We apply the forward modeling algorithm constituted by the convolutional Forsyte polynomial differentiator pro-posed by former worker to seismic wave simulation of complex heterogeneous media and compare the efficienc...We apply the forward modeling algorithm constituted by the convolutional Forsyte polynomial differentiator pro-posed by former worker to seismic wave simulation of complex heterogeneous media and compare the efficiency and accuracy between this method and other seismic simulation methods such as finite difference and pseudospec-tral method. Numerical experiments demonstrate that the algorithm constituted by convolutional Forsyte polyno-mial differentiator has high efficiency and accuracy and needs less computational resources, so it is a numerical modeling method with much potential.展开更多
基金Open Fund of State Key Laboratory of Geological Processes and Mineral Resources, China University of Geo-sciences (GPMR0750)National Natural Science Foundation of China (40437018)
文摘We apply the forward modeling algorithm constituted by the convolutional Forsyte polynomial differentiator pro-posed by former worker to seismic wave simulation of complex heterogeneous media and compare the efficiency and accuracy between this method and other seismic simulation methods such as finite difference and pseudospec-tral method. Numerical experiments demonstrate that the algorithm constituted by convolutional Forsyte polyno-mial differentiator has high efficiency and accuracy and needs less computational resources, so it is a numerical modeling method with much potential.
