Extensive experimental data were acquired for oil-water flow in horizontal pipes for a very wide range of oil viscosity. Pressure drop, flow rate, input water fraction, in-situ holdup, mixture temperature, and flow pattern data were obtained for 612 oil-water tests in 1.5-in. pipe, and 587 tests in 1-in. pipe. Oils with viscosities of 4.7, 58, 84, and 115 cp were used in the 1.5-in. runs, while the 1-in. tests used 237-cp and 2116-cp oils, all measured at 70 degrees F. Mixture velocities varied from 1.5 to 12 ft/s, while input water fractions ranged from 0.05 to 0.90, and mixture temperatures were between 50 and 98 degrees F. A new correlation is proposed for the prediction of the inversion point of an oil-water dispersion. It was found that the input water fraction required to invert the dispersion decreases with increasing oil viscosity. Pressure drop due to friction was also found to increase Pressure drop due to friction was also found to increase abruptly when the flowing oil-water mixture reached the inversion point where the external phase inverted from water to oil. Two pressure-gradient prediction models are presented; one for stratified, and the other for homogeneously dispersed oil-water flows. Comparison between model predictions and experimental data shows satisfactory predictions and experimental data shows satisfactory agreement. Experimental oil-water flow pattern maps were developed. The existing flow pattern in an oil-water mixture depends primarily on mixture velocity, input water fraction, and primarily on mixture velocity, input water fraction, and oil viscosity (only when oil is the external phase). Introduction Cocurrent flow of two immiscible liquids such as oil and water in horizontal pipes is a common occurrence in the petroleum industry. The need to understand the nature petroleum industry. The need to understand the nature and flow behavior of this type of multiphase flow is very complicated due to the existence of various flow patterns and different mechanisms governing them. This phenomenon, coupling with the hard-to-predict rheological behavior of an oil-water system, have been the driving force behind a considerable research effort in this area. The results of these studies would lead to better predictions of the existing flow pattern and its associating pressure gradient, yielding a better designing scheme for such system. This paper investigates the simultaneous flow of different oil-water fluid systems. The study involves gathering approximately 1,200 oil-water experimental data points in 1-in. and 1.5-in. horizontal pipes, for a wide range of flow conditions (flow rates, temperatures, input water fractions, etc.), and also for a wide range of oil viscosities. A correlation is presented, based upon this study and some other published results, for the prediction of the inversion point of an oil-water dispersion system. Two pressure-gradient point of an oil-water dispersion system. Two pressure-gradient prediction models were also developed for two different prediction models were also developed for two different oil-water flow patterns; namely, stratified and homogeneous. In addition, typical experimental oil-water flow pattern maps are also presented. LITERATURE REVIEW An oil-water mixture flow presents a unique and complex problem for pipeline transportation of heavy crude oils in problem for pipeline transportation of heavy crude oils in the petroleum industry due to its complicated rheological behavior, and the vast difference in pressure gradients encountered for different flow patterns. For the homogeneous flow pattern, the system of two immiscible liquids, such as oil and water, could become even more complex since the resulting mixed fluid can turn into an emulsion. An emulsion is a dispersed system which consists of two immiscible liquids. An unstable emulsion, or a dispersion, is an emulsion which can separate into the original phases within a reasonable period of time at rest. These dispersions can also exhibit Newtonian or non-Newtonian rheological behavior; depending on each specific oil-water system. Another phenomenon that further complicates an oil-water dispersion system is the phase inversion phenomenon, in which the dispersed phase inversion phenomenon, in which the dispersed phase switches to the continuous phase. phase switches to the continuous phase. P. 155

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This work presents interfacial tension (IFT) data for the CO2–water system in the pressure and temperature range of (1.48 to 20.76) MPa and (298.15 to 333.15) K. The IFT evaluation is carried out using the pendant drop method. Inaccuracies observed in the literature such as consideration of pure phase densities and short presaturation time durations have been avoided by utilizing saturated phase densities and long presaturation time durations. The water-rich phase density is evaluated using a literature correlation, and the CO2-rich phase density is evaluated using equation-of-state modeling approach. Also, presaturation times were extended up to 24 h to obtain equilibrated IFT data for the CO2–water system. It is observed that the IFT reduces with pressure when the CO2-rich phase is a gas at both subcritical and supercritical temperatures. Further, the IFT values reached a plateau at about 23 mN·m–1 at higher pressures (13.89 to 20.79 MPa) and for the entire temperature range. A predominant buoyancy effect is observable at higher pressures due to the reduction in phase density differences. Comparatively, the evaluated IFT data trends are about (5 to 7) mN·m–1 lower at high pressures than those reported in most of the literature.

Summary This paper presents a general and unified equation for flowing temperature prediction that is applicable for the entire range of inclination angles. The equation degenerates into Ramey's equations for ideal gas or incompressible liquid and into the Coulter and Bardon equation, with the appropriate assumptions. This work also proposes an approximate method for calculating the Joule-Thomson coefficient for black-oil models. Introduction Flowing temperature distribution often is predicted with different methods for pipelines and wellbores. The Ramey method usually is used for predicting wellbore temperature distribution. This method rigorously incorporates the complex process of transient heat transfer between the wellbore and the reservoir. Ramey's method, however, is limited to either ideal gas or incompressible liquid flow. The Coulter and Bardon equation commonly is used for pipeline temperature prediction. A more rigorous thermodynamic behavior of the flowing fluid is taken into account, incorporating the Joule-Thomson coefficient. Although the Coulter and Bardon equation originally was derived for gas flow, it also is used for single-phase liquid or two-phase flow. This equation is limited, however, by the assumptions of steady-state heat transfer with a constant-temperature environment and horizontal flow.

