粘声介质中带有衰减补偿的鲁棒联合自适应多参数波形反演

GEOPHYSICS Pub Date : 2024-01-27 DOI:10.1190/geo2022-0663.1
Chao Li, Guochang Liu, Fang Li, Zhiyong Wang
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引用次数: 0

摘要

全波形反演(FWI)通过迭代减少预测与观测之间的数据残差,已被证明是估算地下参数的有效方法。然而,全波形反演在很大程度上依赖于初始模型,初始模型不佳会导致求解错误。此外,由于地球的无弹性,地震波在传播过程中会衰减,从而导致梯度衰减,使 FWI 在粘声介质中的收敛速度更差。为了缓解这些问题,我们提出了一种改进的多参数(如速度和 Q 值)波形反演方法。受益于 Q 补偿波场传播理论,我们提出了一种 Q 补偿联合多参数波形反演方法,以弱化 FWI 目标函数的非线性,使其能够同时应对衰减引起的梯度能量损失和周期跳变等挑战。我们将所提出的 Q 补偿联合多参数 FWI 方案称为 QJMFWI。QJMFWI 的主要贡献在于(1)考虑到在粘声介质中同时估算速度和 Q 值的困难,QJMFWI 为速度和 Q 值模型的构建提供了一种直接的波形反演方法,通过这种方法我们可以获得更高精度和分辨率的速度和 Q 值信息;(2)与传统的 FWI 方法相比,QJMFWI 放宽了对良好初始速度和 Q 值模型的要求,可以避免陷入局部极小值。数值和现场数据实例表明,QJMFWI 是反演粘声介质中准确地下参数的有效方法。
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Robust joint adaptive multiparameter waveform inversion with attenuation compensation in viscoacoustic media
Full waveform inversion (FWI) has been proven as an effective method to estimate subsurface parameters by iteratively reducing the data residual between the predictions and the observations. Nevertheless, FWI is greatly dependent on the initial model and a poor initial model will lead to a wrong solution. Furthermore, owing to the anelasticity of the earth, seismic waves will attenuate during propagation, which results in an attenuated gradient and makes the convergence rate of FWI even worse in viscoacoustic media. To mitigate these problems, we propose an improved method for multiparameter (e.g. velocity and Q) waveform inversion. Benefiting from the theory of Q-compensated wavefield propagation, we formulate a Q-compensated joint multiparameter waveform inversion method to weaken the nonlinearity of the FWI objective function, which enables it to cope with challenges related with attenuation-induced gradient energy loss and cycle skipping simultaneously. We refer to the proposed Q-compensated joint multiparameter FWI scheme as QJMFWI. The main contributions of QJMFWI are: (1) given the difficulty associated with the estimating of velocity and Q simultaneously in viscoacoustic media, QJMFWI provides a straightforward waveform inversion method for velocity and Q model construction, by which we can obtain velocity and Q information with improved accuracy and resolution; (2) compared with conventional FWI methods, QJMFWI relaxes the requirement for good initial velocity and Q model, which can avoid trapping into local minima. Numerical and field data examples demonstrate that QJMFWI is an effective method to invert for accurate subsurface parameters in viscoacoustic media.
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