In this work we extend the shifted Laplacian approach to the elastic Helmholtz equation. The shifted Laplacian multigrid method is a common preconditioning approach for the discretized acoustic Helmholtz equation. In some cases, like geophysical seismic imaging, one needs to consider the elastic Helmholtz equation, which is harder to solve: it is three times larger and contains a nullity-rich grad-div term. These properties make the solution of the equation more difficult for multigrid solvers. The key idea in this work is combining the shifted Laplacian with approaches for linear elasticity. We provide local Fourier analysis and numerical evidence that the convergence rate of our method is independent of the Poisson's ratio. Moreover, to better handle the problem size, we complement our multigrid method with the domain decomposition approach, which works in synergy with the local nature of the shifted Laplacian, so we enjoy the advantages of both methods without sacrificing performance. We demonstrate the efficiency of our solver on 2D and 3D problems in heterogeneous media.
翻译:在这项研究中,我们扩展了移动拉普拉斯方法,以应用于弹性亥姆霍兹方程。移动拉普拉斯多重网格法是离散声学亥姆霍兹方程的常用预处理方法。在某些情况下,如地球物理震荡成像中,需要考虑弹性亥姆霍兹方程,该方程更难求解: 它的尺寸是离散化声学亥姆霍兹方程的三倍,并且包含具有核心丰富性的grad-div项。这些特性使得多重网格求解器更难以解决该方程。本文的关键思想是结合位移拉普拉斯和线性弹性方法。我们提供了局部傅里叶分析和数值证据,表明我们方法的收敛速率与泊松比无关。此外,为了更好地处理问题的规模,我们将多重网格方法与域分解方法相结合,两种方法之间相互协作,从而在不牺牲性能的前提下获得了两种方法的优点。我们在异质介质中的2D和3D问题上展示了我们求解器的效率。