CCUS封存环境CO 2泄漏监测数据融合算法研究

Research on data fusion algorithm for CO_(2) leakage monitoring in CCUS storage environment

为进一步探究如何提升CCUS封存CO_(2)项目的运行质量,以提升数据监测水平的角度入手,结合实际项目特征与需求,首先整合传感器技术、数据通信技术等,搭建面向CCUS封存环境下的CO_(2)泄漏监测数据系统;而后为提升系统运行质量,设计卡尔曼滤波数据融合算法,以最限度消除数据测量误差,实现更为准确的数据监测。从现场实验测试效果来看,建立的数据监测系统能够实现更为准确的监测,预计其在后续工作中也具有潜在应用价值。

To further explore how to improve the operational quality of CCUS storage CO_(2) project,starting from the perspective of improving data monitoring level,combined with the actual project characteristics and needs,first integrated sensor technology,data communication technology,etc.,and built a CO_(2) leakage monitoring data system for CCUS storage environment.Then,in order to improve the quality of system operation,a Kalman filtering data fusion algorithm was designed to minimize data measurement errors and achieve more accurate data monitoring.From the on-site experimental testing results,it can be seen that the established data monitoring system can achieve more accurate monitoring,and it is expected to have potential application value in subsequent work.