Preprocessing

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.

 

flow 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.

 

data_examp
Figure 3 Sample Husky dataset shot-record before (left) and after (right) preprocessing.