Full‐waveform inversion is characterized by cycle‐skipping when the starting background model differs significantly from the true model and low‐frequency data are unavailable. To mitigate this problem, reflection waveform inversion is applied to provide a background velocity model for full‐waveform inversion. This technique attempts to extract background velocity updates along the reflection wavepath by matching the reflection waveforms. However, two issues arise during the implementation of reflection waveform inversion: amplitude and efficiency. The amplitude is always underestimated due to the complex subsurface parameter (i.e. the source signature, density, attenuation etc.). This makes it unreasonable to match the reflection amplitude involved in waveforms, especially in the filed data cases. In addition, generating the background velocity gradient requires the simulation of the reflection wavefield. However, simulating the reflection wavefield is time‐consuming. To address the former, we introduced a locally normalized objective function, while for the latter, we used an efficient strategy by avoiding the explicit generation of the reflection wavefield. Results show that applying the proposed method to both synthetic and field data can provide a good background velocity model for full‐waveform inversion with high efficiency.

中文翻译：

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使用局部归一化零滞后相关目标函数的高效反射波形反演

当起始背景模型与真实模型有显着差异并且低频数据不可用时，全波形反演的特征是跳频。为了缓解此问题，反射波形反演适用于为全波形反演提供背景速度模型。该技术试图通过匹配反射波形来提取沿反射波路径的背景速度更新。但是，在实现反射波形反演时会出现两个问题：幅度和效率。由于复杂的地下参数（即震源特征，密度，衰减等），振幅总是被低估了。这使得匹配波形中的反射幅度变得不合理，尤其是在现场数据情况下。此外，产生背景速度梯度需要模拟反射波场。但是，模拟反射波场非常耗时。为了解决前者，我们引入了局部归一化的目标函数，而对于后者，我们通过避免显式生成反射波场而使用了有效策略。结果表明，将所提方法应用于合成数据和野外数据均可为高效的全波形反演提供良好的背景速度模型。