摘要
为了降低随钻测量过程中噪声对信号的影响,针对经验模态分解(EMD)去噪方法粗糙和小波包去噪方法缺乏自适应的问题,提出了一种基于EMD-小波包的随钻测量信号去噪方法。利用EMD分解自适应的特点将随钻测量信号分解成几个IMF分量;根据信号自相关函数的特性找出主要含噪的IMF分量,再利用小波包阈值去噪方法将含噪IMF分量中的噪声去除;将去噪后的IMF分量和剩余的分量重构,得到去噪后的随钻测量信号。为验证方法的有效性,进行了随钻测量实验并用该方法对采集的信号进行处理。结果表明该方法能够很好地去除随钻测量信号中噪声的干扰,提高信号的信噪比。
In order to reduce the influence of noise on the signal during drilling process,aiming at the problem that the EMD denoising method is rough and wavelet packet denoising methods is lack of adaptation,a new denoising method based on EMD-wavelet packet is proposed.Firstly,the measured signal is divided into several IMF components by using the characteristics of EMD decomposition;And then take advantage of the characteristics of signal autocorrelation function to find the main noise components of the IMF,and using wavelet packet denoising method to denoise the the main noise components of the IMF;Finally,the denoised IMF component and the remaining components are reconstructed to obtain the measured signal while drilling.In order to verify the validity of the method,the experiment is carried out and the signal is processed by this method.The results show that the method can remove the noise of the measured signal and improve the signal to noise ratio.
出处
《测井技术》
CAS
CSCD
2017年第6期738-742,共5页
Well Logging Technology
基金
国家自然科学基金(41672363
U1404510
61440007)
河南省科技攻关项目(172102210289)
河南省高校基本科研业务费专项资金(NSFRF1619)
河南省创新型科技人才队伍建设工程(CXTD2016054)
河南理工大学杰出青年基金(J2017-5)
关键词
随钻测量
信号去噪
经验模态分解
小波包
自相关
measurement while drilling
signal denoising
empirical mode decomposition (EMD)
wavelet packet
autocorrelation