In the early stage of acoustic full-waveform inversion (AFWI), it is important to exploit the long-wavelength features of the gradient and suppress its short-wavelength features to update the background velocity. However, due to strong near-offset PP reflections and multiples within the pressure data, conventional AFWI sometimes primarily reconstructs the short-wavelength features of a given model and fails to converge on a reliable subsurface P-wave velocity model. Therefore, this study, we propose the usage of pseudo-horizontal particle acceleration (pseudo-a_x) data for AFWI, rather than the original pressure data. Because the amplitudes of PP reflections are implicitly weighted according to the reflection angle in pseudo-a_x data, the near-offset PP reflections and multiples of the pseudo-a_x data are much weaker than those of the pressure data. As a result, AFWI using pseudo-a_x data focuses on reconstructing the longer-wavelength features of a given model in the early iterations, and then gradually reconstructs short-wavelength features as the inversion process continues. Using synthetic and real data examples for the Volve oilfield in the North Sea, we examined the effects and feasibility of this strategy. In the synthetic data example, the proposed strategy rapidly reduced far-offset data misfits related to long-wavelength feature updates and achieved smaller model misfits than the conventional strategy. The real data example showed that the velocity model reconstructed using the proposed strategy flattened some of the reflectors at the angle-domain common-image gathers (ADCIGs) better than the velocity model obtained using the conventional strategy. These findings demonstrate that our strategy converges closer to the real P-wave velocity model than the conventional strategy by building a hierarchical velocity model from long- to short-wavelength structures.

在声学全波形反演（AFWI）的早期，重要的是利用梯度的长波长特征并抑制其短波长特征来更新背景速度。然而，由于压力数据中的强近偏移 PP 反射和多次波，传统的 AFWI 有时主要重建给定模型的短波长特征，而无法收敛到可靠的地下 P 波速度模型上。_{因此，在这项研究中，我们建议在AFWI}中使用伪水平粒子加速度 (pseudo- ax ) 数据，而不是原始压力数据。_{因为 PP 反射的幅度是根据伪 a x}中的反射角隐式加权的数据，准a _x数据的近偏移PP反射和倍数比压力数据弱得多。因此，AFWI 使用伪 a _x数据侧重于在早期迭代中重建给定模型的较长波长特征，然后随着反演过程的继续逐渐重建短波长特征。我们使用北海 Volve 油田的合成和真实数据示例，检验了该策略的效果和可行性。在合成数据示例中，所提出的策略迅速减少了与长波长特征更新相关的远偏移数据失配，并实现了比传统策略更小的模型失配。实际数据示例表明，使用所提出的策略重建的速度模型比使用常规策略获得的速度模型更好地使角域共像道集 (ADCIG) 处的一些反射器变平。