论文标题

从恒定到可变密度反向扩展模型

From constant to variable density inverse extended Born modelling

论文作者

Farshad, Milad, Chauris, Hervé

论文摘要

对于定量地震成像,迭代最小二乘反向时间迁移是推荐的方法。向前建模运算符的倒数的存在将大大减少所需迭代的数量。在扩展模型的背景下,存在这样的伪内,是作为伴随的加权版本构建的,并解释了反卷积,几何扩展和不均匀的照明。伪内生的建模的应用是基于恒定密度的声学介质,这是实用应用的限制因素。为了考虑密度扰动,我们提出并研究了两种方法。第一个是对最新研究的概括,该研究提议从伪内生构模型操作员的角度依赖反应中恢复声学扰动。新版本基于加权最小二乘目标函数。该方法不仅提供了更强大的结果,而且还提供了在目标函数中包含约束以减少参数串扰的灵活性。我们还提出了一种基于泰勒膨胀的替代方法,该方法不需要任何ra。与其他两种方法相比,使用正确且错误的背景模型基于简单和Marmousi2模型的数值示例,使用正确且错误的背景模型验证加权最小二乘法的有效性。泰勒扩展方法似乎包含太多的工件,无法成功适用。

For quantitative seismic imaging, iterative least-squares reverse time migration is the recommended approach. The existence of an inverse of the forward modelling operator would considerably reduce the number of required iterations. In the context of the extended model, such a pseudo-inverse exists, built as a weighted version of the adjoint and accounts for the deconvolution, geometrical spreading and uneven illumination. The application of the pseudo-inverse Born modelling is based on constant density acoustic media, which is a limiting factor for practical applications. To consider density perturbation, we propose and investigate two approaches. The first one is a generalization of a recent study proposing to recover acoustic perturbations from angle-dependent response of the pseudo-inverse Born modelling operator. The new version is based on weighted least-squares objective function. The method not only provides more robust results, but also offers the flexibility to include constrains in the objective function in order to reduce the parameters cross-talk. We also propose an alternative approach based on Taylor expansion that does not require any Radon transform. Numerical examples based on simple and the Marmousi2 models using correct and incorrect background models for the variable density Born modelling, verify the effectiveness of the weighted least-squares method when compared with the other two approaches. The Taylor expansion approach appears to contain too many artifacts for a successful applicability.

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