油井含水在线测量技术的研究进展

Research Progress on On-line Measurement Technology of Oil Well Water Content

本文系统地介绍了当前油井含水率在线检测方法,分析了油井含水率测量的影响因素,综述了其研究进展。为了提高油井含水率测量的准确性和稳定性,总结了近年来出现的基于多传感器融合技术的含水率检测方法,即应用偏最小二乘法(PLS)、神经网络、多维回归分析、支持向量机等方法来构建数据驱动模型。研究表明,结合传统检测方法和多传感器信息融合的原油含水率在线测量技术将是未来油井含水率测量的主要发展方向。

This paper systematically introduces the current on-line detection method of oil well water content, analyzes the influencing factors of oil well water content measurement, and summarizes its research progress. In order to improve the accuracy and stability of oil well water content measurement, the water content detection method based on multi-sensor fusion technology in recent years is summarized, namely partial least squares (PLS), neural network, multi-dimensional regression analysis and support vector machines and other methods to build a data-driven model. Research shows that the online measurement technology of crude oil moisture content combined with traditional detection methods and multi-sensor information fusion will be the main development direction of oil well water content measurement in the future.