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A comprehensive model is formulated to predict the flow behavior for upward two-phase flow. This model is composed of a model for flow-pattern prediction and a set of independent mechanistic models for predicting such flow characteristics as holdup and pressure drop in bubble, slug, and annular flow. The comprehensive model is evaluated by using a well data bank made up of 1,712 well cases covering a wide variety of field data. Model performance is also compared with six commonly used empirical correlations and the Hasan-Kabir mechanistic model. Overall model performance is in good agreement with the data. In comparison with other methods, the comprehensive model performed the best.

Summary A unified steady-state two-phase flow mechanistic model for the prediction of flow pattern, liquid holdup and pressure drop is presented that is applicable to the range of inclination angles from horizontal (0°) to upward vertical flow (90°). The model is based on two-phase flow physical phenomena, incorporating recent developments in this area. It consists of a unified flow pattern prediction model and unified individual models for stratified, slug, bubble, annular and dispersed bubble flow. The model can be applied to vertical, directional and horizontal wells, and horizontal-near horizontal pipelines. The proposed model implements new criteria for eliminating discontinuity problems, providing smooth transitions between the different flow patterns. The new model has been initially validated against existing, various, elaborated, laboratory and field databases. Following the validation, the model is tested against a new set of field data, from the North Sea and Prudhoe Bay, Alaska, which includes 86 cases. The proposed model is also compared with six commonly used models and correlations. The model showed outstanding performance for the pressure drop prediction, with a ?1.3% average error, a 5.5% absolute average error and 6.2 standard deviation. The proposed model provides an accurate two-phase flow mechanistic model for research and design for the industry. Introduction Early predictive means for two-phase flow were based on the empirical approach. This was due to both the complex nature of two-phase flow and the need for design methods for industry. The most commonly used correlations have been the Dukler et al.1 and Beggs and Brill2 correlations for flow in pipelines, and the Hagedorn and Brown3 and Ros4/Duns and Ros5 correlations for flow in wellbores. This approach was successful for solving two-phase flow problems for more than 40 years, with an updated performance of ±30% error. However, the empirical approach has never addressed the "why" and "how" problems for two-phase flow phenomena. Also, it is believed that no further or better accuracy can be achieved through this approach. A new approach emerged in the early 1980's, namely, the mechanistic modeling approach. This approach attempts to shed more light on the physical phenomena. The flow mechanisms causing two-phase flow to occur are determined and modeled mathematically. A fundamental postulate in this method is the existence of various flow configurations or flow patterns, including stratified flow, slug flow, annular flow, bubble flow, churn flow and dispersed bubble flow. These flow patterns are shown schematically in Fig. 1. The first objective of this approach is, thus, to predict the existing flow pattern for a given system. Then a separate model is developed for each flow pattern to predict the corresponding hydrodynamics and heat transfer. These models are expected to be more reliable and general because they incorporate the mechanisms and the important parameters of the flow. All current research is conducted through the modeling approach. Application of models in the field is now underway, showing the potential of this method. The mechanistic models developed over the past two decades have been formulated separately for pipelines and wellbores. Following is a brief review of the literature for these two cases. Pipeline Models. These models are applicable for horizontal and near horizontal flow conditions, namely, ±10°. The pioneering and most durable model for flow pattern prediction in pipelines was presented by Taitel and Dukler.6 Other studies have been carried out for the prediction of specific transitions, such as the onset of slug flow,7 or different flow conditions, such as high pressure.8 Separate models have been developed for stratified flow,6,9-11 slug flow,12–14 annular flow15,16 and dispersed bubble flow (the homogeneous no-slip model17). A comprehensive mechanistic model, incorporating a flow pattern prediction model and separate models for the different flow patterns, was presented by Xiao et al.18 for pipeline design. Wellbore Models. These models are applicable mainly for vertical flow but can be applied as an approximation for off-vertical sharply inclined flow 60° ? 90°) also. A flow pattern prediction model was proposed by Taitel et al.19 for vertical flow, which was later extended to sharply inclined flow by Barnea et al.20 Specific models for the prediction of the flow behavior have been developed for bubble flow21,22 slug flow23–25 and annular flow.26,27 Comprehensive mechanistic models for vertical flow have been presented by Ozon et al.,28 by Hasan and Kabir,21 by Ansari et al.29 and by Chokshi et al.30 Unified Models. Attempts have been made in recent years to develop unified models that are applicable for the range of inclination angles between horizontal (0°) and upward vertical (90°) flow. These models are practical since they incorporate the inclination angle. Thus, there is no need to apply different models for the different inclination angles encountered in horizontal, inclined and vertical pipes. A unified flow pattern prediction model was presented by Barnea 31 that is valid for the entire range of inclination angles (?90° ? 90°). Felizola and Shoham32 presented a unified slug flow model applicable to the inclination angle range from horizontal to upward vertical flow. A unified mechanistic model applicable to horizontal, upward and downward flow conditions was presented by Petalas and Aziz,33 which was tested against a large number of laboratory and field data. Recently, Gomez et al.34 presented a unified correlation for the prediction of the liquid holdup in the slug body.