Oil-water Flow Research Articles

The impact of 180° return bend inclination on pressure drop characteristics and phase distribution during oil-water flow

The present work aims to capture the influence of the inclination of the return bend on flow patterns and pressure drop during oil-water flow. The experiments were carried out for different inclinations (0°, 15°, 30°, and 45°) of return bend for various superficial velocity combinations of oil (kerosene) and water ranging from 0.07 to 0.66 m/s. The experiments showed that pressure drop increases with the increase in inclination. However, the pressure drop at a fixed inclination (say 15°) decreases with the increase in the superficial velocity of the water. Distinct flow patterns observed in the return bend were droplet flow, film inversion, slug flow, plug flow and large slug flow. Droplet flow dominates at the lower range of kerosene (i.e., Usk = 0.07–0.2 m/s) and higher range of water superficial velocity (i.e., Usw = 0.40–0.66 m/s) at all the inclinations considered in this study. Additionally, comparisons between the experimental and numerical simulation results were made. The numerical solution utilized the Euler-Euler approach, considering the different phases as interpenetrating continua. The Volume of Fluid (VOF) model was used within this approach, monitoring the volume fraction of each phase over the domain while calculating one set of momentum equations for each phase. To capture the turbulent effects accurately, the k-ε turbulence model was incorporated. It happened to be found that the numerical findings showed remarkable agreement with the experimental data.

Numerical Simulation of Oil-Water Two-Phase Flow in Low Permeability Tight Reservoirs Based on Weighted Least Squares Meshless Method

Numerical Simulation of Oil-Water Two-Phase Flow in Low Permeability Tight Reservoirs Based on Weighted Least Squares Meshless Method

Pore-scale investigation on the effect of capillary barrier on two-phase displacement in dual-structure porous media

Although immiscible fluid–fluid displacement in porous media has received extensive attention, understanding the dynamics behavior within complex structures remains elusive. This study utilizes the direct numerical simulation by solving the Navier–Stokes equations and coupling with the volume of fluid method to examine oil–water flow in porous media across various contact angles θ and capillary number Ca. Three kinds of artificial porous media were generated with designed opening angle β, including single-structure and dual-structure models. A theoretical analysis of the capillary barrier phenomenon, as well as its occurrence conditions, is identified under water-wet conditions. Generally, when θ + β < 90°, the capillary force consistently drives oil displacement from throats to pores. Conversely, if θ + β > 90°, the direction of the capillary force can move toward the water phase side and prevent the fluid interface from continuing to move. For a single-structure porous medium, the dynamics behavior of fluids is controlled by the capillarity, wettability, and geometric structures. The greatest efficiency occurs when the condition θ + β = 90° is met, particularly at an intermediate Ca. For a dual-structure porous medium with smaller opening angles inside, the water phase tends to infiltrate the embedded pore structure due to weaker capillary barrier effects. Conversely, larger opening angles within the embedded structure lead to stronger capillary barrier effects, hindering water entry into the interior porous medium. This obstruction forces the water phase to bypass and traverse longer flow paths, resulting in the formation of a large amount of residual oil.

The flooding mechanism and oil recovery of nanoemulsion on the fractured/non-fractured tight sandstone based on online LF-NMR experiments

Hydraulic fracturing and water/nanoemulsion flooding technology are effective stimulation measures for tight oil production. The complex pore structure of ultra-low permeability sandstone greatly affects oil recovery. At present, scholars have done a lot of research on the characteristics of oil-water flow in micro-nano pores of ultra-low permeability sandstone reservoirs. However, few scholars have comprehensively studied the whole process of ultra-low permeability sandstone reservoirs from hydraulic fracturing to enhanced oil recovery. In this paper, the whole process from fracturing to production of ultra-low permeability sandstone reservoirs is comprehensively studied at the laboratory scale by combining triaxial fracturing, CT scanning, online LF-NMR and other technologies, aiming to promote the understanding of tight oil development. The results show that the high confining pressure (45 MPa) inhibits the propagation of fractures in the rock samples more than the low confining pressure (15 MPa) during the triaxial fracturing process. The oil recovery of the rock sample with high fracture volume (1213.42 mm3) is 16.32 % higher than that of the rock sample with low fracture volume (674.22 mm3). Whether it is fractured rock or non-fractured rock, nanoemulsion can further improve the oil recovery of micropores on the basis of water flooding, with a maximum increase of 28.21 %. The oil recovery of the nanoemulsion with a concentration of 0.3 wt% was 25.34 % higher than that of the nanoemulsion with a concentration of 0.05 wt%. Confining pressure conditions have an important impact on oil recovery. The oil recovery of non-fractured rock samples with initial confining pressure of 5 MPa is 8.15 % lower than that of non-fractured rock samples with initial confining pressure of 30 MPa. At the same time, we propose a new T1-T2 map region division scheme based on sandstone to better characterize oil displacement behavior at the pore scale. The research results can guide the exploitation of ultra-low permeability sandstone reservoirs.

