Yang Yi, Li Fei, Zhang Nan, Huo Aiqing
School of Electronic Engineering, Xi'an Shiyou University, Xi'an 710065, China.
Sensors (Basel). 2021 Apr 25;21(9):3011. doi: 10.3390/s21093011.
In the process of drilling, severe downhole vibration causes attitude measurement sensors to be erroneous; the errors will accumulate gradually during the inclination calculation. As a result, the ultimate well path could deviate away from the planned trajectory. In order to solve this problem, this paper utilized the stochastic resonance (SR) and chaos phase transition (CPT) produced by the second-order Duffing system to identify the frequency and estimate the parameters of the signal during measurement while drilling. Firstly, the idea of a variable-scale is introduced in order to reconstruct the frequency of the attitude measurement signal, and an SR frequency detection model based on a scale transformation Duffing system is established in order to meet the frequency limit condition of the SR. Then, an attitude measurement signal with a known frequency value is input into the Duffing chaos system, and the scale transformation is used again to make the frequency value meet the parameter requirement of chaos detection. Finally, two Duffing oscillators with different initial phases of their driving signal are combined in order to estimate the amplitude and phase parameters of the measurement signal by using their CPT characteristics. The results of the laboratory test and the field-drilling data demonstrated that the proposed algorithm has good immunity to the interference noise in the attitude measurement sensor, improving the solution accuracy of the inclination in a severe noise environment and thus ensuring the dynamic stability of the well trajectory.
在钻井过程中，严重的井下振动会导致姿态测量传感器产生误差；这些误差在倾角计算过程中会逐渐累积。结果，最终的井眼轨迹可能会偏离计划轨迹。为了解决这个问题，本文利用二阶杜芬系统产生的随机共振（SR）和混沌相变（CPT）来在随钻测量时识别信号频率并估计信号参数。首先，引入变尺度思想以重构姿态测量信号的频率，并建立基于尺度变换杜芬系统的SR频率检测模型以满足SR的频率极限条件。然后，将具有已知频率值的姿态测量信号输入到杜芬混沌系统中，并再次使用尺度变换使频率值满足混沌检测的参数要求。最后，将两个驱动信号初始相位不同的杜芬振子组合起来，利用它们的CPT特性估计测量信号的幅度和相位参数。实验室测试结果和现场钻井数据表明，所提出的算法对姿态测量传感器中的干扰噪声具有良好的抗干扰能力，在强噪声环境下提高了倾角的求解精度，从而确保了井眼轨迹的动态稳定性。
