Study On Measurement Of Flowrate And Its Related Parameters Of Oil-gas Two-phase Flow

Gas-liquid two-phase flow widely exists in many industries such as petroleum and chemical industry, and the research on the two-phase flow has been paid more and more attention. However, the intrinsic complexity of the two-phase flow causes many difficulties in measuring the parameters of the two-phase flow. The measurement technology for the two-phase flow has been one of the bottlenecks in the research field of the two-phase flow.The flowrate parameters of the two-phase flow, which relate to the other parameters of the two-phase flow such as flow pattern, voidage and mass quality, are important for industrial process. The main purpose of this dissertation is to achieve an online measurement method of the flowrates of the oil-gas two-phase flow. And, the measurement of the voidage, the mass quality and the identification of the flow pattern are paid attention to. The main work of the dissertation includes:1. Based on Empirical Mode Decomposition (EMD) and BP neural network, a new method is proposed to identify the flow pattern of the oil-gas two-phase flow. EMD is applied to analyze the differential pressure signal (a nonlinear and non-stationary signal) to obtain frequency components with different scales. The normalized energies of the components are extracted as the eigenvalue of flow pattern. Five flow patterns including bubble flow, plug flow, stratified flow, slug flow and annular flow are identified by using BP neural network. The experimental results indicate that the proposed method is effective for the identification of flow pattern and the identification accuracy are 100%, 89.4%, 93.3%, 96.3% and 96.9% for bubble flow, plug flow, stratified flow, slug flow and annular flow respectively.2. Based on 12-electrode Electrical Capacitance Tomography (ECT) system and Ant System Algorithm (ASA), a new method is proposed for the voidage measurement of the oil-gas two-phase flow. The constructed model of the voidage measurement is the linear combination of the 66 measurement capacitances provided by the ECT. In the establishment of the model, firstly, ASA is used to obtain the capacitance set that has important contribution on the voidage. Then the contribution weight is determined by the Partial Least Square (PLS). In the practical voidage measurement, the appropriate model is chosen to estimate the voidage according to the identified flow pattern. The proposed method has goodreal-time performance and the maximum error of the voidage measurement is less than 6%.3. Seven flowrate measurement models have been evaluated for the oil-gas two-phase flow, and some optimization work of these models has been done according to the characteristics of the oil-gas two-phase flow. Based on the evaluated results, an optimal model is constructed for each flow pattern.4. A new measurement method of the total mass flowrate and individual phase mass flowrates of the oil-gas two-phase flow is proposed based on the optimal flowrate measurement model, the method of the flow pattern identification based on the EMD and BP neural network, and the voidage measurement method based on the ECT and the ASA. The electrical capacitance sensor and the venturi flowmeter are used as the information source. The proposed method selects the optimal flowrate measurement model to implement the flowrate measurement of the oil-gas two-phase flow according to the identified flow pattern. The experimental results show the proposed method is effective.