基于小波变换的随钻测试数据降噪方法研究

RESEARCH OF DENOISING OIL-DRILLING TESTING DATA BASED ON WAVELET

为消除随钻测试装置采集信号中的噪声,给工程人员提供准确的现场信息,提出了基于小波变换的方法对随钻测试数据进行降噪处理。首先,根据含噪声的随钻测试数据模型建立起小波变换降噪的基本流程。其次,在对含噪信号的小波变换特性分析的基础上,运用自相关函数对其在小波变换尺度空间中进行白噪声检验,确定小波最优分解层数。在分析对比小波降噪阈值的不同选取方式后,采用广义交叉确认理论来计算最优降噪阈值,从而在对信号降噪的同时还最大程度地保留了信号的有效特征成分。最后给出了基于该方法小波变换的随钻测试数据降噪的详细步骤,对实测的钻压和扭矩数据进行了小波降噪,取得了良好的降噪效果,为钻井工程后续分析提供了可靠的数据支撑,证明了本方法的优越性。

To provide accurate real-time information for engineer,a new method based on wavelet transform is proposed to eliminate the noise from signals which is sampled by the test device in oil drilling.First,a denoising flow based on wavelet is established according to the model of the oil-drilling testing data which contained much noise.Second,on the basis of analyzing the transforming characteristics of noisy signal based wavelet,a reasonable level of wavelet decomposition is calculated by using self-correlation function to estimate the white noise verification in wavelet scale spaces.Third,compared with different methods in wavelet threshold selection,an optimal denoising threshold is calculated using generalized cross validation(GCV) to hold the important features of signal and remove the noise from the signal.At last,the paper provides detailed steps of denoising the oil-drilling testing data based on the wavelet transform,which has obtained favorable results.The performance of pressure data and torque data confirms the usefulness of this approach,which provides a reliable data support to engineers for further analysis in drilling engineering.