TRACE INTERPOLATION AND EXTRAPOLATION WITH PARTIAL CRS STACKS

Data regularization, seismic trace interpolation and extrapolation are advantages of partial ZO CRS stacks. We edit the SIGSBEE2A synthetic data record to create sparse data. The gaps are chosen randomly in mid-offset and near-offset ranges. We compare the results of the interpolation with the traces we deleted from the record. The interpolation by partial stacks preserves arrival times and frequencies very well. Especially the arrival times in near-offset are preserved with sub-sampling accuracy. Some interpolated traces contain low-intensity noise over the entire frequency bandwidth. The direct wave should be excluded from the interpolation because of its linear move-out and the hyperbolic approach of the partial CRS stack. Extrapolation is a challenge to the partial CRS algorithm. The Fresnel zone defines physical limitations for the CRS apertures. We extrapolated traces at offsets exceeding twice the Fresnel zone. No surprise that this violation of physical limits leads to amplitude artifacts. These effects start appearing at about 1.5 times the Fresnel zone as extrapolation distance. However, extrapolation within the limits of the Fresnel zone supplies a reliable extension of the reflection events. Although the partial stack determines the attributes for the zero offset ray trace interpolation for offset seismograms can be performed and even an extension of the spread is possible. Best interpolation results are obtained for short or intermediate offsets. INTRODUCTION Many tools in reflection seismic data processing require regular data. Particularly wave equation methods rely on a regular distribution of the acquisition. This requirement needs either an interpolation and regularization of the data or to properly take the acquisition footprint into account. The CRS method, namely the partial CRS stack, provides a tool to regularize and interpolate data where the same parameters are used as in the CRS stack, i.e., no additional stacking parameter determination is required. The partial CRS method (Baykulov and Gajewski, 2009b) is derived from the conventional ZO CRS stack (Müller, 1999). The common reflection point is calculated over a window comprising the midpointdisplacement coordinate and a limited number of contributing half-offset traces. This calculated trace is saved for every half-offset coordinate. The CRS approach improves the SNR and provides the ability to interpolate traces. Therefore, it can create supergathers consisting of significantly more traces than the original data record. In this paper we will investigate trace interpolation and extrapolation on a synthetic data record which enables direct comparison of real and interpolated or extrapolated traces. Sine the CRS stack determines the attributes for zero offset we expect the best results of interpolation for the near offset traces. First, we will use the CRS stack on the synthetic Sigsbee2A data record to interpolate traces, which previously were deleted from the shot-gather. We compare the deleted traces to the interpolated traces and analyze the improvement of the SNR by this routine. The extrapolation to extend the acquisition is investigated in a second numerical experiment. 210 Annual WIT report 2010 TRACE INTERPOLATION Interpolation of seismic traces has a long history in seismic processing. The most prominent interpolation technique is the generation of ZO traces. Since more than 60 years the ZO stack provides the first image in the CMP processing chain. Regular geophysical data acquisition has a major influence on the stability and reliability of various processing algorithms, especially waveform-based techniques. However broken geophones, varying geophone spacing, rivers or other obstacles may lead to data gaps. Once the geophone spacing gets too large wave equation-based processing algorithms may encounter aliasing effects. Another problem specific to marine data acquisition originates from missing near offset data. This data is essential for surface-related multiple elimination (SRME; cf. Verschuur et al. (1992)). Dümmong et al. (2009) show that in a 2D-medium prediction errors of the SRME were considerably reduced after partial CRS stack interpolation of near offset traces. First we consider the interpolation of seismic traces where we investigate different offset ranges (near, mid, and far offsets). Time Domain Figure 1(a) shows the original traces taken from the Sigsbee2A data record. Next to it, in Figure 1(b) the result of the interpolation over the data gaps is shown. A first inspection reveals a fairly good comparison