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Seismic wavefield simulation with irregular surface topography and Graphic Processing Unit (GPU) implementation

XIAOBO LIU1 ,  JINGYI CHEN1* ,  HAIQIANG LAN2 ,  ZHENCONG ZHAO1
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1 Seismic Anisotropy Group, Department of Geosciences, The University of Tulsa, Tulsa, OK 74104, U.S.A.,
2 Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, P.R. China.,
JSE 2018, 27(5), 445–472;
Submitted: 24 August 2017 | Accepted: 30 July 2018 | Published: 1 October 2018
© 2018 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Liu, X.B., Chen, J.Y., Lan, H.Q. and Zhao, Z.C., 2018. Seismic wavefield simulation with irregular surface topography and Graphic Processing Unit (GPU) implementation. Journal of Seismic Exploration, 27: 445-472. Seismic wavefield simulation in the presence of surface topography provides important information for characterizing seismic wave propagation. Based on the boundary-conforming grid method, we first transform both elastic wave equations in second-order formulation and free surface boundary condition in first order system from Cartesian coordinates to curvilinear coordinates. Then, the convolutional perfectly matched layer (CPML) boundary condition is applied to absorb the outgoing seismic waves at the edges of the truncated model. The test results (e.g, wavefield snapshots and seismograms) show that our numerical algorithms can effectively simulate seismic wave propagation in a model with rough topography, and CPML is more efficient than perfectly matched layer (PML) boundary condition in suppressing artificial reflections. In addition, the finite-difference algorithms on a single Graphic Processing Unit (GPU) are used to accelerate seismic numerical modeling in both elastic isotropic and anisotropic media. Compared with the conventional CPU version, the GPU implementation greatly reduces the computational cost.

Keywords
wavefield simulation
surface topography
finite-difference
convolutional perfectly matched layer
Graphic Processing Unit
GPU
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Journal of Seismic Exploration, Print ISSN: 0963-0651, Published by AccScience Publishing
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