噪声激振下的油井动液面测量方法研究

油井动液面深度是原油开采中的关键工作参数,也是油田合理安排开采计划的重要依据。 针对目前声共振法存在测量 范围不足和测量精度较低的问题,论文提出了噪声激振下的油井动液面测量优化方法。 本文首先探究了激励频带变化对测量 结果的影响,并建立了强噪声激励下系统输出响应信号的数学模型。 然后,根据建立的数学模型提出了共振信号的提取算法, 通过功率谱估计和自适应同态滤波有效抑制了强噪声对共振信号的干扰。 最后,研究了基于双线性插值的离散频谱校正算法, 实现了共振特征参数的精确估计。 实验结果表明,该方法能在强噪声干扰下提取出共振信号,实现了超过 1 700 m 的动液面稳 定测量,且波动小于 2 m。

Research on detection of dynamic liquid level of oil wells based on noise excitation

As an essential working parameter in crude oil exploitation, the dynamic liquid level depth of oil well is also the indispensable basis for the reasonable arrangement of oil exploitation. In this article, the optimization method based on noise excitation is proposed to ameliorate the existing acoustic resonance method, which has insufficient measurement range and low measurement accuracy. Firstly, the effect of various excitation frequency bands on the measurement results is investigated, and the mathematical model of the output response signal of the system with strong noise excitation is formulated. Then, the extraction algorithm of resonance signal is proposed, which is based on the established mathematical model. The power spectrum estimation and the adaptive homomorphic filtering are applied to suppress the interference of strong noise. Finally, the discrete spectrum correction algorithm based on bilinear interpolation is studied. The resonance characteristic parameters can be estimated accurately. Experimental results show that the resonance characteristic can be extracted under strong noise. The stable measurement of dynamic liquid level can be achieved, where the length of liquid level was over 1 700 m and fluctuation was less than 2 m.