Oil-water Flow Patterns Research Articles

Liquid holdup measurement in horizontal oil–water two-phase flow by using concave capacitance sensor

Due to the complex flow structures of horizontal oil–water flows, the liquid holdup measurement is still a challenging problem. In this paper, we using the finite element analysis build a two-dimensional model of the concave capacitance sensor and investigate the effect of sensor geometry on the distribution of the sensitivity field. Through calculating the sensor static response for different horizontal oil–water flow patterns, we figure out the optimum geometry of the concave capacitance sensor. In addition, we conduct experiment to obtain the measured response of the concave capacitance sensor and achieve the oil-holdup by using quick closing valve. The results indicate that the optimized concave capacitance sensor shows good performance for liquid holdup measurement of horizontal oil–water two-phase flow.

ARTIFICIAL NEURAL NETWORKS IN LIQUID-LIQUID TWO-PHASE FLOW

This research investigates the use of neural networks for identification of oil-water two-phase flow pattern in a horizontal conduit. The investigation seeks to find out if neural networks are useful tools for this application. In order to find a suitable network, all of the various types of networks available are studied and appropriate networks are selected using MATLAB as a computational tool. Four networks are selected for this investigation: feed-forward back propagation (FFBP), radial based function (RBF), probabilistic neural network (PNN), and learning vector quantization (LVQ) Networks. These various networks are created and tested to evaluate the relationships between key variables and performance. Once the networks are optimized, various architectures are compared based on mean square error (MSE), construction time, complexity, and the ability to identify transition regions. PNN is found to be the best network for this particular application, followed by FFBP, RBF, and LVQ. It is observed that making a network larger or more powerful does not necessarily improve the performance. Moreover, doing so causes a network to lose its ability to generalize by eventually “over-fitting” the training data.

Flow pattern identification in oil wells by electromagnetic image logging

Petroleum production logging needs to determine the interpretation models first and flow pattern identification is the foundation, but traditional flow pattern identification methods have some limitations. In this paper, a new method of flow pattern identification in oil wells by electromagnetic image logging is proposed. First, the characteristics of gas-water and oil-water flow patterns in horizontal and vertical wellbores are picked up. Then, the continuous variation of the two phase flow pattern in the vertical and horizontal pipe space is discretized into continuous fluid distribution models in the pipeline section. Second, the electromagnetic flow image measurement responses of all the eight fluid distribution models are simulated and the characteristic vector of each response is analyzed in order to distinguish the fluid distribution models. Third, the time domain changes of the fluid distribution models in the pipeline section are used to identify the flow pattern. Finally, flow simulation experiments using electromagnetic flow image logging are operated and the experimental and simulated data are compared. The results show that the method can be used for flow pattern identification of actual electromagnetic image logging data.

Magnitude and sign correlations in conductance fluctuations of horizontal oil water two-phase flow

In experiment we firstly define five typical horizontal oil-water flow patterns. Then we introduce an approach for analyzing signals by decomposing the original signals increment into magnitude and sign series and exploring their scaling properties. We characterize the nonlinear and linear properties of horizontal oil-water two-phase flow, which relate to magnitude and sign series respectively. We find that the joint distribution of different scaling exponents can effectively identify flow patterns, and the detrended fluctuation analysis (DFA) on magnitude and sign series can represent typical horizontal oil-water two-phase flow dynamics characteristics. The results indicate that the magnitude and sign decomposition method can be a helpful tool for characterizing complex dynamics of horizontal oil-water two-phase flow.

Flow pattern and water holdup measurements of vertical upward oil–water two-phase flow in small diameter pipes

We experimentally investigate vertical upward oil–water two-phase flow in a 20mm inner diameter pipe. We first using vertical multiple electrode array conductance sensor measure the water holdup, and using mini-conductance probes define five observed flow patterns, i.e., very fine dispersed oil-in-water (VFD O/W) flow, dispersed oil-in-water (D O/W) flow, oil-in-water slug (D OS/W) flow, water-in-oil (D W/O) and transition flow (TF). Then we present an experimental flow pattern map with oil and water superficial velocity ranging from 0.258m/s to 3.684m/s and 0.184m/s to 1.474m/s, respectively. In addition, we obtain the flow pattern transition boundaries in terms of water holdup. Finally, we propose an effective quadric time–frequency representation, i.e., the adaptive optimal kernel time–frequency representation (AOK TFR) to investigate the complex behavior underlying vertical upward oil–water flow. In particular, we extract total energy and time–frequency entropy to characterize the evolutions of flow patterns. The results suggest that AOK TFR based method could potentially be a powerful tool for characterizing the dynamical characteristics of different vertical upward water-dominant oil–water flow patterns.

