Least-squares reverse time migration (RTM) has become the method of choice for quantitative seismic imaging. The main drawback of such a scheme is that it requires many migration/modeling cycles. The convergence of least-squares RTM can be accelerated by using a suitable preconditioner. In the context of an extended domain in variable-density acoustic media, the pseudoinverse Born operator is the recommended preconditioner, providing quantitative results within a single iteration. This method consists of two steps: application of the pseudoinverse Born operator and inversion of two parameters using an efficient weighted least-squares approach based on the Radon transform. As expected, crosstalk artifacts are generated in the second step due to limited acquisition. We have developed a variable-density pseudoinverse Born operator constrained with the ${\ell }_1$-norm for each model parameter to suppress the artifacts. The fast iterative shrinkage-thresholding algorithm is used to carry out the optimization problem. In classic iterative least-squares migration, the ${\ell }_1$-norm constraints would affect the whole imaging process. Because the imaging method is split into two steps, only the Radon transform part is modified, where no wave-based operators are involved. Through numerical experiments, we verify the robustness of our method against different migration artifacts including the parameter crosstalk, interfaces with abrupt truncations, sparse shot acquisition geometry, noisy data, and high-contrast complex structures.

中文翻译：

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声介质中稀疏度促进的多参数拟逆Born反演

最小二乘逆时偏移（RTM）已成为定量地震成像的首选方法。这种方案的主要缺点是它需要许多迁移/建模周期。最小二乘RTM的收敛可以通过使用合适的预处理器来加速。在可变密度声学介质的扩展域中，建议使用伪逆Born算子进行预处理，在一次迭代中提供定量结果。该方法包括两个步骤：伪逆Born运算符的应用和使用基于Radon变换的高效加权最小二乘法对两个参数进行求逆。如所预期的，由于有限的采集，在第二步骤中产生了串扰伪像。${\ell }_{\mathrm{1个}}$-norm为每个模型参数抑制伪影。快速迭代收缩阈值算法用于执行优化问题。在经典的迭代最小二乘迁移中，${\ell }_{\mathrm{1个}}$-规范约束会影响整个成像过程。由于成像方法分为两个步骤，因此仅修改了Radon变换部分，其中不涉及基于波的算子。通过数值实验，我们验证了我们的方法针对不同迁移工件的鲁棒性，这些工件包括参数串扰，突然截断的接口，稀疏的镜头采集几何形状，嘈杂的数据以及高对比度的复杂结构。