Multichannel 3D reconstruction and deghosting techniques based on multicomponent streamer measurements of the pressure wavefield and its associated gradients were recently introduced in literature. In particular, the Generalized Matching Pursuit (GMP) technique was applied to multicomponent 3D synthetic data bringing significant improvements to address the aliasing arising from sparse crossline sampling. In this abstract, we present an example of real data acquired by an experimental 3D towed multicomponent cable array and show the performance of GMP applied to the multicomponent measurements. The real data examples illustrate that GMP reconstructs and deghosts the pressure wavefield onto a 2D receiver grid uniformly sampled at 6.25 m in both, the inline and the crossline directions, starting from a very limited number of crossline samples at realistic spacings (i.e., 75 m). We analyze the contribution of each component to the overall crossline reconstruction. We show that the crossline component of particle velocity is the key enabler for GMP to produce a very effective and robust reconstruction of the three-dimensional wavefield back-scattered by the subsurface for each recorded seismic shot.
We present a fast and effective method to detect and eliminate seismic interference from 3D marine data measured by four-component (4C) streamers.
The interference elimination method we propose acts on each shot record independently from the others, relying on the pressure wavefield being reconstructed (and simultaneously deghosted) on a 2D grid, densely sampled in both the inline and the crossline directions. Such reconstruction is enabled by matching-pursuit-based signal processing techniques proposed recently in the literature that have the capability to explicit the information in the multicomponent measurements. Without these measurements, the reconstruction capability is seriously compromised by the strong crossline aliasing.
We show that the interference can be easily isolated and removed from the data, with a high degree of signal preservation, after the data are reconstructed on a dense grid of receivers. When supported by vector based seismic interference detection, this technique has the potential of being automated and applied directly during the acquisition timeframe.