The development of a conductance method for measuring liquid holdup in horizontal oil–water two-phase flows

This paper presents the design and geometry optimization of a ring conductance probe for measuring the conductance of oil–water mixtures in horizontal pipes. Using the finite element method (FEM), we first investigate the sensitivity distribution of the electric field generated by a pair of ring-shaped exciting electrodes, and calculate the static response on the measurement electrodes under horizontal oil–water flow patterns; we then figure out the optimum geometry dimension with minimum deviation from linearity and high spatial resolution. Finally, we carry out the flow loop test in a horizontal oil–water two-phase flow pipe to obtain the measurement response of the ring conductance probe, and conclude some advantages for measuring liquid holdup with the newly designed conductance method.

Geometrical and kinematic properties of interfacial waves in stratified oil–water flow in inclined pipe

The stratified oil–water flow pattern is common in the petroleum industry, especially in offshore directional wells and pipelines. Previous studies have shown that the phenomenon of flow pattern transition in stratified flow can be related to the interfacial wave structure (problem of hydrodynamic instability). The study of the wavy stratified flow pattern requires the characterization of the interfacial wave properties , i.e., average shape, celerity and geometric properties (amplitude and wavelength) as a function of holdup, inclination angle and phases’ relative velocity. However, the data available in the literature on wavy stratified flow is scanty, especially in inclined pipes and when oil is viscous. This paper presents new geometric and kinematic interfacial wave properties as a function of a proposed two-phase Froude number in the wavy-stratified liquid–liquid flow. The experimental work was conducted in a glass test line of 12 m and 0.026 m i.d., oil (density and viscosity of 828 kg/m 3 and 0.3 Pa s at 20 °C, respectively) and water as the working fluids at several inclinations from horizontal (−20°, −10°, 0°, 10°, 20°). The results suggest a physical relation between wave shape and the hydrodynamic stability of the stratified liquid–liquid flow pattern.

Complex network analysis in inclined oil–water two-phase flow

Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling many complex natural and artificial systems. Oil–water two-phase flow is one of the most complex systems. In this paper, we use complex networks to study the inclined oil–water two-phase flow. Two different complex network construction methods are proposed to build two types of networks, i.e. the flow pattern complex network (FPCN) and fluid dynamic complex network (FDCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K-means clustering, useful and interesting results are found which can be used for identifying three inclined oil–water flow patterns. To investigate the dynamic characteristics of the inclined oil–water two-phase flow, we construct 48 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of the inclined oil–water two-phase flow. In this paper, from a new perspective, we not only introduce a complex network theory into the study of the oil–water two-phase flow but also indicate that the complex network may be a powerful tool for exploring nonlinear time series in practice.

Nonlinear dynamic analysis of large diameter inclined oil–water two phase flow pattern

We experimentally investigate the inclined oil–water two phase flow characteristics in 125 mm inner diameter pipe by using the vertical multi-electrode array (VMEA) conductance probe and mini-conductance probes. For the oil and water superficial velocities in the range of 0.0052–0.3306 m/s and inclination angle at 15° and 45° from vertical, we observe the four typical inclined oil–water flow patterns, i.e., Dispersion of oil-in-water-Pseudoslugs, Dispersion oil-in-water-Countercurrent, Transitional Flow and Dispersion of water-in-oil flow pattern. Since the mini-conductance probes are sensitive to local change of flow pattern, with the help of high speed camera, we exactly identify different flow patterns under different flow conditions by analyzing the measured signals. In addition, we also propose the inclined oil–water two phase flow pattern maps for large diameter pipe. Furthermore, we further characterize the flow patterns by applying recurrence quantification analysis and chaotic attractor geometry morphological description to VMEA signals. The results show that the proposed nonlinear analysis method is an effective tool not only for classifying different water-dominated flow patterns but also for characterizing the complex flow structure of inclined oil–water two phase flow system.

