基于超声波和云测试的油井液面测试系统研究

针对目前油井液面深度测试系统测量范围小、误差大、稳定性低的缺点,提出了基于声波法测动液面原理,利用时间序列分析技术、新息自适应卡尔曼滤波技术来实时检测回波信号,进而实现对油井液面深度的高精度测量和噪声处理；选用FPGA和云测试技术成功实现了油井液面深度测量系统的远程化和网络化。基于云测试的油井液面远程监测系统目前已在油田生产现场通过测试,测试结果表明,系统稳定,算法实时、高效,动液面深度测量误差小,测量精度高,能满足实际工程应用。

The Study of Oil Well Remote Monitoring System Based on the Ultrasonic Distance Measurement and Cloud Testing

Aiming at the shortcomings of the small measuring range, low measurement accuracy and low stability of the current well test system, A method based on acoustic method is proposed to measure the fluid level of the oil well. The time series analysis techniques and the Innovation-based adaptive Kalman filter are also used to Real-time detect the echo signal and eliminate the noise error. The network and remote oil level depth measurement system is successfully implemented based on FPGA and cloud testing. The system has been used in the producing oil field. The actual test, this system has high accuracy, real time and efficient. And the measurement error is small, which can meet the practical engineering applications.