Least squares migration has been an important research topic in the academia for about two decades, but only recently it has attracted interest from the industry. The main reason is that from a practical point of view its ratio of benefit/cost has not been sufficient for its use in seismic exploration. Another problem is that these benefits are mixed with effects from the filtering techniques used to regularize the inversion, which are computationally much cheaper. In this paper, I discuss some challenges with least squares Kirchhoff depth migration. This algorithm, although less precise than the more popular least squares reverse time migration, has the advantage of being fast enough to be applied in a production environment, and flexible enough to be applied without data regularization. This last characteristic makes it a good candidate to understand benefits in terms of footprint acquisition and aliasing. In addition, its limitations in terms of modelling/imaging accuracy make more evident some problems that exist but are often ignored when using reverse time migration with synthetic data.
Presentation Date: Wednesday, September 27, 2017
Start Time: 3:55 PM
Location: 361A
Presentation Type: ORAL
