Efficient frequency-domain Full Waveform Inversion (FWI) of long-offset/wide-azimuth node data can be designed with a few discrete frequencies. However, 3D frequency-domain seismic modeling remains challenging since it requires solving a large and sparse linear indefinite system per frequency. When such systems are solved with direct methods or hybrid direct/iterative solvers, based upon domain decomposition preconditioner, finite-difference stencils on regular Cartesian grids should be designed to conciliate compactness and accuracy, the former being necessary to mitigate the fill-in induced by the Lower-Upper (LU) factorization. Compactness is classically implemented by combining several second-order accurate stencils covering the eight cells surrounding the collocation point, leading to the so-called 27-point stencil. Accuracy is obtained by applying optimal weights on the different stiffness and consistent mass matrices such that numerical dispersion is jointly minimized for several number of grid points per wavelength ($G$). However, with this approach, the same weights are used at each collocation point, leading to suboptimal accuracy in heterogeneous media. In this study, we propose a straightforward recipe to improve the accuracy of the 27-point stencil. First, we finely tabulate the values of $G$ covering the range of wavelengths spanned by the subsurface model and the frequency. Then, we estimate with a classical dispersion analysis in homogeneous media the corresponding table of optimal weights that minimize dispersion for each $G$ treated separately. We however apply a Tikhonov regularization to guarantee smooth variation of the weights with $G$. Finally, we build the impedance matrix by selecting the optimal weights at each collocation point according to the local wavelength, hence leading to a wavelength-adaptive stencil.
翻译:高效的频率- 全波变换( FWI) 长距离缩压/ 宽度调频节数据( FWI), 可以设计一些离散频率 。 但是, 3D 频域地震模型仍然具有挑战性, 因为它需要解决每个频率的大型和稀散线性线性不定期系统。 当这些系统通过直接的方法或混合的直接/ 直线/ 平坦解决方案来解决时, 以域分解前置器为基础, 常规的卡尔提亚格罗格网网的有限差值应该设计为调和精度和准确度, 前者是减少由低频率( LU) 系数引发的填充量。 但是, 借助这一方法, 降低下调调调调调调频度( LUU) 系数化。 经典调调调频域域模型的精度将几级精确度精确度组合在一起, 将每升G 的精度精确度加固度加固度 。