同时反演速度和反射率:FWI + LSRTM

Y. Yang, J. Ramos-Martínez, D. Whitmore, G. Huang, N. Chemingui
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引用次数: 3

摘要

我们提出了一种同时估计速度和反射率的迭代非线性反演方法。反演工作流程的核心是用速度和矢量反射率参数化的全声波场建模关系。一个关键的方面是基于逆散射理论分离梯度的低波数和高波数分量,使灵敏度核分别更新速度和矢量反射率。估计问题是一个多参数伴随状态反演,其中速度和反射率之间的权衡通过尺度分离最小化。我们的方法相当于使用全波场在单个框架中执行全波形反演(FWI)和最小二乘逆时偏移(LSRTM)。反演的输出是一个详细的速度模型,以及对地球反射率的精确估计,并补偿了采集不完全、光照差和多重串扰。新方法通过将速度模型构建(FWI)和成像(LSRTM)结合到一个反演过程中,以最少的数据预处理,减少了成像项目的周转时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simultaneous velocity and reflectivity inversion: FWI + LSRTM
Summary We present an iterative non-linear inversion method to simultaneously estimate both velocity and reflectivity. The core of the inversion workflow is a full acoustic wavefield modeling relation parameterized in terms of velocity and vector reflectivity. A key aspect is the separation of the low- and high-wavenumber components of the gradient based on inverse scattering theory, enabling the sensitivity kernels to update the velocity and the vector reflectivity, respectively. The estimation problem is formulated as a multi-parameter adjoint-state inversion where the trade-off between velocity and reflectivity is minimized through scale separation. Our approach is equivalent to performing Full Waveform Inversion (FWI) and Least-Squares Reverse Time Migration (LSRTM) in a single framework using the full wavefield. The output of the inversion is a detailed velocity model together with an accurate estimate of the earth reflectivity with compensation for incomplete acquisition, poor illumination, and multiple crosstalk. The new approach reduces the turnaround time of imaging projects by combining velocity model building (FWI) and imaging (LSRTM) into a single inversion process with minimal data pre-processing.
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