Effect of flow patterns and velocity field on oil-water two-phase flow rate in horizontal wells

In a wellbore, any change in flow rate will result in a change in flow pattern and velocity. The flow pattern and velocity are the key parameters that determine the pressure gradient and liquid holdup. To study the effect of the flow pattern and velocity field on the flow rate of oil-water flow in horizontal wells, we apply the commercial software package ANSYS Fluent 2020 R2 to predict the flow patterns, water holdups, pressure gradients, flow rates, and velocity fields of horizontal wells. Trallero’s flow pattern chart and existing experimental data are used to verify the reliability of the model. We develop a simplified mathematical model of water holdup and compare it with existing models. This mathematical model may be limited to the range of fluid properties in the simulated method. The water holdup of the numerical simulation has a definite correlation with the experimental data. By comparing the numerical simulation results of the Nicolas model, the relationship between the slip velocity and water holdup is verified, and the reliability of the simulation results is verified. The simulation results demonstrate that the change in flow pattern is highly sensitive to the change in flow rate. When the flow pattern is stratified flow, the relative error of the simulated flow is small. When the flow pattern is dispersed flow, the relative error of the simulated flow is slightly larger. The oil is mainly concentrated in the high-velocity core area. At a higher total mixing velocity, the flow pattern is that of dispersed flow, with one phase uniformly mixed in the other phase. The simulation results have good qualitative and quantitative agreement with the experimental results.

Two-phase imbibition of water-oil displacement in silica nanochannels

Classical imbibition theory cannot describe imbibition flow dynamics in nanoporous media in tight reservoirs and other industrial applications. In this work, the two-phase imbibition flow of water-oil displacement in silica nanochannels is studied by using molecular dynamics simulations. Interestingly, it is found that the two-phase imbibition length is shown to increase linearly with increasing time, which is inconsistent with the variation of single-phase imbibition length. The imbibition rate increases with the increase of external driving force, and the large channel height can accelerate the two-phase imbibition flow. As the increase of chain length of alkane molecules, the imbibition rate reduces gradually. The more oil-wet the silica surface is, the slower the imbibition rate is. Furthermore, we derive a theoretical model to describe the two-phase imbibition flow of water-oil displacement in nanochannels by considering the static force equilibrium of external driving forces, capillary forces, and viscous forces of the water and oil phases. The theoretical model can well describe the two-phase imbibition flow under various conditions using the pre-calculated oil-water interfacial tension, the viscosity of fluids, and the three-phase contact angle. This study will enrich the theoretical understanding of oil-water two-phase flow at nanoscale.

Experimental study of viscous oil-water core-annular flow in horizontal pipe

Transporting viscous oils through pipelines is usually challenging due to their very high viscosity. Significant friction reduction in the transportation of viscous oils through pipelines using an ecologically friendly way is the most appealing feature of the core annular Flow (CAF) technique. An experimental study has been conducted to investigate the flow patterns and pressure gradient of viscous oil-water two-phase flow in a horizontal acrylic pipe with a 50 mm inner diameter. The test section was equipped with a fluid lubrication injector element to artificially provide CAF. The pressure gradient measurements were focused on the CAF pattern. The prediction models of the CAF pressure gradient were reviewed and evaluated. An empirical prediction model of CAF pressure gradient was developed, relying on both the present and previously published experimental results. The flow patterns were classified into five patterns. It was observed that the CAF occupied a large region in the constructed flow pattern map and its frictional pressure gradient closely resembles that of water flowing alone. It was found that the developed empirical model provided quite good predictions of the experimental pressure gradients and significantly outperformed the original model. The reviewed prediction models in this area for CAF either overpredicted or underpredicted the experimental pressure gradients. Some of these models considered the extensive effect of viscous oil adhered to the inner wall of the pipe, while others neglected the effect entirely.

