【摘要】 奇异值分解(SVD)是一种利用地震资料的相关性进行去噪的有效方法。但对于信号较弱、信噪比极低的微地震资料,传统SVD方法处理效果较差。针对单道微地震记录噪声周期性较强的特点,提出了一种基于单道SVD的去噪方法。首先利用单道微地震记录来构建分解矩阵,然后对矩阵进行奇异值分解,通过对奇异值分布规律的分析,选取适当的奇异值实现矩阵的重构,最后通过SVD反变换得到重构信号,从而达到去除噪声、突出有效信号的目的。实践表明,该方法能有效去除微地震记录中的噪声,为微地震事件的正确识别与震源的准确定位提供强有力的前提保障。更多还原

【Abstract】 The singular value decomposition(SVD) was an effective denoising method using the correlation of seismic data.However,because microseismic signals were weak,and signal to noise ratio of micro-seismic data was extremely low,it was difficult to obtain a satisfactory processing result by using conventional SVD method.According to strong cyclical characteristics of noise to single-channel microseismic record,a denoising method based on single-channel SVD was proposed.It uses a single-channel seismic records to build the decomposing matrix,and then selects appropriate singular values to rebuild the matrix through analyzing the distribution law of the singular values of matrix,the purpose of removing noise and highlighting effective signals is achieved through rebuilding signals by using SVD inverse transform.The practice shows that this method can effectively remove the noise in the microseismic records.It provides a strong guarantee for identifying microseismic events correctly and locating sources exactly.更多还原