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《Progress in Geophysics》 2008-04
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2.5D modelling of elastic waves using the convolutional differentiator method

CHENG Bing-jie1,LI Xiao-fan2(1.Mobile Postdoctoral Center,Southwest Branch Co.,SINOPEC,Chengdu 610081,China;2.Institute of Geology and Geophysics,Chinese Academy of Science,Beijing 100029,China)  
Early convolutional differentiators were all based on the Fourier transformation,their precision was a little higer than that of the four-order finite difference.For improving the precision and efficiency of seismic modeling,the authors develop 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.The solution of this new method is much close to the exact value,and the precision is nearly equal to that of 16-order finite difference,and higher than that of the pseudospectral method.2.5D modelling is more efficient than 3D modelling,and more effective to model the 3D seismic field than 2D modelling.This paper applies the convolutional Forsyte polynomial differentiator method to model 2.5D seismic waves field.The numerical results show that the algorithm can bring reliable outcomes with high precision and fast speed,and 2.5D modelling is much efficient and economical,and deserves more attentation,research and extensive application.
【Fund】: 国家自然科学基金委员会重点项目(40437018);; 中石化股份公司科研项目"3D多波多分量属性提取及综合应用技术研究"(P06028-T02)联合资助
【CateGory Index】: P631.4
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