Processing algorithms for transversely isotropic (TI) media are widely used in depth imaging and typically bring substantial improvements in reflector focusing and positioning. Here, we develop acoustic image-domain tomography (IDT) for reconstructing VTI (TI with a vertical symmetry axis) models from P-wave reflection data. The modeling operator yields an integral wave-equation solution, which is based on a separable dispersion relation and contains only P-waves. The zero-dip NMO velocity (Vnmo) and anellipticity parameter η are updated by focusing energy in space-lag images obtained by least-squares reverse-time migration (LSRTM). Application of LSRTM helps mitigate aperture- and illumination-induced artifacts in space-lag gathers and improve the robustness of η-estimation. The impact of the trade-off between Vnmo and η is reduced by a three-stage inversion algorithm that gradually relaxes the constraints on the spatial variation of η. Assuming that the depth profile of the Thomsen parameter d is known at two or more borehole locations, we employ image-guided interpolation to constrain the depth scale of the parameter fields and the migrated image. Image-guided smoothing is also applied to the IDT gradients to facilitate convergence towards geologically plausible models. The algorithm is tested on synthetic reflection and borehole data from the structurally complicated elastic VTI Marmousi-II model. Although the initial velocity field is purely isotropic and substantially distorted, all three relevant parameters (Vnmo, η, and δ) are estimated with sufficient accuracy. The algorithm is also applied to a line from a 3D ocean-bottom-node data set acquired in the Gulf of Mexico.
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported by the Consortium Project on Seismic Inverse Methods for Complex Structures at CWP and competitive research funding from King Abdullah University of Science and Technology (KAUST). We are grateful to Shell Exploration and Production Company for sharing the 3D Gulf of Mexico data set with Colorado School of Mines, and their permission to publish the results using this data set. We also thank Daniel Rocha (CWP) for his help in preprocessing the data. The numeric examples in this paper are generated with the Madagascar open-source software package (Fomel et al., 2013a) freely available from http://www.ahay.org