基于模糊多级时频峰值滤波消减地震勘探随机噪声
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摘要
为解决时频峰值滤波采用单一窗长无法同时压制随机噪声和保留信号特征的问题,需要针对信号和噪声设置不同长度的窗函数,提出一种基于模糊判别的多级窗长时频峰值滤波方法。该方法结合模糊判决准则,根据地震信号局部时变特征模糊判定地震图像中各像素隶属于有效信号和随机噪声的程度。对于模糊分段后的信号和噪声,分别根据信号频率特征和噪声强度设置多级时频峰值滤波窗长时频峰值滤波算法,在噪声区域采用较长的窗长以压制随机噪声,在信号部分采用较短的窗长以保持地震信号的细节。将模糊多级时频峰值滤波应用于合成记录和共炮点地震勘探记录,结果表明,改进的方法增强了时频峰值滤波算法保持信号特征的能力,能够有效提高地震勘探图像的信噪比。
Aiming at solving the problem that the time-frequency peak filtering(TFPF) hardly recover the subtle structures of the seismic events as attenuating random noise,different windowing lengths need to be set respectively for signal and noise.A fuzzy time-frequency peak filtering(FTFPF) algorithm was proposed using multiple time-windowing lengths.The new method used a fuzzy determination threshold to identify the membership of each sample to the noise segment and signal segment in seismic data.Then the multi-level windowing lengths were set for FTFPF according to the noise intensity in noise segments and frequency characteristics of signal in signal segments.The longer windowing length was used for noisy segments to remove random noise effectively,and the shorter windowing lengths were used in signal segments to preserve the details of the signal.The FTFPF was applied to synthetic records and common-shot point record,the model analysis indicates that the fuzzy discrimination can identify the signal and noise correctly.The filtered result by FTFPF has better ability to remove noise and preserve signal than that by TFPF.The signal-to-noise ratio(SNR) of the seismic image has been improved.
引文
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