Multiphase Flow Parameters Research Articles

CFD-PBM simulations the effect of aeration rates on hydrodynamics characteristics in a gas-liquid-solid aerobic fluidized bed biofilm reactor

A CFD-PBM coupling model was developed to simulate and calculate multiphase flow parameters, flow morphology, and bubble diameter in the aerobic fluidized bed biofilm reactor (AFBBR) under different aeration rates. The simulated radial solid volume fraction values were generally in agreement (within ±15%) with the experimental values. The gas phase predominantly occupied the central area of the reactor, with three distinct velocity peaks observed in the liquid and solid phases. Higher aeration rates improve the mixing of multiple phases by augmenting fluidization velocity, gas-phase volume fraction, eddies size, and turbulence characteristics, thereby leading to a rise in the average size of bubbles from 1.54 mm to 2.03 mm. However, the proportion of small diameter bubbles (0.27–1.03 mm) decreased from 69.4% to 59.6%. These studies concluded that the multiphase flow parameters under an aeration rate of 5.77 m3/(h·m3) were more favorable for improving oxygen mass transfer efficiency and reducing energy consumption.

Modeling of sand transport and elbow erosion in horizontal two-phase slug flow

Horizontal wells play an important role in maximizing the recovery of hydrocarbons from oil and gas reservoirs. During production, if the rate of production of produced fluids with sand particles is low, the deposition of sand particles in horizontal flow lines can wreak havoc on production systems in such a way as to cause increased pressure loss and reduction or loss of production when the pipe is partially or completely blocked. On the other hand, if the production rate of fluids is high, the impact of sand particles on the wall of the pipe will erode the inner surface of the pipe fittings. In this case, erosion can be severe enough to cause a hazardous spill and complete shutdown of systems. Therefore, it is important to quantify the sand transport and erosivity of different flow regimes. Under moderate velocities, there exists a flow regime which is called slug flow which is characterized by the intermittent appearance of liquid slugs propagating through the pipe. Studying the sand deposition and erosion due to sand particles entrained in intermittent flows is extremely difficult since the solid particle velocity magnitudes are coupled with several multiphase flow parameters such as phase distribution and slippage between the phases. This work focuses on the improvement of mechanistic models for predicting critical deposition of sand particles in horizontal pipes and erosion in horizontal-horizontal elbows. In this investigation, a modified model is proposed to better predict the critical deposition velocity and the characteristic particle velocity as a function of the slug flow characteristics. The model predictions are compared with the sand transport and erosion data collected at the University of Tulsa and other research institutions. The results show that the new approach provides improved predictions for sand transport and maximum erosion in standard elbows when compared with existing models.

Mass flow rate measurement of gas-liquid two-phase flow using acoustic-optical-Venturi mutisensors

The measurement of multiphase flow parameters is essential for the online monitoring of industrial production and energy metering. In this paper, a multi-sensor experimental measurement device is designed based on NIR, acoustic emission sensors, and throated Venturi. The measurement information is decomposed using modal decomposition, and the characteristic variables of the gas volume fraction are extracted by flow noise decoupling and light attenuation analysis. A new gas volume fraction model is proposed based on Gradient Boosting Decision Tree (GBDT) through feature-level fusion, and the Mean Absolute Percentage Error (MAPE) of the gas volume fraction prediction models is within 4% for the three flow patterns. A new flow rate model is established based on the Homogeneous and Collins models. Laboratory results indicate that the MAPE of the flow rate model is 1.56%, and 98.61% relative deviations are within ±20% error band. The study provides a new method for online measurement of multiphase fluid motion and a theoretical basis for sensing mechanism and measurement of multiphase flow.

