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The Mukherjee-Brill prediction model of pressure gradient is the common calculation model in oil-gas field development. The laboratory experimental results of multiphase flow show that the average prediction relative error is 35% and the maximum relative error reaches 72%. By comparing the prediction residual of the Mukherjee-Brill model with the test condition parameters, this paper suggests that the predicted residual of Mukherjee-Brill model has a close relationship with the gas-liquid ratio and has no clear correlation with the water content of fluid when the volume flow rate of liquid is constant. This paper first builds a cubic regression model of the prediction residual of the Mukherjee-Brill model regarding the gas-liquid ratio, and subsequently, combining the cubic regression model with the Mukherjee-Brill model, builds a new prediction model of pressure gradient, the MBM model. The results for 90 test groups show that the average prediction relative error of the MBM model is reduced to 7.66%. The MBM model improves the prediction accuracy of the pressure gradient for multiphase flow, and assists in advancing the reliability of the design and analysis of oil and gas wells. [ABSTRACT FROM AUTHOR]

It is crucial for the completion parameter design and production performance detection interpretation to have an accurate pressure gradient. The Aziz prediction model of pressure gradient is a common calculation model in oil-gas field development. The laboratory experiment results of multiphase flow show that the average prediction relative error is 29.62% and the maximum relative error reaches 70.1%. By comparing the prediction residual of the Aziz model with the experiment condition parameters, as the volume flow rate of the liquid phase is constant, this paper considers that the prediction residual of the Aziz model is closely related to the gas liquid ratio and has no clear correlation with the water fraction of fluid phase. Based on unifying the orders of magnitude of the prediction residual and the gas liquid ratio, this paper uses a cubic function of the gas liquid ratio to fit the prediction residual of the model to obtain a new pressure prediction method which is called Aziz-1 model. The results for ninety groups of experimental data show that the average prediction relative error of the Aziz-I model is reduced to 10.82%. Hence, the Aziz-I model improves the prediction accuracy of pressure gradient for multiphase flow. [ABSTRACT FROM AUTHOR]

problem of pressure drop for oil-gas-water three phase vertical flow, the prediction accuracy of the existing prediction model is lower based on the high-accuracy data. This paper displays the predicted pressure drop graphically. Considering the geometrical characteristics of the predicted pressure drop, a new prediction model of pressure drop is built based on the function fitting and interpolation. The new model is suitable for the water content from 0 to 100%. The computed results show that the predicted average relative error is decreased from more than 40% to less than 2.33% under different water content conditions with the experimental data. This paper uses the experimental data with water content 30 and 90% to obtain the pressure drop under water content 60% by interpolation. The average relative error is decreased from 41.5 to 12.00%. [ABSTRACT FROM AUTHOR]