wang% latex2html id marker 2442
\setcounter{footnote}{2}\fnsymbol{footnote}
% latex2html id marker 2443
\setcounter{footnote}{1}\fnsymbol{footnote}Xi'an Jiaotong University, National Engineering Laboratory for Offshore Oil Exploration, Xi'an, China, 710049
% latex2html id marker 2444
\setcounter{footnote}{2}\fnsymbol{footnote}CCTEG Xi'an Research Institute, Xi'an, China, 710077


Abstract:

GPU has become a booming technology in reverse time migration (RTM) to perform the intensive computation. Compared with saving forward modeled wavefield on the disk, RTM via wavefield reconstruction using saved boundaries on device is a more efficient method because computation is much faster than CPU-GPU data transfer. In this paper, we introduce the effective boundary saving strategy in backward reconstruction for RTM. The minimum storage requirement for regular and staggered grid finite difference is determined for perfect reconstruction of the source wavefield. Particularly, we implement RTM using GPU programming, combining staggered finite difference scheme with convolutional perfectly matched layer (CPML) boundary condition. We demonstrate the validity of the proposed approach and CUDA codes with numerical example and imaging of benchmark models.




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2015-03-27