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    基于有限差分-低秩分解策略的黏声各向异性纯qP波正演模拟方法

    Pure qP-wave forward modelling for viscoacoustic anisotropic media based on finite-difference low-rank decomposition strategy

    • 摘要: 地下介质的黏弹性和各向异性特征会导致地震波出现相位频散和振幅衰减, 如果在地震数据处理中忽略这些影响, 那么成像结果会出现同相轴畸变和偏移假象。常规黏声TTI介质拟声波方程可用于模拟地震波在黏声各向异性介质中的传播特征, 但存在伪横波干扰和受模型参数限制(各向异性参数ε必须大于δ)等问题。为了解决上述问题, 将基于声学近似的纯qP波频散关系与常Q衰减模型相结合, 推导了一种黏声TTI介质纯qP波方程。该方程包含解耦的相位频散和振幅衰减项, 便于实现衰减补偿逆时偏移。基于新推导的方程, 发展了有限差分-低秩分解求解策略, 实现了黏声TTI介质纯qP波正演模拟。数值模拟结果表明, 该方程克服了黏声TTI介质拟声波方程的局限, 可较为准确且稳定地模拟地震波在黏声各向异性介质中的传播过程。同时, 该有限差分-低秩分解求解策略继承了有限差分求解方法高效的优势, 相比于传统低秩分解法具有更高的计算效率。

       

      Abstract: Viscoelastic and anisotropic characteristics of subsurface media cause phase dispersion and amplitude dissipation of seismic waves.If these undesired effects are ignored during seismic processing, distorted events and migration artifacts may appear in imaging results.The traditional pseudo-acoustic qP-wave equation for viscoacoustic TTI media can be used to simulate seismic-wave propagation in viscoacoustic anisotropic media.However, this equation produces shear wave artifacts, and its application is limited by model parameters (ε>δ).To address this issue, a pure qP-wave equation for viscoacoustic TTI media is derived by combining the pure qP-wave dispersion relation based on acoustic approximation with the constant-Q attenuation model.The newly derived wave equation contains decoupled phase dispersion and amplitude loss terms, and it is conducive to the implementation of attenuation-compensated reverse time migration.Based on the newly derived wave equation, the finite-difference low-rank decomposition strategy is proposed to realize pure qP-wave forward modeling for viscoacoustic TTI media.The numerical simulation results show that the newly derived wave equation overcomes the limitation of pseudo-acoustic qP-wave equation for viscoacoustic TTI media and can simulate seismic-wave propagation in viscoacoustic anisotropic media accurately and stably.In addition, the finite-difference low-rank decomposition strategy developed in this paper inherits the high efficiency of finite-difference solutions and has higher computational efficiency than traditional low-rank decomposition methods.

       

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