井下接收信号的改进分层阈值降噪方法
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摘要
针对旋转导向钻井中井下接收信号的噪声干扰问题,提出一种在分层阈值基础上改进阈值函数的消噪方法。分层阈值地改进保证了小波系数经阈值作用后的平滑过渡,克服了传统阈值函数带来的恒定偏差,同时具有很强的灵活性。选取不同小波进行了多尺度分解与重构实验,得到Sym6小波基降噪结果最好,失真最小。采用全局阈值、分层阈值和改进分层阈值等不同降噪算法对井下接收信号实现了降噪处理,同时特别研究了小波分解层数对降噪效果的影响,对比分析了降噪后的信噪比、均方根误差和相关系数。实验结果表明,采用Sym6小波4层改进的分层阈值法取得了最佳的降噪效果。
In order to solve the problem of noise interference of downhole receiving signal in rotary steerable drilling an improved noise-eliminating method by using threshold function was proposed in this paper on the basis of layered threshold. The improved layered threshold function ensured the smooth transition of the wavelet coefficients after the threshold overcome the constant deviation caused by the traditional threshold function and has a strong flexibility. The multi-scale decomposition and reconstruction experiments of different wavelet were carried out and the results show that Sym6 wavelet basis de-noising has the best effect of noise reduction and the least distortion. In addition the influence of the number of wavelet decomposition layers on the noise reduction effect was also studied in this paper and the signal-to-noise ratio mean square root error and correlation coefficient after noise reduction were compared and analyzed. The experimental results show that the optimal de-noising effect is achieved by using 4 layers of improved layered threshold method of Sym6 wavelet.
In order to solve the problem of noise interference of downhole receiving signal in rotary steerable drilling an improved noise-eliminating method by using threshold function was proposed in this paper on the basis of layered threshold. The improved layered threshold function ensured the smooth transition of the wavelet coefficients after the threshold overcome the constant deviation caused by the traditional threshold function and has a strong flexibility. The multi-scale decomposition and reconstruction experiments of different wavelet were carried out and the results show that Sym6 wavelet basis de-noising has the best effect of noise reduction and the least distortion. In addition the influence of the number of wavelet decomposition layers on the noise reduction effect was also studied in this paper and the signal-to-noise ratio mean square root error and correlation coefficient after noise reduction were compared and analyzed. The experimental results show that the optimal de-noising effect is achieved by using 4 layers of improved layered threshold method of Sym6 wavelet.
引文
[1] 汤楠,霍爱清,汪跃龙,等.旋转导向钻井系统下行通讯接收功能的开发 [J].石油学报,2010,31(1):157-160.
[2] 李琪,彭元超,张绍槐,等.旋转导向钻井信号井下传送技术研究 [J].石油学报,2007,28(4):108-111.
[3] MALLAT S G.A theory for multiresolution signal decomposition:the wavelet representation [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1989,11(7):674-693.
[4] DONOHO D L,Johnstone I M.Ideal spatial adaptation via wavelet shrinkage [J].Biometrika,1994,81(12):425-455.
[5] DONOHO D L.De-noising by soft-thresholding [J].IEEE Transactions on Information Theory,1995,41(3):613-627.
[6] JOY J,PETER S,JOHN N.Denoising using soft thresholding [J].International Journal of Advanced Research in Electrical,Electronics and Instrumentation Engineering,2013,2(3):1027-1032.
[7] BRUNO C Z,HONóRIO,RODRIGO D,et al.Well log denoising and geological enhancement based on discrete wavelet transform and hybrid thresholding [J].Energy,Exploration & Exploitation.2012,30(3):417-434.
[8] 林坤,马朝选,彭晓光,等.基于Matlab自然伽马测井曲线小波降噪算法研究 [J].测井技术,2017,41(2):194-198.
[9] 李红延,周云龙,田峰,等.一种新的小波自适应阈值函数振动信号去噪算法 [J].仪器仪表学报,2015,36(10):2200-2206.
[10] 马超群,张亚洲,万晓玉,等.随钻测量系统的井下数据传输方式的研究 [J].西部探矿工程,2014,26(10):58-60,64.
[11] TANG N,WANG Y L,HUO A Q,et al.A downward signal processing method for rotary steerable drilling system based on signal similarity [J].Petroleum Exploration and Development Online,2012,39(1):119-126.
[12] MORTEZANEJAD R,GHOLAMI A.Optimization of wavelet-and curvelet-based denoising algorithms by multivariate SURE and GCV [J].Journal of Geophysics and Engineering,2016,13(3):378-390.
[13] 赵鸿图,刘芳,侯守明.基于改进阈值函数的分数阶小波电能信号去噪 [J].测控技术,2017,36(8):20-25.
[14] 张俊杰,冯俞.分层阈值电力电缆局放电信号的小波去噪研究 [J].电子测量技术,2018,41(5):68-72.
[15] CUI Y,CHEN S J,QU M,et al.Research and application of new threshold de-noising algorithm for monitoring data analysis in nuclear power plant [J].Journal of Shanghai Jiaotong University (Science),2017,22(3):355-360.
[2] 李琪,彭元超,张绍槐,等.旋转导向钻井信号井下传送技术研究 [J].石油学报,2007,28(4):108-111.
[3] MALLAT S G.A theory for multiresolution signal decomposition:the wavelet representation [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1989,11(7):674-693.
[4] DONOHO D L,Johnstone I M.Ideal spatial adaptation via wavelet shrinkage [J].Biometrika,1994,81(12):425-455.
[5] DONOHO D L.De-noising by soft-thresholding [J].IEEE Transactions on Information Theory,1995,41(3):613-627.
[6] JOY J,PETER S,JOHN N.Denoising using soft thresholding [J].International Journal of Advanced Research in Electrical,Electronics and Instrumentation Engineering,2013,2(3):1027-1032.
[7] BRUNO C Z,HONóRIO,RODRIGO D,et al.Well log denoising and geological enhancement based on discrete wavelet transform and hybrid thresholding [J].Energy,Exploration & Exploitation.2012,30(3):417-434.
[8] 林坤,马朝选,彭晓光,等.基于Matlab自然伽马测井曲线小波降噪算法研究 [J].测井技术,2017,41(2):194-198.
[9] 李红延,周云龙,田峰,等.一种新的小波自适应阈值函数振动信号去噪算法 [J].仪器仪表学报,2015,36(10):2200-2206.
[10] 马超群,张亚洲,万晓玉,等.随钻测量系统的井下数据传输方式的研究 [J].西部探矿工程,2014,26(10):58-60,64.
[11] TANG N,WANG Y L,HUO A Q,et al.A downward signal processing method for rotary steerable drilling system based on signal similarity [J].Petroleum Exploration and Development Online,2012,39(1):119-126.
[12] MORTEZANEJAD R,GHOLAMI A.Optimization of wavelet-and curvelet-based denoising algorithms by multivariate SURE and GCV [J].Journal of Geophysics and Engineering,2016,13(3):378-390.
[13] 赵鸿图,刘芳,侯守明.基于改进阈值函数的分数阶小波电能信号去噪 [J].测控技术,2017,36(8):20-25.
[14] 张俊杰,冯俞.分层阈值电力电缆局放电信号的小波去噪研究 [J].电子测量技术,2018,41(5):68-72.
[15] CUI Y,CHEN S J,QU M,et al.Research and application of new threshold de-noising algorithm for monitoring data analysis in nuclear power plant [J].Journal of Shanghai Jiaotong University (Science),2017,22(3):355-360.