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arXiv 2206.07367math.OC
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关于WRI与FWI的联系--黑塞矩阵中非线性项的分析

On the connection between WRI and FWI: Analysis of the nonlinear term in the Hessian matrix

Ali Gholami, Hossein S. Aghamiry, Stephane Operto

摘要:

标准全波形反演(FWI)的实现带来了困难,因为初始模型偏离真实模型。波场重建反演(WRI)通过放松波动方程约束来缓解这些困难。本文针对FWI中黑塞矩阵中的非线性项,提出了一种新的近似Hessian,即包含二阶导数信息的增广高斯-牛顿(AGN)Hessian。此外,我们建立了一个更新公式之间的密切联系,该公式是由牛顿法与AGN Hessian近似解决FWI问题和WRI方法。我们的分析开辟了新的视角,开发有效的算法FWI的基础上牛顿法,并突出了黑塞矩阵,这是在大多数情况下被忽略的非线性项的重要性。

英文摘要:

Implementation of the standard full waveform inversion (FWI) poses difficulties as the initial model offsets from the true model. The wavefield reconstruction inversion (WRI) was proposed to mitigate these difficulties by relaxing the wave-equation constraint. In this abstract, working on the nonlinear term in the Hessian matrix of FWI, we develop a new approximate Hessian as an Augmented Gauss-Newton (AGN) Hessian including second-order derivative information. Moreover, we establish an intimate connection between an updating formula which results from approximate solve of the Newton's method with the AGN Hessian on the FWI problem and the WRI method. Our analysis opens new perspectives for developing efficient algorithms for FWI based on the Newton's method and highlights the importance of the nonlinear term in the Hessian matrix, which is ignored in most cases.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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