A high-resolution upwind numerical scheme for solving transient multiphase flow in wellbore

The identification of gas-liquid interface is the basis for accurate calculation of wellbore flow parameters after gas invasion, which plays an important role in the safety and reliability of drilling engineering. At present, most petroleum engineering uses a simple difference algorithm to calculate the wellbore multiphase flow, this scheme can not capture the gas-liquid interface accurately, and the numerical accuracy is low. Therefore, this paper proposes a mathematical and numerical calculation model for transient multiphase flow in wellbore during gas invasion. Using second-order Runge-Kutta method and OMUSCL2 method, a high-precision and high-resolution upwind AUSMV numerical scheme is constructed to capture the gas-liquid interface. The research shows that the high-precision and high-resolution upwind AUSMV scheme can accurately capture the gas-liquid interface, and thus accurately solve the multiphase flow parameters in wellbore during the gas invasion.

The impact of bimodal pore size distribution and wettability on relative permeability and capillary pressure in a microporous limestone with uncertainty quantification

Pore-scale X-ray imaging combined with a steady-state flow experiment was used to study the displacement processes during waterflooding in an altered-wettability carbonate, Ketton limestone, with more than two orders of magnitude difference in pore size between macropores and microporosity. We simultaneously characterized macroscopic and local multiphase flow parameters, including relative permeability, capillary pressure, wettability, and fluid occupancy in pores and throats. An accurate method was applied for porosity and fluid saturation measurements using greyscale based differential imaging without image segmentation. The relative permeability values were corrected by considering the measured saturation profile along the sample length to account for the so-called capillary end effect. The behaviour of relative permeability and capillary pressure was compared to other measurements in the literature to demonstrate the combined effects of wettability and pore structure. Typical oil-wet behaviour in resolvable macropores was measured from contact angle, fluid occupancy and curvature. The capillary pressure was negative while the oil relative permeability dropped quickly as oil was drained to low saturation and flowed through connected oil layers. Brine initially largely flowed through water-wet microporosity, and then filled the centre of large oil-wet pore bodies. Thus, the brine relative permeability remained exceptionally low until brine formed a connected flow path in the macropores leading to a substantial increase in relative permeability. Overall, this work demonstrates that not only wettability but also pore size distribution and microporosity have significant impact on displacement processes.

Physics-informed multi-fidelity learning-driven imaging method for electrical capacitance tomography

The electrical capacitance tomography is considered to be a promising non-invasive visualization method for the measurement of multiphase flow parameters, but low-quality tomograms limit the reliability and accuracy of measurements. In order to overcome this limitation and bottleneck, the physics-informed data-dependent prior learned from the given samples is introduced and coupled with the measurement mechanism and the domain knowledge modeled by a new L1/L2 norm-based regularizer into a new optimization imaging model in this study. To improve the convergence and reduce the computational load, the built imaging model is solved by a new numerical scheme driven by the split Bregman method and the forward–backward splitting method. A new physics-informed robust sparse extreme learning machine method that not only obeys the measurement mechanism in training but also promotes the robustness and performance of the model is proposed and used to build a novel multi-fidelity learning method to infer the physics-informed data-dependent prior. The new imaging method achieves multi-source data fusion, leads to new changes in reconstruction algorithms, increases the complementarity and diversity of image priors, unifies the image reconstruction and multi-fidelity learning method, and improves robustness, numerical stability and flexibility of the model. The reconstruction results show that the new imaging method achieves more accurate reconstruction with reduced sensitivity to noise compared to important and popular imaging methods. This study leads to new changes in imaging algorithms and mining and use of image priors, and serves as a catalyst for the paradigm shift in image reconstruction.

Effects of Enzymatically Induced Carbonate Precipitation on Capillary Pressure–Saturation Relations

