We investigate an implementation of Gaussian beam depth migration which images seismic data after compression by a digital wavelet transform. Conventional Gaussian beam migration consists of two main steps: (1) a local plane wave decomposition of the input seismic traces into directional components or beam traces; and (2) mapping of each beam trace sample to its depth location through dynamic ray tracing into a given velocity model. Instead of migrating each beam time sample individually, we propose to migrate a selection of picked wavelets. These wavelets are associated with the largest coefficients of an appropriate digital wavelet transform of the beam traces. Coupling a Gaussian beam decomposition with a wavelet compression can lead to an improved signal-to-noise ratio and a direct saving in computation at the cost of some reduction in imaging accuracy.
We test this approach on both synthetic and real data sets. By only imaging a small percentage (1% to 3%) of the wavelet coefficients we enhance the signal-to-noise ratio of both stack images and pre-stack common image gathers.
Presentation Date: Wednesday, October 17, 2018
Start Time: 1:50:00 PM
Location: Poster Station 20
Presentation Type: Poster