Interfacial tension controlled W/O and O/W 2-phase flows in microchannel

In microfluidic systems, interfacial tension plays a predominant role in determining the two-phase flow behavior due to the high surface area to volume ratio. We investigated the influence of both solid-liquid (sigmaSL) and liquid-liquid (sigmaLL) interfacial tensions on water-oil two-phase flows in microfluidic devices. Experimental results show that, unlike macroscopic systems, sigmaSL plays a dominant role, determining the emulsion type created in microchannels: oil-in-water (O/W) flow in hydrophilic microchannels and water-in-oil (W/O) flow in the corresponding hydrophobically treated microchannels. Modification of sigmaLL by surfactants only plays a secondary role. By tuning sigmaLL, oil-water two-phase flow patterns could be changed from droplet-based to stratified flows under constant flow conditions in the same device. In addition, also droplet deformation, coalescence and emulsion inversion could be achieved by tailoring sigmaSL and sigmaLL in microfluidic devices. Microfluidic technology therefore provides a valuable additional tool for quantitatively manipulating and evaluating these phenomena which are difficult to realize in the macroscale devices.

The perimeter measure analysis of chaotic attractor morphology of inclined oil-water two phase flow patterns

In two-dimensional phase space, the attractor morphology parameters of perimeter measures, such as area, lengths of long axis and short axis, are defined, and the variations of these parameters with the delay time are investigated. It was found that the growth rates of the above parameters do not change notably in the first zone during the attractor unfolding process, which is suitable for attractor morphology characterization. The classification effectiveness of this method is verified by applying it to simulating signals, such as sine signal, white noise, mixed signals and Lorenz signals. By the experiment of inclined oil-water two phase flow, the conductance signals were acquired from the vertical multi-electrode array sensor, and the water dominated inclined oil-water flow patterns are analyzed by using the attractor morphology parameters and we found that the growth rate of area is an invariant quantity of attractor morphology, which can give a good classification of dispersion of oil in water-pseudoslugs flow and dispersion of oil in water-countercurrent flow.

Characterization of Oil-Water Flow Patterns in Vertical and Deviated Wells

SummaryAn oil-water flow pattern classification and characterization for wellbores is proposed based on the integrated analysis of experimental data, including frictional pressure drop, holdup, and spatial phase distribution, acquired in a transparent test section (2-in. i.d., 51-ft long) using a refined mineral oil and water (ρo / ρw = 0.85,μ o /μw 20.0, and σo-w = 33.5dyn/cm at 90°F). The tests covered inclination angles of 90°, 75°, 60°, and 45° from horizontal.The oil-water flow patterns have been classified into two major categories given by the status of the continuous phase, including water-dominated flow patterns and oil-dominated flow patterns. It was found that most water-dominated flow patterns show signifi- cant slippage but relatively low frictional pressure gradients. In contrast, all the oil-dominated flow patterns exhibit negligible slippage but significantly larger frictional pressure gradients. Six flow patterns have been characterized in upward vertical flow; three were water dominated and three were oil dominated. In upward inclined flow there were four water-dominated flow patterns, two oil-dominated flow patterns and a transitional flow pattern. Flow-pattern maps for each of the tested inclination angles are presented. A mechanistic model to predict flow-pattern transitions in vertical wells is proposed. The transitions to the very-fine- dispersed flow patterns were evaluated by combining the concepts of turbulent kinetic energy with the surface free energy of the droplets, while the transitions to the churn flow pattern and the phase inversion were predicted based on the concept of agglomeration. The model compares favorably with the measured data.

Investigation of Holdup and Pressure Drop Behavior for Oil-Water Flow in Vertical and Deviated Wells

Two-phase flow of oil and water is commonly observed in wellbores, and its behavior under a wide range of flow conditions and inclination angles constitutes a relevant unresolved issue for the petroleum industry. Among the most significant applications of oil-water flow in wellbores are production optimization, production string selection, production logging interpretation, down-hole metering, and artificial lift design and modeling. In this study, oil-water flow in vertical and inclined pipes has been investigated theoretically and experimentally. The data are acquired in a transparent test section (0.0508 m i.d., 15.3 m long) using a mineral oil and water (ρo/ρw = 0.85, μo/μw = 20.0 & σo−w = 33.5 dyne/cm at 32.22°C). The tests covered inclination angles of 90, 75, 60, and 45 deg from horizontal. The holdup and pressure drop behaviors are strongly affected by oil-water flow patterns and inclination angle. Oil-water flows have been grouped into two major categories based on the status of the continuous phase, including water-dominated and oil-dominated flow patterns. Water-dominated flow patterns generally showed significant slippage, but relatively low frictional pressure gradients. In contrast, oil-dominated flow patterns showed negligible slippage, but significantly large frictional pressure gradients. A new mechanistic model is proposed to predict the water holdup in vertical wellbores based on a drift-flux approach. The drift flux model was found to be adequate to calculate the holdup for high slippage flow patterns. New closure relationships for the two-phase friction factor for oil-dominated and water-dominated flow patterns are also proposed.