Evaluation of Two-Phase Flow Test Pipeline Configurations for an Offshore Oil Field

1983 ◽  
Author(s):  
J.P. Brill ◽  
T.R. Sifferman ◽  
Zelimir Schmidt ◽  
Yugdutt Sharma ◽  
Kunal Dutta-Roy
Keyword(s):  
Two Phase Flow ◽  
Oil Field ◽  
Phase Flow ◽  
Two Phase ◽  
Flow Test ◽  
Offshore Oil

Air/water two-phase flow test tunnel for airfoil studies

1994 ◽  
Vol 29 (1) ◽  
pp. 249-256
Author(s):  
H. Ohashi ◽  
Y. Matsumoto ◽  
Y. Ichikawa ◽  
T. Tsukiyama
Keyword(s):  
Two Phase Flow ◽  
Phase Flow ◽  
Two Phase ◽  
Flow Test

scholarly journals A study of relative permeability parameters on rock cores using a two-phase flow test

2017 ◽  
Vol 28 (3) ◽  
pp. 177-192
Author(s):  
Chung-Hui Chiao ◽  
Chi-Wen Yu ◽  
Shih-Chang Lei ◽  
Jyun-Yu Lin ◽  
Chia-Yu Lu
Keyword(s):  
Relative Permeability ◽  
Two Phase Flow ◽  
Phase Flow ◽  
Two Phase ◽  
Rock Cores ◽  
Flow Test

scholarly journals The two-phase flow analysis of helico-axial oil-gas multiphase pump for offshore oil fields

2018 ◽  
Vol 163 ◽  
pp. 012015
Author(s):  
S Y Li ◽  
J Zhang ◽  
X P Jiang ◽  
H Zhu ◽  
Y X Xiao ◽  
...  
Keyword(s):  
Two Phase Flow ◽  
Flow Analysis ◽  
Oil Fields ◽  
Phase Flow ◽  
Two Phase ◽  
Multiphase Pump ◽  
Offshore Oil ◽  
Oil Gas

scholarly journals Operational Flexibility of Two-Phase Flow Test Rig for Investigating the Dynamic Instabilities in Tube Boiling Systems

2020 ◽  
Vol 8 ◽  
Author(s):  
Ayman Temraz ◽  
Falah Alobaid ◽  
Thomas Lanz ◽  
Ahmed Elweteedy ◽  
Bernd Epple
Keyword(s):  
Two Phase Flow ◽  
Phase Flow ◽  
Operational Flexibility ◽  
Test Rig ◽  
Two Phase ◽  
Flow Test

scholarly journals Prediction performance advantages of deep machine learning algorithms for two-phase flow rates through wellhead chokes

2021 ◽  
Vol 11 (3) ◽  
pp. 1233-1261
Author(s):  
Hossein Shojaei Barjouei ◽  
Hamzeh Ghorbani ◽  
Nima Mohamadian ◽  
David A. Wood ◽  
Shadfar Davoodi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Flow Rate ◽  
Prediction Accuracy ◽  
Two Phase Flow ◽  
Prediction Performance ◽  
Oil Field ◽  
Large Field ◽  
Phase Flow ◽  
Two Phase ◽  
Flow Rates

AbstractTwo-phase flow rate estimation of liquid and gas flow through wellhead chokes is essential for determining and monitoring production performance from oil and gas reservoirs at specific well locations. Liquid flow rate (QL) tends to be nonlinearly related to these influencing variables, making empirical correlations unreliable for predictions applied to different reservoir conditions and favoring machine learning (ML) algorithms for that purpose. Recent advances in deep learning (DL) algorithms make them useful for predicting wellhead choke flow rates for large field datasets and suitable for wider application once trained. DL has not previously been applied to predict QL from a large oil field. In this study, 7245 multi-well data records from Sorush oil field are used to compare the QL prediction performance of traditional empirical, ML and DL algorithms based on four influencing variables: choke size (D64), wellhead pressure (Pwh), oil specific gravity (γo) and gas–liquid ratio (GLR). The prevailing flow regime for the wells evaluated is critical flow. The DL algorithm substantially outperforms the other algorithms considered in terms of QL prediction accuracy. The DL algorithm predicts QL for the testing subset with a root-mean-squared error (RMSE) of 196 STB/day and coefficient of determination (R2) of 0.9969 for Sorush dataset. The QL prediction accuracy of the models evaluated for this dataset can be arranged in the descending order: DL > DT > RF > ANN > SVR > Pilehvari > Baxendell > Ros > Glbert > Achong. Analysis reveals that input variable GLR has the greatest, whereas input variable D64 has the least relative influence on dependent variable QL.

Air/water two-phase flow test tunnel for airfoil studies

1990 ◽  
Vol 8 (5) ◽  
pp. 249-256 ◽  
Author(s):  
H. Ohashi ◽  
Y. Matsumoto ◽  
Y. Ichikawa ◽  
T. Tsukiyama
Keyword(s):  
Two Phase Flow ◽  
Phase Flow ◽  
Two Phase ◽  
Flow Test

Fundamental Study on Injector Flow Characteristics of Self-Pressurizing Fluid for Small Rocket Engines

2020 ◽  
Vol 143 (2) ◽  
Author(s):  
Kazuki Yasuda ◽  
Daisuke Nakata ◽  
Masaharu Uchiumi ◽  
Kugo Okada ◽  
Ryoji Imai
Keyword(s):  
Nitrous Oxide ◽  
Two Phase Flow ◽  
Flow Characteristics ◽  
Acoustic Oscillation ◽  
Chamber Pressure ◽  
Rocket Engines ◽  
Phase Flow ◽  
Two Phase ◽  
Firing Test ◽  
Flow Test

Abstract Nitrous oxide is a suitable propellant for rocket engines and has been widely used in various countries, given its high saturated vapor pressure, which enables self-pressurization. Because nitrous oxide is in a state of vapor–liquid equilibrium in tanks, it is easy to form a gas–liquid two-phase flow by cavitation in feed line. Since accurately estimating the performance of rocket engines requires evaluating the characteristics of propellant flows, tests reported in this paper were conducted using hybrid rocket engines under three conditions: cold flow test, hot firing test at low back pressure, and hot firing test at high back pressure. With consideration to the subcooling degrees, nitrous oxide may be in an unsteady superheated state in the upstream flow of the injector. In a comparison of the pressure ratios between the injector in each test condition, it is observed that a critical two-phase flow was formed in the injector in the cold flow test and in the low backpressure firing test. In the high backpressure hot firing test, the injector flow may be choked, but the large oscillations were observed in chamber pressure and thrust. According to the FFT analysis results, these oscillations were caused by chugging and acoustic oscillation. In light of these experimental results, it is suggested that when the chamber pressure fluctuates due to combustion instability such as chugging and acoustic oscillation, it may affect the injector flow characteristics and the critical two-phase flow.

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