An approach to model three-phase flow coupling during steam chamber rise

2013 ◽  
Vol 92 (6) ◽  
pp. 1100-1112 ◽  
Author(s):  
Muhammad Murtaza ◽  
Zhongxue He ◽  
Hassan Dehghanpour
Keyword(s):  
Phase Flow ◽  
Steam Chamber ◽  
Flow Coupling ◽  
Three Phase ◽  
Three Phase Flow

Three-Phase Flow during Steam Chamber Rise

2012 ◽  
Author(s):  
Muhammad Murtaza ◽  
Hassan Dehghanpour
Keyword(s):  
Phase Flow ◽  
Steam Chamber ◽  
Three Phase ◽  
Three Phase Flow

scholarly journals Application of Artificial Intelligence and Gamma Attenuation Techniques for Predicting Gas–Oil–Water Volume Fraction in Annular Regime of Three-Phase Flow Independent of Oil Pipeline’s Scale Layer

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1460
Author(s):  
Abdulaziz S. Alkabaa ◽  
Ehsan Nazemi ◽  
Osman Taylan ◽  
El Mostafa Kalmoun
Keyword(s):  
Gamma Radiation ◽  
Volume Fraction ◽  
Phase Flow ◽  
Gas Oil ◽  
Oil Pipeline ◽  
Intelligent Technique ◽  
Scale Layer ◽  
Three Phase ◽  
Three Phase Flow ◽  
Annular Regime

To the best knowledge of the authors, in former studies in the field of measuring volume fraction of gas, oil, and water components in a three-phase flow using gamma radiation technique, the existence of a scale layer has not been considered. The formed scale layer usually has a higher density in comparison to the fluid flow inside the oil pipeline, which can lead to high photon attenuation and, consequently, reduce the measuring precision of three-phase flow meter. The purpose of this study is to present an intelligent gamma radiation-based, nondestructive technique with the ability to measure volume fraction of gas, oil, and water components in the annular regime of a three-phase flow independent of the scale layer. Since, in this problem, there are several unknown parameters, such as gas, oil, and water components with different amounts and densities and scale layers with different thicknesses, it is not possible to measure the volume fraction using a conventional gamma radiation system. In this study, a system including a 241Am-133Ba dual energy source and two transmission detectors was used. The first detector was located diametrically in front of the source. For the second detector, at first, a sensitivity investigation was conducted in order to find the optimum position. The four extracted signals in both detectors (counts under photo peaks of both detectors) were used as inputs of neural network, and volume fractions of gas and oil components were utilized as the outputs. Using the proposed intelligent technique, volume fraction of each component was predicted independent of the barium sulfate scale layer, with a maximum MAE error of 3.66%.

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.

Sign in / Sign up

Export Citation Format

Share Document