This study aimed to obtain the production profiles of oil-in-water flow under low flow rate and high water-cut conditions in oil wells.A combination production profile logging composed of an arc-type conductance senso...This study aimed to obtain the production profiles of oil-in-water flow under low flow rate and high water-cut conditions in oil wells.A combination production profile logging composed of an arc-type conductance sensor(ATCS)and a cross-correlation flow meter(CFM)with a center body is proposed and experimentally evaluated.The ATCS is designed for water holdup measurement,whereas the CFM with a center body is proposed to obtain the mixture velocity.Then,a drift-flux model based on flow patterns is established to predict the individual-phase superficial velocity of oil-in-water flows.Results show that the ATCS possesses high resolution in water holdup measurement and that flow pattern information can be deduced from its signal through nonlinear time series analysis.The CFM can enhance the correlation of upstream and downstream signals and simplify the relationship between the cross-correlation velocity and mixture velocity.On the basis of the drift-flux model,individual-phase superficial velocities can be predicted with high accuracy for different flow patterns.展开更多
基金supported by the National Natural Science Foundation of China(Nos.51527805 and 11572220)
文摘This study aimed to obtain the production profiles of oil-in-water flow under low flow rate and high water-cut conditions in oil wells.A combination production profile logging composed of an arc-type conductance sensor(ATCS)and a cross-correlation flow meter(CFM)with a center body is proposed and experimentally evaluated.The ATCS is designed for water holdup measurement,whereas the CFM with a center body is proposed to obtain the mixture velocity.Then,a drift-flux model based on flow patterns is established to predict the individual-phase superficial velocity of oil-in-water flows.Results show that the ATCS possesses high resolution in water holdup measurement and that flow pattern information can be deduced from its signal through nonlinear time series analysis.The CFM can enhance the correlation of upstream and downstream signals and simplify the relationship between the cross-correlation velocity and mixture velocity.On the basis of the drift-flux model,individual-phase superficial velocities can be predicted with high accuracy for different flow patterns.
