Velocity-estimation improvements and migration/demigration using CRS with continuing deconvolution in the time domain

Journal article

To obtain an image of the earth's subsurface, time-imaging methods can be applied, as they are reasonably fast, less sensitive to velocity model errors than depth-imaging methods and, usually, easy to parallelize. A powerful tool for time-imaging consists of a series of prestack time-migrations and demigrations. We apply multi-parameter stacking techniques to obtain an initial time-migration velocity model. The velocity model building proposed here, is based on the kinematic wavefield attributes. A following refinement of the velocities uses a coherence filter which is based on a predetermined threshold, and followed by an interpolation and smoothing. Then, we perform a migration deconvolution to obtain the final time-migrated image. The migration deconvolution consists of one iteration of least-squares migration with an estimated Hessian. We estimate the Hessian by non-stationary matching filters, i.e., in a data-driven fashion. The model building uses the framework of the common-reflection-surface , and the migrated deconvolution is fully automated. Therefore, minimal user interaction is required to carry out both the velocity model refinement and the image update. We apply the suggested approaches of velocity refinement and migration deconvolution to complex synthetic and field data.

Authors: Glöckner, M; Dell, S; Schwarz, B; Vanelle, C; Gajewski, D

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Society of Exploration Geophysicists
• Journal: Geophysics
• Volume: 84
• Issue: 4
• Pages: A37-WA81
• Publication date: 2019-03-15
• Acceptance date: 2019-02-20
• DOI: 10.1190/geo2018-0173.1
• EISSN: 1942-2156
• ISSN: 0016-8033
• Language: English
• Keywords: time migration; deconvolution