Prestack Data

Figure shows a constant offset section of the prestack, unmigrated data. It is windowed around the BSR. The figure shows numerous strong diffractions underneath the BSR. These diffractions can be caused by three-dimensional features such as small gas pockets. Scattering or side-swipe energy from such features might be visible underneath the BSR Lee et al. (1994).

 

diffractor
Figure 4 Constant offset section of the data.

Examining the raw prestack CMP gathers (Figure ), a traveltime kink is very striking in all reflections near the central offset of the CMP gathers. This kink occurs exactly at the transition zone between the non-linear cable group spacing of 100 m at the near-offsets, and 50 m group spacing at the far-offsets.

 

cmp-ann
Figure 5 Upper panel shows a raw CMP gather. Lower panel shows the CMP gather after interpolating the near-offset traces, resulting in a constant group spacing of 50 m at all offsets.

One possible way of eliminating the traveltime kink in the data is adding the far-offset traces in pairs to simulate a constant cable spacing of 100 m at all offsets. This correction, however, causes the data to have less spatial resolution than the original data, based on a decrease from 48 to 36 traces. Furthermore, the group summation causes a significant loss in temporal frequency content at the far-offsets because of spatial averaging of moveout delayed reflections across a twice longer effective group array. A possible way to compensate for this low-frequency group array response is to filter (deconvolve) the far-offset data in the k-x domain. However, the decreased number of summed far-offset traces results in a very short data series, which makes accurate spectral estimates and the application of spatial deconvolutional filters difficult. Another way to account for this frequency loss is to deconvolve the far-offsets as a function of Snell's parameters p in the slant stack domain. Unfortunately, the small number of traces tends to introduce large edge effects in the slant-stack spectrum. These edge effects could be minimized by using a least-squares slant stack, which, however, would smear the notches in the $\tau-p$ spectrum; the resulting deconvolution would overemphasize those portions of the spectrum. Therefore, it seems unreasonable to correct the raw data for the different group spacing by summing the far-offset traces in pairs. A simple linear interpolation of the near-offset traces after NMO, with source wavelet deconvolution and amplitude calibration to compensate for the hydrophone array attenuation, appears to be a better method for suppressing the non-linear cable effects. Figure displays a CMP gather after application of those corrections, which will be discussed in more detail in section 2.4.