Leakage mitigation methods are an important part of reservoir engineering and subsurface fluid storage, in particular. In the context of multi-phase systems of subsurface storage, e.g., subsurface CO2 storage, a reduction in the intrinsic permeability is not the only parameter to influence the potential flow or leakage; multi-phase flow parameters, such as relative permeability and capillary pressure, are key parameters that are likely to be influenced by pore-space reduction due to leakage mitigation methods, such as induced precipitation. In this study, we investigate the effects of enzymatically induced carbonate precipitation on capillary pressure–saturation relations as the first step in accounting for the effects of induced precipitation on multi-phase flow parameters. This is, to our knowledge, the first exploration of the effect of enzymatically induced carbonate precipitation on capillary pressure–saturation relations thus far. First, pore-scale resolved microfluidic experiments in 2D glass cells and 3D sintered glass-bead columns were conducted, and the change in the pore geometry was observed by light microscopy and micro X-ray computed tomography, respectively. Second, the effects of the geometric change on the capillary pressure–saturation curves were evaluated by numerical drainage experiments using pore-network modeling on the pore networks extracted from the observed geometries. Finally, parameters of both the Brooks–Corey and Van Genuchten relations were fitted to the capillary pressure–saturation curves determined by pore-network modeling and compared with the reduction in porosity as an average measure of the pore geometry’s change due to induced precipitation. The capillary pressures increased with increasing precipitation and reduced porosity. For the 2D setups, the change in the parameters of the capillary pressure–saturation relation was parameterized. However, for more realistic initial geometries of the 3D samples, while the general patterns of increasing capillary pressure may be observed, such a parameterization was not possible using only porosity or porosity reduction, likely due to the much higher variability in the pore-scale distribution of the precipitates between the experiments. Likely, additional parameters other than porosity will need to be considered to accurately describe the effects of induced carbonate precipitation on the capillary pressure–saturation relation of porous media.

Wellbore drift flow relation suitable for full flow pattern domain and full dip range

Aiming at the simulation of multi-phase flow in the wellbore during the processes of gas kick and well killing of complex-structure wells (e.g., directional wells, extended reach wells, etc.), a database including 3561 groups of experimental data from 32 different data sources is established. Considering the effects of fluid viscosity, pipe size, interfacial tension, fluid density, pipe inclination and other factors on multi-phase flow parameters, a new gas-liquid two-phase drift flow relation suitable for the full flow pattern and full dip range is established. The distribution coefficient and gas drift velocity models with a pipe inclination range of −90°–90° are established by means of theoretical analysis and data-driven. Compared with three existing models, the proposed models have the highest prediction accuracy and most stable performance. Using a well killing case with the backpressure method in the field, the applicability of the proposed model under the flow conditions with a pipe inclination range of −90°–80° is verified. The errors of the calculated shut in casing pressure, initial back casing pressure and casing pressure when adjusting the displacement are 2.58%, 3.43%, 5.35%, respectively. The calculated results of the model are in good agreement with the field backpressure data.

The Effect of Pore-Scale Two-Phase Flow on Mineral Reaction Rates

In various natural and engineered systems, mineral–fluid interactions take place in the presence of multiple fluid phases. While there is evidence that the interplay between multiphase flow processes and reactions controls the evolution of these systems, investigation of the dynamics that shape this interplay at the pore scale has received little attention. Specifically, continuum scale models rarely consider the effect of multiphase flow parameters on mineral reaction rates or apply simple corrections as a function of the reactive surface area or saturation of the aqueous phase, without developing a mechanistic understanding of the pore-scale dynamics. In this study, we developed a framework that couples the two-phase flow simulator of OpenFOAM (open field operation and manipulation) with the geochemical reaction capability of CrunchTope to examine pore-scale dynamics of two phase flow and their impacts on mineral reaction rates. For our investigations, flat 2D channels and single sine wave channels were used to represent smooth and rough geometries. Calcite dissolution in these channels was quantified with single phase flow and two phase flow at a range of velocities. We observed that the bulk calcite dissolution rates were not only affected by the loss of reactive surface area as it becomes occupied by the non-reactive non-aqueous phase, but also largely influenced by the changes in local velocity profiles, e.g., recirculation zones, due to the presence of the non-aqueous phase. The extent of the changes in reaction rates in the two-phase systems compared to the corresponding single phase system is dependent on the flow rate (i.e., capillary number) and channel geometry, and follows a non-monotonic relationship with respect to aqueous saturation. The pore-scale simulation results highlight the importance of interfacial dynamics in controlling mineral reactions and can be used to better constrain reaction rate descriptions in multiphase continuum scale models. These results also emphasize the need for experimental studies that underpin the development of mechanistic models for multiphase flow in reactive systems.

