Seismic wave field numerical modeling using high-order staggerd grid finite-difference method

Author(s):  
Z. Yang ◽  
R.Y. Li ◽  
J.G. Yue ◽  
Y.S. Xiao
2014 ◽  
Vol 1055 ◽  
pp. 254-258
Author(s):  
Jie Zhang ◽  
Fan Shun Meng ◽  
Yang Sen Li

In the process of seismic wave field numerical simulation using finite difference method, the simulation accuracy and computational efficiency is one of the keys to the problem which is especially important to the numerical simulation of small scale geological body which velocity changes violently. In order to describe the local structure of medium subtly and guarantee the efficiency of the simulation, this article introduces the variable grid finite difference method to the staggered grid high-order finite difference numerical simulation on the basic of the traditional staggered grid finite difference algorithm to improve the staggered grid spatial algorithm and avoid the reduction of the simulation accuracy and computational efficiency caused by the interpolation factor. The results show that the variable staggered grid numerical simulation of finite difference algorithm can accurately depict the space variation of underground medium physical properties to further enhance the adaptability of numerical simulation of complex medium, it also can provide reliable basis for wave field imaging and the combined interpretation of p-wave and s-wave.


Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4573
Author(s):  
Anna Franczyk ◽  
Damian Gwiżdż ◽  
Andrzej Leśniak

This paper aims to provide a quantitative understanding of the performance of numerical modeling of a wave field equation using general-purpose processors. In particular, this article presents the most important aspects related to the memory workloads and execution time of the numerical modeling of both acoustic and fully elastic waves in isotropic and anisotropic mediums. The results presented in this article were calculated for the staggered grid finite difference method. Our results show that the more realistic the seismic wave simulations that are performed, the more the demand for memory and the computational capacity of the computing environment increases. The results presented in this article allow the estimation of the memory requirements and computational time of wavefield modeling for the considered model (acoustic, elastic or anisotropic) so that their feasibility can be assessed in a given computing environment and within an acceptable time. Understanding the numerical modeling performance is especially important when graphical processing units (GPU) are utilized to satisfy the intensive calculations of three-dimensional seismic forward modeling.


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