Multiparameter Full-Waveform Inversion for Velocity and Attenuation Reconstruction Using Nearly-Constant Q Models

被引:0
作者
Huang, Xingguo [1 ]
Sun, Tong [1 ]
Han, Li [1 ]
Deng, Dun [2 ]
Ouyang, Min [3 ]
Greenhalgh, Stewart [4 ]
Luo, Xiaodong [5 ]
机构
[1] Jilin Univ, Coll Instrumentat & Elect Engn, Changchun 130061, Peoples R China
[2] CNOOC China Ltd, Hainan Branch, Haikou 570311, Peoples R China
[3] China Natl Offshore Oil Corp, Beijing 100010, Peoples R China
[4] Inst Geophys, Swiss Fed Inst Technol ETH Zurich, Dept Earth Sci, CH-8092 Zurich, Switzerland
[5] Norwegian Res Ctr NORCE, N-5008 Bergen, Norway
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2025年 / 63卷
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Mathematical models; Attenuation; Crosstalk; Computational modeling; Linear programming; Data models; Optimization; Image reconstruction; Time-frequency analysis; Solid modeling; full-waveform inversion(FWI); nearly constant Q; reconstruction; PROPAGATION; GRADIENT; KERNELS;
D O I
10.1109/TGRS.2024.3510539
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Precise modeling of the attenuation parameter Q is important to confirm the robust and diagnostic attenuation characteristics of seismic waveforms in oil and gas reservoirs. For this purpose, the nearly constant Q viscoacoustic wave equation is beneficial. Compared with attenuation models such as standard linear solid (SLS), the wave equation corresponding to the nearly constant Q model contains an explicit Q, which is conducive to inversion and can provide a more effective parameterization. This parameterization facilitates the initial suppression of parameter crosstalk in multiparameter inversion. We derive the adjoint equation containing auxiliary variables, compare the sensitive kernels of different parameterizations, and explain the superiority of the constructed parameterization. The truncated Gauss-Newton (GN-TRN) method is introduced to suppress parameter crosstalk further. The GN-TRN method updates the model parameters by calculating the Hessian vector product and iteratively solving the approximation of the Newton gradient directions. The test results of the theoretical model and field data verify the effectiveness and stability of the inversion method.
引用
收藏
页数:12
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