Prediction of porous media fluid flow using physics informed neural networks

Due to the explosion of the digital age of data, deep learning applications for different physical sciences have gained momentum. In this paper, we implement a physics informed neural network (PINN) technique that incorporates information from the fluid flow physics as well as observed data to model the Buckley-Leverett problem. The classical problem of drainage of gas into a water-filled porous medium is used to validate our implementation. Several cases are tested that signify the importance of the coupling between observed data and physics-informed neural networks for different parameter space. Our results indicate that PINNs are capable of capturing the overall trend of the solution even without observed data but the resolution and accuracy of the solution are improved tremendously with observed data. Adding a small amount of diffusion to the PDE-constrained loss function improved the solution slightly only when observed data were used. Moreover, the PINN is used to solve the inverse problem and infer the most optimal multiphase flow parameters. The performance of the PINN is compared to that of an artificial neural network (ANN) without any physics. We show that the ANN performs comparably well to the PINN when the observed data used to train the ANN include times that span the early- and late-time behavior. As opposed to the PINN, the ANN is not able to predict the solution when only early-time saturation profiles are provided as observed data and extrapolation are needed.

Steady-State Gas Flow from Tight Shale Matrix Subject to Water Blocking

Summary This work studies 1D steady-state flow of gas from compressible shale matrix subject to water blocking toward a neighboring fracture. Water blocking is a capillary end effect causing wetting phase (e.g., water) to accumulate near the transition from matrix to fracture. Hydraulic fracturing is essential for economical shale gas production. Water is frequently used as fracturing fluid, but its accumulation in the matrix can reduce gas mobility and production rate. Gas transport is considered at a defined pressure drop. The model accounts for apparent permeability (slip), compressibility of gas and shale, permeability reduction, saturation tortuosity (reduced relative permeability upon compaction), and multiphase flow parameters like relative permeability and capillary pressure, which depend on wettability. The behavior of gas flow rate and distributions of gas saturation, pressure, and permeability subject to different conditions and the stated mechanisms is explored. Water blockage reduces gas relative permeability over a large zone and reduces the gas flow rate. Despite gas flowing, strong capillary forces sustain mobile water over the entire system. Reducing drawdown gave lower driving force and higher resistance (by water blockage) for gas flow. The results show that 75% reduction of drawdown made the gas flow rate a couple orders of magnitude lower compared to if there was no blockage. The impact was most severe in more water-wet systems. The blockage caused most of the pressure drop to occur near the outlet. High pressure in the rest of the system reduced effects from gas decompression, matrix compression, and slip-enhanced permeability, whereas rapid gradients in all these effects occurred near the outlet. Gas decompression resulted in an approximately 10 times higher Darcy velocity and pressure gradient near the outlet compared to inlet, which contributed to removing blockage, but the added resistance reduced the gas production rate. Similarly, higher gas Corey exponent associated gas flow with higher pressure drop. The result was less blockage but lower gas production. Slip increased permeability, especially toward the outlet, and contributed to increase in gas production by 16%. Significant matrix compression was associated with permeability reduction and increased Corey exponent in some examples. These effects reduced production and shifted more of the pressure drop toward the outlet. Upstream pressure was more uniform, and less compression and permeability reduction were seen overall compared to a system without water blockage.

Quantitative analysis of the influence of capillary pressure on geologic carbon storage forecasts case study: CO2-EOR in the Anadarko basin, Texas

