Research Of Spectrum Sharing Processing Technique In Pre-stack Depth Migration

Today, the seismic migration over complex structures and high resolution has become the major development direction of oil exploration. Pre-stack depth migration is the best imaging methods of the complex structures with velocity greatly changed. Because of its high efficiency and good imaging effect, pre-stack depth migration by Kirchhoff integration is widely used in pre-stack depth migration. But Kirchhoff pre-stack depth migration seismic sections have low vertical resolution, so it can't distinguish thin interbedding。The earth is very a complex filter, so seismic waves will greatly change when waves transmit in it. Convolution can lead to the change of spectrum. Some waves in high frequency are weaken more hardly than that in low frequency which make the energy of seismic data centralize in waves of low frequency. Signal-to-Noise of seismic waves become lower, and each frequency waves have different signal-to-Noise. Signal-to-Noise of wave in high frequency is much lower than it in low frequency. Even that seismic wave velocity change along with frequency induces frequency dispersion. This is bad for seismic data processing, and it will inevitable result in low vertical resolution. For improving vertical resolution of pre-stack depth migration, this article has applied spectrum sharing technology to pre-stack depth migration.Spectrum sharing processing technique has considered effective method to improve involution of seismic profile. In the past spectrum sharing processing technique was more used in general processing but not in pre-stack depth migration. In this paper spectrum sharing processing was used is a 2D line, and the outcome showed that spectrum sharing processing technique can spread frequency spectrum effectively. Spectrum sharing processing technique was also used in pre-stack depth migration of 3D seismic data in Xingcheng area which is in the north of Songliao basin, which improved vertical involution of seismic profile.