Seismic waves modeling by convolutional Forsyte polynomial differentiator method

Numerical modeling is important in studying a variety of problems in seismic wave propagation, many methods have been investigated for calculating the spatial terms in the wave equations, the most widely used methods are the classical finite difference (FD) method, the Fourier pseudo - spectral (FPS) method and Finite Element (FE) method. It is clear that each method has its own merits and drawbacks. For improving the precision and efficiency of seismic modeling, this paper develops a new modeling approach (Convolutional Forsyte Polynomial Differentiator Method) by using optimized convolutional operators for spatial differentiation and staggered-grid finite-difference for time differentiation in wave equation computation, a theoretical computation example of 2-D seismic wave field is given and the numerical results show that the algorithm can bring reliable outcomes with high precision and fast speed, and be adapted to complex inhomogeneous geological models and readily be extended to wave modeling for anisotrople media.