Numerical models are a critical tool for forecasting subsurface multiphase flow associated with geologic carbon storage. The uncertainty of model results stems from many factors, including uncertainty in multiphase flow parameters. Specifically, relative permeability and capillary pressure relationships depend on both the rock properties and fluid properties, and the latter may be highly nonlinear as fluid temperature, and pressure conditions change. Forecasts of trapping mechanisms, phase behavior, and plume movement are impacted by choice of relative permeability and capillary pressure functions and how those functions are calibrated and constrained. In particular, one of the most neglected aspects of such simulations is meaningful capillary pressure processes. A primary goal of this study is to quantify the difference in forecasts for models that utilize capillary pressure functions calibrated with measured data from the results of models without such. Additionally, the relative permeability models developed here were derived from measured capillary pressure data. Those data were used to constrain saturation endpoints in the relative permeability curves and dictate how that relative permeability was distributed spatially. The main conclusions drawn from this analysis include (1) heterogeneity in relative permeability plays a significant role in simulated forecasts of CO2 migration, trapping mechanisms and storage capacity, as well as oil and water production, and (2) capillary pressure, and in particular, the magnitude of capillarity also plays a significant role in these processes. Conversely, if the magnitude of capillarity is small relative to in situ fluid pressures, it imparts insignificant effects on these processes.

A mechanistic model for predicting erosion in churn flow

Sand particles, which are regularly entrained with the production fluids while transporting from a reservoir to surface facilities, can cause severe erosion and erosion-corrosion damage to production equipment. A crucial parameter for studying erosion in multiphase flows is the flow pattern. The particle motion characteristics will change drastically with changes in the flow pattern in the pipelines. In vertical upward gas-liquid flow, a widely accepted flow pattern classification is bubble, slug, churn and annular flow. Churn flow is a chaotic flow pattern consisting of Taylor bubbles and liquid slugs that are distorted in shape and it is characterized by the presence of periodic large interfacial waves called flooding-type waves. Studying the erosion due to sand particles entrained in churn flows is extremely difficult, since the solid particle erosion magnitudes are coupled with several multiphase flow parameters such as phase distribution and velocities. This work focuses on improvement of a multiphase churn flow erosion model for elbows in vertical pipes. In this investigation, a drift-flux model is proposed to better predict the flow behavior and the characteristic initial particle velocity for churn gas-liquid flow. Based on the drift-flux model, the actual gas velocity is calculated as a function of mixture and drift velocities. The coefficients of the drift flux expression under churn flow conditions are determined from datasets available in literature. The model predictions are compared with the erosion data bank at the Erosion/Corrosion Research Center and other published papers. The data comprises effects of pipe diameter, particle characteristics, flow velocities, and liquid viscosity. The results show that the new approach provides much better predictions for the maximum erosion in bends when compared with the original mixture based model and other models available in literature.

Diagnostic and prognostic development of a mechanistic model for multiphase flow in oil-gas pipelines

A mechanistic model has been applied to predict corrosion rate in multiphase (water–oil-gas) flow regimes. It is applied due to the inadequacies of existing models to adequately address a wide variety of corrosion-dependent parameters with special emphasis on multiphase flow parameters. This model considers water cut, volumetric phase fraction of oil and gas, temperature, pressure, and other data collected relating to the pipe age, sand particle deposit, CO2 partial pressure, flow velocity, pH, chloride contents, mass transfer coefficients, and hydrogen sulfide. The applied model results show well above 91 percent prediction accuracy, while the prediction error ranges between 0.022 and 0.045 percent. When predicted results compared actual value (experimental data) with DeWaard and Milliams’ model; used in the oil and gas industries, it showed good agreement. It is seen that the resulting model produced an R2 value of 0.91 in comparison to 0.53, the value for Dewaard and Milliams’. It is obvious from the numerical simulation that the multiphase flow parameters have major effects on the entire rate of corrosion of oil and gas multiphase flow pipelines. Finally, this research concluded by showing the developed model performance, and a comparison was made with numerical results. It is expected that the outcome of this research will be of significant help in strengthening the application of mechanistic models for predicting corrosion rates. This model will be useful for oil and gas industries worldwide for accurate corrosion rate prediction.

