FILTERING VIBROSEIS DATA IN THE PRECORRELATION DOMAIN

Vibroseis data recorded at short source-receiver offsets can be swampe d by direct waves from the source. The signal-to-noise ratio, where pr imary reflections are the signal and correlation side lobes are the no ise, decreases with time and late reflection events are overwhelmed. T his leads to low seismic resolution on the vibroseis correlogram. A ne w precorrelation filtering approach is proposed to suppress correlatio n noise. It is the 'squeeze-filter-unsqueeze' (SFU) process, a combina tion of 'squeeze' and 'unsqueeze' (S and U) transformations, together with the application of either an optimum least-squares filter or a li near recursive notch filter. SFU processing provides excellent direct wave removal if the onset time of the direct wave is known precisely, but when the correlation recognition method used to search for the fir st arrival fails, the SFU filtering will also fail. If the tapers of t he source sweeps are badly distorted, a harmonic distortion will be in troduced into the SFU-filtered trace. SEU appears to be more suitable for low-noise vibroseis data, and more effective when we know the swee p tapers exactly. SFU requires uncorrelated data, and is thus cpu inte nsive, but since it is automatic, it is not labour intensive. With non -linear sweeps, there are two approaches to the S,U transformations in SFU. The first requires the non-linear analytical sweep formula, and the second is to search and pick the zero nodes on the recorded pilot trace and then carry out the S,U transformations directly without requ iring the algorithm or formula by which the sweep was generated. The l atter method is also valid for vibroseis data with a linear sweep. SFU may be applied to the removal of any undesired signal, as long as the exact onset time of the unwanted signal in the precorrelation domain is known or determinable.