Elastic full-waveform inversion (FWI) is a powerful tool for high-resolution subsurface multiparameter characterization. However, 3D FWI applied to land data for near-surface applications is particularly challenging because the seismograms are dominated by highly energetic, dispersive, and complex-scattered surface waves (SWs). In these conditions, a successful deterministic FWI scheme requires an accurate initial model. Our study, primarily focused on field data analysis for 3D applications, aims at enhancing the resolution in the imaging of complex shallow targets, by integrating devoted SW analysis techniques with a 3D spectral-element-based elastic FWI. From dispersion curves, extracted from seismic data recorded over a sharp-interface shallow target, we build different initial S-wave ($V_{\mathrm{S}}$) and P-wave ($V_{\mathrm{P}}$) velocity models (laterally homogeneous and laterally variable), using a specific data transform. Starting from these models, we carry out 3D FWI tests on synthetic and field data, using a relatively straightforward inversion scheme. The field data processing before FWI consists of band-pass filtering and muting of noisy traces. During FWI, a weighting function is applied to the far-offset traces. We test 2D and 3D acquisition layouts, with different positions of the sources and variable offsets. The 3D FWI workflow enriches the overall content of the initial models, allowing a reliable reconstruction of the shallow target, especially when using laterally variable initial models. Moreover, a 3D acquisition layout guarantees a better reconstruction of the target’s shape and lateral extension. In addition, the integration of model-oriented (preliminary monoparametric FWI) and data-oriented (time windowing) strategies into the main optimization scheme has produced further improvement of the FWI results.

中文翻译：

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3D 弹性全波形反演浅层目标重建的挑战——哪个初始模型？

弹性全波形反演 (FWI) 是用于高分辨率地下多参数表征的强大工具。然而，应用于近地表应用的陆地数据的 3D FWI 尤其具有挑战性，因为地震图主要由高能量、色散和复杂散射的表面波 (SW) 主导。在这些条件下，成功的确定性 FWI 方案需要准确的初始模型。我们的研究主要侧重于 3D 应用的现场数据分析，旨在通过将专用 SW 分析技术与基于 3D 光谱元素的弹性 FWI 相结合，提高复杂浅层目标成像的分辨率。从在尖锐界面浅层目标上记录的地震数据中提取的频散曲线，我们构建了不同的初始 S 波（${伏}_{\mathrm{秒}}$) 和 P 波 (${伏}_{\mathrm{磷}}$) 速度模型（横向均匀和横向可变），使用特定的数据变换。从这些模型开始，我们使用相对简单的反演方案对合成和现场数据进行 3D FWI 测试。FWI 之前的现场数据处理包括带通滤波和噪声迹线的静音。在 FWI 期间，权重函数应用于远偏移量轨迹。我们测试 2D 和 3D 采集布局，具有不同的源位置和可变偏移。3D FWI 工作流程丰富了初始模型的整体内容，允许对浅层目标进行可靠的重建，尤其是在使用横向可变初始模型时。此外，3D 采集布局保证了目标形状和横向扩展的更好重建。此外，