Although the Husky dataset is of high quality, significant preprocessing is required to enhance signal quality. Data processing steps, applied using the proprietary OMEGA processing package, are listed in Figure . After geometry assignment, a swell-noise debursting algorithm was applied in the shot- and receiver-record and CMP domains to reduce anomalous low-frequency noise. Ground roll suppression and near-offset bandpass filtering subsequently reduced ground roll and airwave noise. Application of de-spiking and surface-consistent amplitude modules improved the relative amplitude balance across the shot-record and offset panels.
Figure 2 Husky data processing flow chart.
Static time shifts were then complied to generate a second datumed dataset. This dataset was generated by applying two static time shifts - one from the source/receiver location to a intermediate CMP datum, and a second to a constant elevation of -1800 m (assuming a 3200 m/s replacement velocity layer). Reflection statics (that optimized the power of the constant velocity scan stack) also were applied to both datasets. Figure presents a comparison of a shot-record before and after data processing.