Abstract
The technique of ocean bottom cable (OBC) dual-sensor acquisition is an effective method to suppress the ghost wave and the reverberation at the receiver. With the advent of this technique, the processing method has become the key to the effective use of the OBC dual-sensor data. This paper has developed a new set of processing workflow based on the principle of combining the hydrophone and geophone data. This new process was applied to the OBC data acquired in Bohai area. The actual processing results show that the ghost and the reverberation are attenuated effectively. The frequency energy of the first notch point of the hydrophone data increased from −22 dB to −13 dB, and the frequency energy of the first notch point of the geophone data increased from −18 dB to −10 dB. The spectral characteristics of the dual-sensor data are more reasonable. The frequency spectrum is broadened and richer, and the resolution of the stack profile is improved greatly.
Highlights
In seismic exploration, 3D seismic data describe reservoirs more accurately and guide production more effectively
The actual processing results show that the ghost and the reverberation are attenuated effectively
The frequency energy of the first notch point of the hydrophone data increased from −22 dB to −13 dB, and the frequency energy of the first notch point of the geophone data increased from −18 dB to −10 dB
Summary
3D seismic data describe reservoirs more accurately and guide production more effectively. When the seismic wave travels from the ground up to the sea, it continues to reflect downwards to the bottom of the sea, this process repeats These interferences which disturb effective signal and generate frequency notches are called receiver-side free-surface multiples. In the OBC dual-sensor processing, Barr and Sanders (1989) places special calibration shots to record the direct arrivals and analysis the scale factor at each detection point [7] [8]. This method obtains accurate scale factors, but it will add more cost of a survey. The results show that this processing workflow greatly improves the quality of seismic data
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