I have developed an efficient 3D forward modeling algorithm based on radiation boundary conditions for controlled-source electromagnetic data. The proposed algorithm derives computational efficiency from a stretch-free discretization, air-free computational domain, and a better initial guess for an iterative solver. A technique for estimation of optimum grid stretching for multifrequency modeling of electromagnetic (EM) data is developed. This technique is similar to the L-curve method used for the estimation of the trade-off parameter in inversion. Using wavenumber-domain analysis, it is illustrated that, as one moves away from the source, the EM field varies smoothly even in the case of a complex model. A two-step modeling algorithm based on radiation boundary conditions is developed by exploiting the smoothness of the EM field. The first step involves a coarse-grid finite-difference modeling and computation of a radiation boundary field vector. In the second step, a relatively fine grid modeling is performed with radiation boundary conditions. The fine-grid discretization does not include the stretched grid and air medium. An initial solution derived from coarse-grid modeling is used for fine-grid modeling. Numerical experiments demonstrate that the developed algorithm is one order faster than the finite-difference modeling algorithm in most of the cases presented.

中文翻译：

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基于辐射边界法的受控源电磁数据3D正演建模

我已经开发了一种基于辐射边界条件的有效3D正向建模算法，用于受控源电磁数据。所提出的算法从无拉伸离散化，无空气计算域以及迭代求解器的更好初始猜测中得出了计算效率。开发了一种用于估计电磁（EM）数据多频模型的最佳网格拉伸的技术。该技术类似于用于反演中折衷参数估计的L曲线方法。使用波数域分析，可以说明，当远离源时，即使在复杂模型的情况下，电磁场也会平稳变化。利用电磁场的平滑性，建立了基于辐射边界条件的两步建模算法。第一步涉及到粗网格有限差分建模和辐射边界场矢量的计算。第二步，在辐射边界条件下执行相对精细的网格建模。细网格离散化不包括拉伸的网格和空气介质。从粗网格建模派生的初始解决方案用于精细网格建模。数值实验表明，在大多数情况下，所开发的算法比有限差分建模算法快一阶。从粗网格建模派生的初始解决方案用于精细网格建模。数值实验表明，在大多数情况下，所开发的算法比有限差分建模算法快一阶。从粗网格建模派生的初始解决方案用于精细网格建模。数值实验表明，在大多数情况下，所开发的算法比有限差分建模算法快一阶。