【摘要】 为解决油气地球物理勘探中地震资料的噪声问题,研究了Steerable Pyramid分解阈值去噪对地震资料强随机噪声背景下弱信号识别的影响。根据地震资料弱信号的Steerable Pyramid分解系数值较小的特点,从Steerable Pyramid分解域硬阈值去噪出发,采用降低阈值的方法保护Steerable Pyramid分解系数值较小的弱信号,同时针对时域噪声残留采用均值平滑的方法保证去噪效果。经过理论模型和实际资料实验,得出在Steerable Pyramid分解域采用硬阈值降阈值+均值滤波的方法可以从较强的噪声背景中识别出弱信号,并且保证信噪比有足够的提高;在去噪的同时,不但连续性好,反射强的同相轴得到了增强,而且即使连续性差,反射弱的同相轴也得到了有效的保留。采用本方法去噪伪影较少,剖面的保真度较高。更多还原

【Abstract】 To solve the noise problem of seismic data in geophysical exploration of oil and gas,the effect of Steerable Pyramid decomposition threshold denoising on weak signal recognition in the background of strong random noise in seismic data is studied.Then,according to the characteristic of weak signal whose coefficients are small after Steerable Pyramid decomposition,the reduced threshold denoising has been adopted to retain the small coefficients based on hard threshold,and the smoothing method is used to remove the outlier in time domain.The theoretical and real experiments show that we can recognize weak signal from strong noise using reduced hard threshold,and the SNR is improved enough.In the meantime,not only the phase axis which is well continuity and strong reflection is enhanced,but also the phase axis which is bad continuity and slight reflection is retained effectively.The pseudo-image is less and the fidelity of profile is high when we adopt reduced hard threshold to recognize weak signal.更多还原