Wavefield reconstruction inversion (WRI) mitigates cycle skipping by using an inaccurate initial velocity. This attractive technique is usually implemented with shot records. However, if large numbers of shot records are used, WRI can become computationally burdensome due to the many over-determined linear systems that need to be solved. To alleviate this computational issue, we propose an efficient WRI scheme involving plane-wave encoding (WRI-PW) in the frequency domain. Plane-wave encoding can dramatically reduce the number of relevant datasets by transforming shot records into common ray-parameter gathers with time shifting. Therefore, plane-wave encoding is widely used in many aspects of seismic data processing (e.g. waveform inversion, reverse time migration, etc.). Initially, we performed a simple numerical experiment using a velocity model with a box-shaped anomaly. WRI-PW also could generate scattering wavefields in a homogeneous model. Next, computational efficiency was checked with a modified Marmousi-2 model. The results show that the usage of a sufficient plane-wave angle can achieve satisfactory inversion results. It indicates that WRI-PW requires small datasets compared to WRI. Thus, the computational costs for solving the augmented system can be reduced. Further experiments were conducted to evaluate the robustness of WRI-PW to random noise and to compare WRI-PW and conventional full waveform inversion (FWI) with a modified SEG/EAGE salt velocity model. We verify that WRI-PW is more robust to random noise than WRI, it exhibited less dependency on the accuracy of the initial velocity model than conventional FWI and it is computationally efficient.

中文翻译：

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平面波编码策略的地震波场重构反演

波场重建反演（WRI）通过使用不正确的初始速度来减轻周期跳跃。这种吸引人的技术通常通过拍摄记录来实现。但是，如果使用大量镜头记录，由于需要解决许多超定线性系统，因此WRI可能在计算上变得繁重。为了缓解此计算问题，我们提出了一种有效的WRI方案，该方案在频域中涉及平面波编码（WRI-PW）。平面波编码可以通过将镜头记录转换为具有时移的通用射线参数集合，从而大大减少相关数据集的数量。因此，平面波编码被广泛用于地震数据处理的许多方面（例如，波形反演，逆时偏移等）。原来，我们使用具有箱形异常的速度模型进行了简单的数值实验。WRI-PW还可以在均匀模型中生成散射波场。接下来，使用改进的Marmousi-2模型检查了计算效率。结果表明，使用足够的平面波角可以获得令人满意的反演结果。这表明与WRI相比，WRI-PW需要较小的数据集。因此，可以减少用于求解扩充系统的计算成本。进行了进一步的实验，以评估WRI-PW对随机噪声的鲁棒性，并将WRI-PW与常规全波形反演（FWI）与改进的SEG / EAGE盐速度模型进行比较。我们验证了WRI-PW对随机噪声的抵抗力比WRI更强，