论文详情
针对地面微地震资料强周期干扰和随机干扰突出的特点以及单一去噪方法无法有效压制噪声的问题,提出了基于单道奇异值分解(singular value decomposition,SVD)和振幅比的联合去噪方法。首先利用单道微地震记录构建分解矩阵,使矩阵各维具有较强的相关性,然后对分解矩阵进行奇异值分解,选取数值居中部分奇异值进行矩阵重构,以达到压制单道微地震记录强周期干扰的目的。其次采用具有伸缩特性时窗的振幅比法改善有效信号与随机噪声的统计特性差异,有效压制微地震资料中的随机噪声。理论模型数据和四川某地区地面微地震射孔资料应用结果表明,联合去噪方法有效地压制了微地震记录中的噪声,提高了资料的信噪比,在很大程度上改善了单一去噪方法无法较好突出微地震有效信号的不足,为后期微地震资料的处理与解释奠定了良好的基础。
In view of ground microseismic data with strong periodic disturbance and random noise,single de-noising method cannot suppress noise effectively.Therefore,a joint denoising method combining single-channel singular value decomposition (SVD) and amplitude ratio is proposed.Initially,a decomposition matrix is constructed using single-channel microseismic record to make the dimensions of the matrix have strong correlation.Next,the SVD is used to the decomposition matrix,then a few of singular values in the middle of singular value sequence are selected for the matrix reconstruction,to suppress the strong periodic disturbance in single-channel in microseismic record.Then,the amplitude ratio method with the expansion time window is adopted to improve the statistical characteristics of effective signal and random noise,to suppress random noise effectively.Testing on both synthetic data and ground microseismic perforation data in a certain area of Sichuan showed that the joint denoising method can highlight effective signals and improve signal-to-noise ratio of microseismic data effectively,which lays a good foundation for the processing and interpretation of microseismic data.
国家自然科学基金(41204101)、四川省重点实验室开放课题基金(2015trqdz03)共同资助。