基于集合经验模态的随钻脉冲信号优良降噪算法  

Extracting pulse signals in measurement while drilling using optimum denoising methods based on the ensemble empirical mode decomposition

作　　者：郑一[1,2] 孙晓峰[1,2] 陈健[1,2] 岳军[1,2] 

机构地区：[1]青岛理工大学理学院 [2]青岛理工大学数值计算与应用研究所

出　　处：《石油勘探与开发》2012年第6期750-753,共4页Petroleum Exploration and Development

基　　金：国家高技术研究发展计划(863计划)(2008AA09A402)

摘　　要：为了准确提取原始随钻钻井液脉冲信号,采用集合经验模态分解方法,基于固有模态分量构建不同的低通滤波算法,进一步采取方波整形处理,建立脉冲信号的降噪整形算法,并依据算法逼近度指标、相关度指标建立优良降噪算法的判断准则。利用单位脉冲信号、周期性杂波信号和高斯白噪声信号合成数值模拟钻井液信号,分析钻井液信号的降噪效果,所得优良降噪低通滤波算法由去掉前4个固有模态分量的其余模态分量及余项构成,其降噪结果能清晰描述单位脉冲信号,算法的逼近度达到0.7719,相关度高达0.8929。利用选定的优良降噪算法分析了实测的随钻测量钻井液信号,所得结果合理、有效。To extract original pulse signals in measurement while drilling（MWD）,different low-pass filtering methods were designed based on intrinsic mode functions through the ensemble empirical mode decomposition（EEMD）.After shaping square waves,a filtering and shaping algorithm on pulse signals was designed.An indgement criterion of filtering algorithms was established according to the degree of approximation and relevance of the algorithm.To simulate pulse signals in measurement while drilling,unit impulse signal,periodic noise signal and Gaussian white noise signal were combined,the denoising effect on the simulating signals was analyzed.The optimum denoising algorithm is composed of the intrinstic mode functions（without the front 4 intrinsic mode functions） and the remainders in EEMD.The degree of approximation of denoising algorithm is 0.771 9 and relevance is as high as 0.892 9.The real-time mud signals of MWD was analyzed and discussed with the help of the algorithm,the results obtained were reasonable and effective.

关 键 词：脉冲信号 集合经验模态分解(EEMD) 低通滤波 优良降噪算法 

分 类 号：P634.3[天文地球—地质矿产勘探] TN87[天文地球—地质学]