Study on measurement of oil gas water three phase flow with conductance correlative flow meter

2008 ◽  
Author(s):  
Guomin Xue ◽  
Yi Shen
Keyword(s):  
Phase Flow ◽  
Flow Meter ◽  
Three Phase ◽  
Three Phase Flow ◽  
Oil Gas

Flow Rate Measurement of Oil∕Gas∕Water Three-Phase Flow with V-Cone Flow Meter

2010 ◽  
Author(s):  
F. S. Zhang ◽  
F. Dong ◽  
Liejin Guo ◽  
D. D. Joseph ◽  
Y. Matsumoto ◽  
...  
Keyword(s):  
Flow Rate ◽  
Phase Flow ◽  
Rate Measurement ◽  
Flow Rate Measurement ◽  
Flow Meter ◽  
Three Phase ◽  
Three Phase Flow ◽  
Oil Gas

Image Fusion of ECT/ERT for Oil-Gas-Water Three-Phase Flow

2011 ◽  
Vol 3 (2) ◽  
pp. 29-34 ◽  
Author(s):  
Lifeng Zhang
Keyword(s):  
Image Fusion ◽  
Electrical Capacitance Tomography ◽  
Phase Flow ◽  
Electrical Capacitance ◽  
Cross Sectional ◽  
Three Phase ◽  
Three Phase Flow ◽  
Capacitance Tomography ◽  
Oil Gas ◽  
Image Fusion Method

The tomographic imaging of process parameters for oil-gas-water three-phase flow can be obtained through different sensing modalities, such as electrical resistance tomography (ERT) and electrical capacitance tomography (ECT), both of which are sensitive to specific properties of the objects to be imaged. However, it is hard to discriminate oil, gas and water phases merely from reconstructed images of ERT or ECT. In this paper, the feasibility of image fusion based on ERT and ECT reconstructed images was investigated for oil-gas-water three-phase flow. Two cases were discussed and pixel-based image fusion method was presented. Simulation results showed that the cross-sectional reconstruction images of oil-gas-water three-phase flow can be obtained using the presented methods.

Multi-Scale Long-Range Magnitude and Sign Correlations in Vertical Upward Oil–Gas–Water Three-Phase Flow

2016 ◽  
Vol 71 (1) ◽  
pp. 33-43 ◽  
Author(s):  
An Zhao ◽  
Ning-de Jin ◽  
Ying-yu Ren ◽  
Lei Zhu ◽  
Xia Yang
Keyword(s):  
Long Range ◽  
Phase Flow ◽  
Scaling Properties ◽  
Long Range Correlations ◽  
Nonlinear Properties ◽  
Three Phase ◽  
Three Phase Flow ◽  
Original Time ◽  
Churn Flow ◽  
Oil Gas

AbstractIn this article we apply an approach to identify the oil–gas–water three-phase flow patterns in vertical upwards 20 mm inner-diameter pipe based on the conductance fluctuating signals. We use the approach to analyse the signals with long-range correlations by decomposing the signal increment series into magnitude and sign series and extracting their scaling properties. We find that the magnitude series relates to nonlinear properties of the original time series, whereas the sign series relates to the linear properties. The research shows that the oil–gas–water three-phase flows (slug flow, churn flow, bubble flow) can be classified by a combination of scaling exponents of magnitude and sign series. This study provides a new way of characterising linear and nonlinear properties embedded in oil–gas–water three-phase flows.

Transfer Heat Mechanism of Oil-Gas-Water Three-Phase Flow in Pipeline

2011 ◽  
Vol 199-200 ◽  
pp. 1609-1612
Author(s):  
Qian Jun Mao
Keyword(s):  
Mathematical Model ◽  
Soil Temperature ◽  
Phase Flow ◽  
Fundamental Theory ◽  
Three Phase ◽  
Three Phase Flow ◽  
The Mathematical Model ◽  
Oil Gas ◽  
Flow Transfer ◽  
Heat Mechanism

It is well known that the oil-gas-water three-phase flow belongs to the field of multiphase flow,transfer heat mechanism of which is very complicated.Transfer heat mechanism is affected not only by different buries in oil gathering pipeline, but also by soil temperature periodicity change. Both domestic and oversea scholars have already studied on the transfer heat mechanisms of oil-gas-water three phase,but they are still in the level of fundamental theory and laboratory.This paper establishes transfer heat models of the oil-gas-water three-phase flow in buried oil gathering pipeline, including the physical model and the mathematical model,and testing in experiment .The purpose of this paper is to analyze value between the calculation and the testing . The results show that the mathematical model of this paper is accurate , and the relative error is ≤ 10%.

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