Observations of the Impact of MM-Cm Scale Lamination on the Migration and Trapping of CO <sub>2</sub> in Reservoir Rocks

Small scale (mm-cm scale) capillary heterogeneity can result in capillary induced flows and trapping. This can have significant impact on the migration of the injected CO2. In this research, we have measured and characterized the impact of small scale lamination on multiphase-flow parameters and residual trapping of CO2 by combining experimental, numerical, and analytical methods. Experimental CO2/water core-flood tests were performed at reservoir conditions on a laminated reservoir rock core. A medical X-ray CT scanner was used for visualization. Effective drainage and imbibition relative permeability, effective drainage capillary pressure, and residually trapped CO2 were measured. The experimental results were used to obtain a model of the rock core using the method described in. The layers of the rock core are tilted and truncated at the inlet, outlet, and radial outer boundary of the core. To correct for this, the layers were shifted, such that the layers became parallel to the flow direction and extended in the lateral direction. The model of the rock core was used to simulate the drainage core-flood test for a range of flow-rates and flow-rate dependent effective relative permeability and capillary pressure were derived. In addition, simplified analytical models were used to obtain these drainage parameters, as well as capillary limit imbibition effective relative permeability and capillary pressure. The results indicate that simplified analytical models can give a good approximation of these effective multi-phase flow parameters. Furthermore, they show that to correctly derive effective multi-phase flow parameters for layered systems, the geology of the system has to be taken into account. Experimental measurements on rock cores with artificially truncated layers can lead to the incorrect inclusion of the impact small scale heterogeneity.

About Identifiability of Oil and Water Relative Permeability Curves and Reservoir Heterogeneity through Integrated Well Test Study

Relative permeabilities (RP) play an important role in reservoir engineering. RP functions together with the permeability anisotropy coefficient predetermine waterflooding efficiency and oil/water ratio in production forecast. Traditionally multiphase flow parameters are estimated from core analysis data. But such measurements suffer from small representative elementary volume (REV) and limited characterization of reservoir properties. Therefore using core data in 3D reservoir modelling could lead to distorted description of actual flow conditions. Despite those functions (RP) could be history matched with assimilated production data, such a procedure would require long history of waterflooding. So the authors’ idea is to apply integrated well test study to estimate the displacement efficiency and/or relative permeability functions at downhole conditions. Well testing is traditionally applied in reservoir engineering for single-phase reservoir parameters estimation. Our approach is extended to multi-phase flow and is based on data collection at well bottomholes and subsequent data assimilation in flow model.In this paper we summarize both features of mathematical problem statement and identifiability of multiphase parameters through inverse problem solution, but also discuss 10+ -year experience in interpretation of two-phase well testing using our technologies. To estimate multiphase parameters, we have to jointly consider complex data of well logging and dynamic data of well testing. Both data sets are used in the inverse problem quality criteria, where the least squares method has been applied. Forward problem corresponds to a 3D multiphase fluid flow model in porous media. The latter consists of continuity equation with multiphase Darcy equation instead of moment balances. For data assimilation modern methods of optimal control theory were successfully applied. For all synthetic test cases real reservoir parameters were accurately recovered through the use of forward simulation data.In order to estimate reservoir heterogeneity, we applied a single-phase model to get the ratio of vertical to horizontal permeability. Data of well self-interference testing were used for vertical permeability estimation. Depending on the depth of reservoir pressure perturbation, reservoir properties could be properly inferred from observations. Two other options of 3D interference testing using vertical and horizontal wells are also presented.In other words, all the problems considered are identifiable, and the level of their correctness is completely predetermined by the amount and quality of observed data. And transition to digital (intelligent) oil-and-gas production and closed-loop reservoir management [1] provides a possibility to remove discussed restrictions and all inverse problems considered should be accounted as fully identifiable.

Computational Fluid Dynamics (CFD) for Modelling Multiphase Flow in Hilly-Terrain Pipelines

The design and operation of subsea pipelines over the life-cycle of an asset is vital for continuous oil and gas production. Qualitative design and effective production operation of pipelines depend on fluid type(s) involved in the flow; and in the case of multiphase flow, the need to understand the behaviour of the fluids becomes more imperative. This work presented in this report is borne out of the need for more accurate ways of predicting multiphase flow parameters in subsea pipelines with hilly-terrain profiles by better understanding their flow behaviors. To this end, Computational Fluid Dynamics has been used as against existing experimental and mechanistic methods which have inherent shortcomings. The results showed that multiphase flow parameters including flow-regimes, liquid hold-up and pressure drop in hilly-terrain pipelines can be modelled without associated errors in existing techniques. Similarity in trend was found when results of pressure gradient in downward-incline pipe were compared with results from existing correlations and mechanistic method. CFD can be used as a design tool and also a research tool into the understanding of the complexities of multiphase flow in hilly-terrain pipelines towards qualitative design and effective operation of hilly-terrain pipelines.

