Graph-Guided Partial Representation-Based Oil–Gas–Water Flow State Monitoring via Dual-Modal Detection

The detection and monitoring of oil-gas-water three-phase flow is highly demanded in oil-gas well industry. Concentrating on combining the three sub-states of oil, gas and water to form a holistic flow state, a monitoring framework based on graph guided partial representation is proposed while maintaining linkage among flow states. In this framework, a differential pressure (DP)-pulse wave ultrasonic Doppler (PWUD) system is designed for obtaining information of three-phase structure and the intrinsic relationships among different phases, so as to accurately characterize the sub-states of oil, gas and water. Furthermore, within the unified paradigm of variational mode decomposition (VMD), standard VMD and reduced-order VMD (rVMD) are respectively utilized in the information mining of DP mode depicting 1-D flow fluctuations and PWUD mode representing 2-D spatiotemporal flow field. The time-varying non-stationarity of flow evolution is then quantified using statistical analysis. Based on converting flow data to flow features, graph guidance and parts-based nonnegative matrix factorization (NMF) are integrated to model and monitor the flow states in complicated oil-gas-water flow process. The proposed novel scheme about graph guided partial representation-based horizontal oil-gas-water flow state monitoring via dual-modal detection is verified by dynamic experiments on three-phase flow loop at Tianjin University.