Severral Digital Techniques And Their Application For Optimizing Quality Of Seismic Data

The high signal-to-noise ratio (SNR) and resolution is the aim that people are pursuing for gaining good seismic profile and geologic interpretation. This paper tells us three methods in order to improve SNR and resolution of seismic data. Natural gradient blind deconvolution algorithm can extract true mixed-phase-wavelet. Adapt beamforming can suppressing single-sensor ground-roll, not only synthetic seismic data but also Yakenbei real seismic data, there is a obvious effect. Mathematical morphology also has a obvious effect on suppressing ground-roll. Natural gradient blind deconvolution algorithm extract true mixed-phase-wavelet, and improve the resolution.Estimating seismic wavelet is one of the most important problems of geophysics. True wavelet's estimating is a important task in seismology, it is the base of seismic deconvolution, migration, feature extracting, geophysics interpretation and so on. Convention deconvolution assumes statistics under seismic wavelet and reflex coefficient are unknown, this will low the resolution and reliability of seismic data. Natural gradient blind deconvolution algorithm hasn't need any assumes, using natural gradient estimate wavelet, gain true mixed-phase-wavelet, and use in deconvolution to improve resolution. First of all, we introduced mathematic foundation of original data's can be separated, then we introduced mathematical principal of seismic blind deconvolution, and inducted compensate function, derived the seismic blind deconvolution's iteration function, at last, we use this method to verify synthetic seismic data and real seismic data, the result shows than natural gradient blind deconvolution algorithm can estimate true mixed-phase-wavelet better, and it can estimate reflex coefficient better.Compare natural gradient blind deconvolution to convention deconvolution, it has many advantages: first, it hasn't needed assuming seismic wavelet minimum phase; second, this algorithm used natural gradient method, and this algorithm seems stead, contraction fast, not sensible to noise, and those are very good to write software; third, this algorithm is adaptive, it can update filter coefficient; forth, in synthetic seismic data, though compare to convention deconvolution, it is obvious that natural gradient blind deconvolution can estimate seismic wavelet better. So, we uses this algorithm to real seismic data, we still have a good effect, it can improve seismic data's resolution.At the same time, this paper also study on improving seismic data's SNR. On single-sensor seismic section, the energy of ground-roll is very strong, reflect wave is hidden, and the SNR is very low. In convention seismic processing, we usually use High-pass filter to suppress ground-roll, it has problems, ground-roll still lie or many effect wave is filtered. F-K method and wavelet transform method also have the same disadvantages. So, we propose adaptive beamforming method to suppress ground-roll. This method uses the different apparent velocity of reflect wave and ground-roll, design cost function, make the filter coefficient better and better, suppress energy of ground-roll area. It is used in Xinjiang Yakenbei single-sensor data, and the effect is very good, SNR is improved.Adaptive beamforming mainly has those advantages. First, on single-sensor seismic section, the energy of ground-roll is very strong, and the SNR is very low. We transform the data to 2D Fourier area in order to make original data and ground-roll are in its self's apparent velocity; Second, we need the beamforming can accept stand signals, at the same time, attenuate other noise, those noise and effect signals have same frequency in time area. We want to design useful filter to improve SNR; Third, when adaptive beamforming suppressing ground-roll, there exit space alias. Ground-roll is in low frequency area, effect wave and other noise are in wide frequency. Ground-roll and effect wave are mixed, especially when group interval is big, it is disadvantage to suppress noise. The group interval in single-sensor is 5m in most times, this decrease the space alias; Forth, the adaptive beamformging has contraction problems, it is up to step's uncertainty. As adaptive beamforming is adaptive, it can be used in suppressing other linear noise; Fifth, in real seismic data processing, compare this method to convention band-pass filter, it is better than band-pass filter in seismic section and frequency section. So this method can be wide in seismic data processing, and has important theory and application value in improve SNR of seismic data.This paper also study mathematical morphology to suppress ground-roll. Mathematical morphology is stand on strict math theory, it's basic idea and method make a important influence on image processing. In fact, mathematical morphology has compromise a new theory, and is applied in many areas. In this paper, we use this method to suppress ground-roll, though its basic calculation, such as dilation, erosion, opens, close. The result shows this method very well, and can perfectly suppress ground-roll. After midian filtering to original data, then suppressing ground-roll with this method, we can see the data became much clean than before, at the same time, the ground-roll has been suppressed and concordant axis became continuiously.