Shape Memory Alloy-Based Sensor for Two-Phase Flow Detection

In contemporary times, Shape Memory Alloys (SMAs) are ubiquitously used as actuators due to their ability to achieve pre-deformed shape upon heating, thus creating a plethora of applications in active shape and vibration control domains. However, use of SMA material as sensing elements need definite exploration. In this study, a novel application of the Nickel Titanium Naval Ordnance Laboratory - NITiNOL based SMA wire sensor (Flexinol NiTi, $100~\mu m$ diameter), to determine two-phase flow characteristics in a gas-liquid Taylor bubble flow is demonstrated, using the principle of significant change in its electrical resistance during its solid-phase transformation (austenite-martensite) which occurs when the heated SMA wire experiences an intermittent flow of gas and liquid over it. Determination of multi-phase (gas or vapour dispersed in liquid) flow parameters such as constituent phase distribution, local velocities and bubble frequency is exhibited. Design challenges include the matching of convective thermal transient time scales with those of the sensor with available control parameters. A preliminary design methodology is outlined and validated. The limitations of this type of sensor platform is also delineated for improving prospects.

An Electrical and Ultrasonic Doppler System for Industrial Multiphase Flow Measurement

Accurate measurement of flow parameters of multiphase flow has great significance for safe, economic, and efficient operation of the industrial production process. To simultaneously measure the water holdup and velocity, a combined electrical and ultrasonic Doppler measurement system based on a compact peripheral component interconnect (CPCI) bus is designed. The combined sensor consists of a six-ring conductance sensor, two pairs of capacitance plate sensors, and an ultrasonic Doppler sensor. The measurement system is cored with a field-programmable gate array (FPGA) and consists of a series of functional modules. Through flexible programming and interboard communication, the system can meet different measurement requirements. To meet industrial data transmission standards and increase system extensibility, the demodulated data are transmitted to a host computer through the CPCI bus for further data analysis. Dynamic experiments demonstrated that the multimodal system has stable and preferable performance in water holdup and velocity measurement under all flow patterns. The conductance and capacitance sensor could realize the water holdup measurement with the root-mean-square error (RMSE) of 3.02% and the overall superficial velocity estimation through cross correlation with the RMSE of 0.09 m/s. Besides, the pulse ultrasonic Doppler transducer could measure the overall superficial velocity through the area integration of the velocity profile with the RMSE of 0.08 m/s.

An assessment of gas void fraction prediction models in highly viscous liquid and gas two-phase vertical flows

Gas void fraction plays a significant role in determination of several multiphase flow parameters. Good insight of its behaviour coupled with accurate prediction is imperative for design of efficient equipment which has the potential to translate to higher production rates in the petroleum industry. Against the background of the prevalence of higher viscous and imminent application of highly viscous liquids in the petroleum industry, air-water and air-low viscous liquid mixtures dominate gas void fraction research in vertical pipes. In this work, gas-liquid (μl=100−7000mPas) mixtures are used to investigate the behaviour of gas void fraction in vertical pipes. The influence of superficial phase velocities and liquid viscosity are observed. Further, a combined database consisting of experimental and the reported data of Schmidt et al. (2008) is employed to evaluate the predictions of 100 existing correlations. The results indicate that the Hibiki and Ishii (2003) and Bestion (1990) correlations are the overall best and second-best performing correlations. In the absence good performing correlations for churn and annular flows, two correlations each, based on drift flux and slip ratio, are developed respectively. Predictions from these correlations show good agreement with the database and comparable performance with the overall best correlations.