基于幅度和相位融合的微波两相流测量系统设计
Design of Microwave Two-phase Flow Measurement System Based on Amplitude and Phase Fusion
李利品 1代雷 1黄燕群 2卢宇 1颜曌恩1
作者信息
- 1. 西安石油大学,陕西省油气井测控技术重点实验室
- 2. 西安现代控制技术研究所
- 折叠
摘要
针对油井开采过程中需要对各相含量进行精确预测以调整开采策略的实际问题,设计了 一种基于微波法的油水两相流检测系统.该系统利用微波在不同介质中透射能力的差异,构建了 一套包含微波信号源、功率放大器、功率分配器、检波器和STM32F103ZET6核心板的硬件电路系统,通过编写AD采集和串口通信的软件代码,来接收检波器端幅度和相位数据.在数据处理方面,分别对幅度数据、相位数据和幅度-相位融合数据采用BP神经网络的方法预测含水率.实验表明:在使用融合数据时,预测准确度可以提高至96.33％,取得了较理想的效果.
Abstract
To address the practical problem of accurately predicting the phase content in oil well production for optimizing ex-traction strategies,a microwave-based oil-water two-phase flow detection system was designed.This system utilized on the differences in microwave transmission capabilities across different media and built a hardware circuit system including a microwave signal source,power amplifier,power distributor,detector,and STM32F103ZET6 microcontroller.By writing AD acquisition and serial communication software codes,amplitude and phase data from the detector end were received.For data processing,BP neural net-work method was employed to predict water cut based on amplitude data,phase data,and amplitude-phase fusion data separately.Experimental results show that when using fused data,the prediction accuracy can be improved to over 96.33％,achieving an ide-al effect.
关键词
幅度和相位融合/微波法/两相流/含水率/BP神经网络/AD采集Key words
amplitude and phase fusion/microwave method/two-phase flow/water content/BP neural network/AD collection引用本文复制引用
基金项目
国家自然科学基金(41874158)
国家自然科学基金(51974250)
陕西省自然科学基金(2023-JC-YB-343)
西安石油大学研究生创新与实践能力培养计划资助(YCS23214243)
2023年陕西省学位与研究生教育研究项目(SXGERC2023086)
出版年
2024
NETL
NSTL
万方数据