Least-squares reverse time migration has proven to be the state-of-the-art for linear imaging technique of complex subsurface structures. Assuming a variable-density acoustic medium, least-squares iterations have the potential to compensate for the artifacts caused by finite frequency of the seismic source, limited acquisition aperture, uneven illumination and parameter cross-talk. The main drawback of such an iterative imaging scheme is the substantial computational expense induced by additional modeling/adjoint steps at each iteration. To accelerate the convergence rate, we propose to leverage the variable-density pseudoinverse extended Born operator as a preconditioner. Our imaging scheme consists of two main steps. We first construct a true-amplitude extended image through Conjugate Gradient iterations with/without preconditioning. Then, by applying a 2D Radon transform, we simultaneously estimate the physical parameters from the angle-domain response using a weighted least-squares method. The second step does not involve wave propagation terms. Through numerical experiments, we show that the proposed preconditioning scheme not only largely reduces the required number of iterations to achieve a given data misfit but also significantly increases the quality of the inverted images even in presence of strong parameter cross-talk and inaccurate migration background models. This is further confirmed by analyzing the shape of the multi-parameter Hessian obtained on a model with limited size.

最小二乘逆时偏移已被证明是复杂地下结构线性成像技术的最新技术。假设是可变密度声学介质，最小二乘迭代有可能补偿由有限频率的震源、有限的采集孔径、不均匀的照明和参数串扰引起的伪影。这种迭代成像方案的主要缺点是每次迭代时额外的建模/伴随步骤引起的大量计算开销。为了加快收敛速度​​，我们建议利用可变密度伪逆扩展 Born 算子作为预处理器。我们的成像方案包括两个主要步骤。我们首先通过带/不带预处理的共轭梯度迭代构建真实幅度扩展图像。然后，通过应用 2D Radon 变换，我们同时使用加权最小二乘法从角域响应中估计物理参数。第二步不涉及波传播项。通过数值实验，我们表明所提出的预处理方案不仅大大减少了实现给定数据失配所需的迭代次数，而且即使在存在强参数串扰和不准确的迁移背景模型的情况下也显着提高了倒置图像的质量. 通过分析在有限大小的模型上获得的多参数 Hessian 的形状，进一步证实了这一点。第二步不涉及波传播项。通过数值实验，我们表明所提出的预处理方案不仅大大减少了实现给定数据失配所需的迭代次数，而且即使在存在强参数串扰和不准确的迁移背景模型的情况下也显着提高了倒置图像的质量. 通过分析在有限大小的模型上获得的多参数 Hessian 的形状，进一步证实了这一点。第二步不涉及波传播项。通过数值实验，我们表明所提出的预处理方案不仅大大减少了实现给定数据失配所需的迭代次数，而且即使在存在强参数串扰和不准确的迁移背景模型的情况下也显着提高了倒置图像的质量. 通过分析在有限大小的模型上获得的多参数 Hessian 的形状，进一步证实了这一点。