The Slope-Attribute-Regularized High-Resolution Prestack Seismic Inversion - Huang, Guangtan; Chen, Xiaohong; Li, Jingye; Saad, Omar M.; Fomel, Sergey; Luo, Cong; Wang, Hang; Chen, Yangkang (Surveys in geophysics, 2021)
Prestack seismic inversion can be regarded as an optimization problem, which minimizes the error between the observed and synthetic data under the premise of certain geological/geophysical a priori information constraints. It has been proved to be a powerful approach for reconstructing the subsurface properties and building the elastic parameter models (e.g., P- and S-wave velocity, and density). With respect to the specific expressions of a priori information, the starting model and regularization are expected to be the most widely used and indispensable constraints to reconstruct structural features and subsurface properties. The conventional prestack inversion (trace-by-trace) methods perform well when the geological structure of the target area is not too complex. However, due to the lack of lateral constraint, such trace-independent methods are inevitably limited by their capability of characterization (including accuracy, resolution, and robustness) in the case of geologically complex structures, such as tilted stratum and steep faults. The geological structure-guided constraint, herein referred to as the seismic slope attribute, can be exploited as a lateral constraint integrated into the prestack inversion algorithm. In this work, the seismic slope attribute is introduced to the amplitude variation with offset/angle inversion from two aspects, i.e., starting model building and regularization penalty. Firstly, using the seismic slope attribute, instead of the traditional manual interpreted geological horizons, as a constraint, the well-log data are interpolated to build the initial model. The interpolation algorithm is formulated as solving the inverse problem by using the shaping regularization method rather than the kriging-based algorithm. Secondly, by rotating the coordinate system according to the seismic slope attribute, the directional total variation regularization is used as a constraint to improve the resolution (in both vertical and horizontal directions) and lateral continuity of the inversion results. Finally, the proposed methods are applied to synthetic and real seismic data. Synthetic tests and field data applications demonstrate that the proposed method is capable of revealing complex structural features and achieving stabilized inversion of multi-parameters with less uncertainty.