ZHENG Wan-Qiu,
MENG Xiao-Hong,
LIU Jian-Hong et al
.2016.High precision elastic wave equation forward modeling based on cosine modulated Chebyshev window function.Chinese Journal Of Geophysics,59(7): 2650-2662,doi: 10.6038/cjg20160728
High precision elastic wave equation forward modeling based on cosine modulated Chebyshev window function
ZHENG Wan-Qiu1, MENG Xiao-Hong1, LIU Jian-Hong2, WANG Jian1
1. School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China; 2. BGP Research and Development Center, CNPC, Hebei Zhuozhou 072751, China
Abstract:The finite difference forward modeling is the basis of elastic wave reverse-time migration and full waveform inversion in the time domain. The accuracy of forward modeling also controls the accuracy of seismic imaging and inversion. The migration or inversion will bring illusion if the accuracy is not high. We can get optimized explicit finite difference operators by using the window function to truncate spatial convolution counterpart of the pseudo-spectral method. Based on this, a cosine modulated Chebyshev window is designed. On the basis of the original Chebyshev window, the modulation times and modulation domain are introduced, and we can adjust truncation error visually by controlling these two parameters. As the new window function inherits the character of Chebyshev window, we observe that the spectral range using the modulated window function for truncation is significantly broader than using the conventional window function with stable error. For different forward modeling orders N, we give a set of empirical modulation factors and compare the forward modeling effect of the new method and improved binomial window by the numerical simulation method. The results demonstrate that the operators based on the cosine modulated Chebyshev window can efficiently suppress the numerical dispersion and get more accurate forward modeling results on the large grid. From economic perspective, this method reduces the computational cost and improves efficiency.
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