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Image-domain full waveform inversion: Field data example

机译:图像域全波形反演:现场数据示例

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摘要

The main difficulty with the data-domain full waveform inversion (FWI) is that it tends to get stuck in the local minima associated with the waveform misfit function. This is the result of cycle skipping which degrades the low-wavenumber update in the absence of low-frequencies and long-offset data. An image-domain objective function is defined as the normed difference between the predicted and observed common image gathers (CIGs) in the subsurface offset domain. This new objective function is not constrained by cycle skipping at the far subsurface offsets. To test the effectiveness of this method, we apply it to marine data recorded in the Gulf of Mexico. Results show that image-domain FWI is less sensitive to the initial model and the absence of low-frequency data compared with conventional FWI. The liability, however, is that it is almost an order of magnitude more expensive than standard FWI.
机译:数据域全波形反演(FWI)的主要困难在于,它容易陷入与波形失配函数相关的局部最小值中。这是循环跳过的结果,在没有低频和长偏移数据的情况下,跳变会降低低波数更新的速度。图像域目标函数定义为地下偏移域中预测和观察到的公共图像集(CIG)之间的标准差。这个新的目标函数不受远地下偏移处的循环跳跃的约束。为了测试此方法的有效性,我们将其应用于记录在墨西哥湾的海洋数据。结果表明,与传统FWI相比,图像域FWI对初始模型较不敏感,并且缺少低频数据。但是,责任在于它比标准FWI贵了近一个数量级。

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