Full waveform inversion for land seismic data requires the development of specific strategies for modelling the complex response associated to the near surface. Seismic wave propagation is distorted by several effects, such as topographic relief, wavefield scattering, attenuation (often frequency-dependent) and anisotropy. The modelling of such shallow complexities is often unmanageable by parametric inversions such that data preconditioning and surface-related corrections are required before tackling the full waveform inversion velocity modelling problem. We developed a unified framework addressing both surface-consistent corrections and full waveform inversion by using the transmitted portion of the wavefield. The problem of surface-consistent decomposition is recast in terms of the transmitted wavefield leading to kinematic and dynamic corrections to account for sub-resolution wave propagation distortions occurring in the near surface weathering layer. Seismic data are deconvolved from the effects of the near surface to better represent the deeper subsurface wavefield propagation. Signal-to-noise enhancement is obtained after the surface-consistent transmission preconditioning by the generation of virtual super gathers reconstructed in the midpoint-offset sorting domain. An original scheme of 1.5D Laplace–Fourier full waveform inversion, involving 3D radiation and 1D velocity inversion, is then applied for the velocity reconstruction where the amplitude information of the seismic data is fully preserved and utilized. The unified approach of surface-consistent transmission preconditioning and velocity modelling is demonstrated on the Society of Exploration Geophysicists Advanced Modelling arid model dataset as well as on two complex field datasets containing near surface complexities typical of arid regions. The approach provides the solution of the near surface distortions by performing data preconditioning and velocity inversions in a unified scheme. The surface-consistent full waveform inversion approach has been utilized for large land seismic projects and represents a robust tool for supporting land seismic imaging.

中文翻译：

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超分辨率地表一致全波形反演

陆地地震数据的全波形反演需要开发特定策略来对与近地表相关的复杂响应进行建模。地震波传播会受到多种影响的影响，例如地形起伏、波场散射、衰减（通常与频率相关）和各向异性。这种浅层复杂性的建模通常无法通过参数反演来管理，因此在解决全波形反演速度建模问题之前需要进行数据预处理和与表面相关的校正。我们开发了一个统一的框架，通过使用波场的透射部分来解决表面一致校正和全波形反演。表面一致分解问题根据传输波场进行了重新设计，导致运动学和动态校正，以解决近地表风化层中发生的亚分辨率波传播畸变。地震数据从近地表的影响中去卷积，以更好地表示更深的地下波场传播。通过在中点偏移分选域中重建的虚拟超级道集的生成，在表面一致传输预处理后获得信噪比增强。然后将原始的1.5D拉普拉斯-傅里叶全波形反演方案（涉及3D辐射和1D速度反演）应用于速度重建，其中地震数据的振幅信息被充分保留和利用。地表一致传输预处理和速度建模的统一方法在勘探地球物理学家协会高级建模干旱模型数据集以及包含干旱地区典型的近地表复杂性的两个复杂现场数据集上得到了演示。该方法通过在统一方案中执行数据预处理和速度反演来提供近地表畸变的解决方案。地表一致全波形反演方法已用于大型陆地地震项目，是支持陆地地震成像的强大工具。