Enhancing Velocity Model for Gas Cloud Using First Break Travel Time Tomography Full Waveform Inversion

S. Prajapati, D. Ghosh
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引用次数: 0

Abstract

The velocity model is of a great importance for geological as well as structural properties of complex structure such as gas cloud. Instead of ray-based techniques, eikonal wavefield tomography can provide a higher resolution velocity model for seismic images. We have implemented first break travel time tomography to enhance the initial velocity model for seismic full waveform inversion (FWI) for better imaging rather than guess initial velocity model for FWI. The First-break travel time concept is based on the eikonal equation, relies on inversion to resolve the complex gas cloud imaging. It allows not only the receivers but the shots to change position along the ray path. Tomography results are useful particularly significant in the presence of noise, scattering in the data. We have implemented this approach on marmousi as well as gas cloud model and output are used as input velocity model for FWI and results of proposed approach is more robust than the traditional with faster convergence.
利用初破行时层析成像全波形反演增强气体云速度模型
速度模型对气体云等复杂构造的地质性质和构造性质具有重要意义。与基于射线的技术相比,斜向波场层析成像可以为地震图像提供更高分辨率的速度模型。为了更好地成像,我们采用了首次断层走时层析成像技术来增强地震全波形反演(FWI)的初始速度模型,而不是猜测FWI的初始速度模型。首破行时概念是基于eikonal方程,依靠反演解决复杂气体云成像问题。它不仅允许接收器,而且允许镜头沿着光线路径改变位置。层析成像结果在数据中存在噪声和散射时尤其有用。我们已经在marmousi和气云模型上实现了该方法,并将输出作为FWI的输入速度模型,结果表明该方法比传统方法具有更强的鲁棒性和更快的收敛速度。
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