Impact of interfacial tension on oil-water flow in a narrow gap

Numerous researchers have examined the co-current flow of oil-water and aqueous solutions containing polymers and surfactants in thin gaps for oil recovery. While some have focused on charges and forces at the interfaces of oil-surfactant solutions during flow. The study of flow structures, interface behavior, and relative permeabilities of oil and aqueous phases of surfactant flow through thin gaps has been less explored. For the first time, this research aims to comprehensively investigate the flow of oil-water and oil-surfactant solutions through a thin gap (Hele-Shaw cell) with a particular focus on the impact of sodium dodecyl sulfate (SDS). The experiments reveal that SDS forms an emulsion near the oil-water interface, capturing oil droplets and enabling their flow along with the SDS solution. Microscopic studies confirm this, showing that when SDS contacts oil, it creates channels through the oil phase, leading to the accumulation and division of oil into small round-shaped droplets, resulting in an oil-in-water emulsion. The addition of SDS to the injecting water significantly enhances relative permeabilities, leading to a remarkable 90% increase in oil recovery from the cell. The research suggests that the optimal SDS concentration range for maximum oil recovery is between 1.5 and 2 wt%, as it achieves the minimum interfacial tension between oil and water.

Oil-Water Flowing Experiments and Water-Cut Range Classification Approach Using Distributed Acoustic Sensing

Summary The accurate measurement of dynamic water cut is of great interest for analyzing reservoir performance and optimizing oilwell production. Downhole water-cut measurement is a very challenging work. Moreover, the surface-measured water cut is a comprehensive indicator of commingled producing well and it is difficult to use this parameter to deduce the downhole water cut of each contributing layer. In this paper, we propose to use distributed fiber-optic acoustic sensing (DAS) technology for the classification of water-cut range. DAS can dynamically monitor the entire wellbore by “listening” to the acoustic signals during flow. A large number of laboratory experimental data from DAS have been collected and analyzed using wavelet time scattering transform and short-time Fourier transform (STFT). The extracted low-variance scattering feature, short time-frequency feature, and fusion feature (combination of two extracted features) were learned with backpropagation (BP) neural network, decision tree (DT), and random forest (RF) algorithm. Then, a classification method of water-cut range in oil-water flow was established with machine learning. Field DAS data were collected from two oil wells to verify the effectiveness of the proposed method. The classification accuracies for the vertical well (Well A) are 92.4% and 87.4% by DT and RF model, respectively. For the horizontal well (Well B), the average classification accuracy exceeds 90% for all three methods. Water shutoff measure was conducted in Well B, and an obvious water decrease was realized. The result shows that the fusion feature overweighs single feature in machine learning with DAS data. This study provides a novel way to identify downhole water-cut range and detect water entry location in horizontal, vertical, and deviated oil-producing wells.

Numerical Simulation of Oil-water Two-phase Flow Interface Tracking

The insulation performance of transformer oil has a great connection with the stable operation of power systems, and transformer oil will inevitably be mixed with water and other impurities in the actual operation. To explore the mechanism of the influence of suspended water droplets on the insulation performance of transformer oil, this paper uses the phase field method to simulate the interaction and phase transition process between oil and water phases in motion. They systematically analyse the influence of electric field and oil flow parameters on the deformation and coalescence of water droplets. The results indicate that droplets in the oil channel will deform along the direction of the electric field, and the degree of deformation gradually increases with the increase of the electric field strength. The electric field strength has an important impact on the degree of deformation of droplets in the oil channel. In addition, under the same electric field intensity, the radius of droplets is an important factor that leads to the length of aggregation time of droplets. Research has found that the aggregation time between droplets becomes shorter as the radius gradually increases.

New Measurement Method of Oil-Water Two-Phase Flow with High Water Holdup and Low Rate by Phase State Regulation

Abstract Flow rate and holdup are two essential parameters to describe oil-water two-phase flow. The distribution of oil-water two-phase flow in the pipeline is very uneven, and there is a significant slippage between the phases. This makes it difficult to measure these two flow parameters. In this paper, a new measurement method of flow rate and holdup based on phase state regulation is proposed. The oil-water two-phase flow is adjusted to oil or water single-phase flow according to the time sequence by the phase state regulation, and the oil-water phase interface is measured with a conductance sensor. A wavelet transform based phase inflection point detection model is proposed to detect the oil-water phase change point. The experimental results show that the maximum measurement error of the flow rate of water is 3.73%, the maximum measurement error of the flow rate of oil is 3.68%, and the flow rate measurement repeatability is 0.0002. The accuracy of the measurement holdup is better than 3.23%, and the repeatability of the measurement holdup is 0.0003. The prototype designed based on this method has two advantages. One is that it is small in size, the other is that it does not depend on the accuracy of the sensor. Therefore, it can be widely used in oilfield ground measurement.

Seepage Simulation of Conglomerate Reservoir Based on Digital Core: A Case Study of the Baikouquan Formation in Mahu Sag, Junggar Basin

Pore structure and flow characteristics are key factors affecting oil recovery rates in heterogeneous tight conglomerate reservoirs. Using micron computed tomography (CT) and modular automated processing system (MAPS) techniques, the pore structure of downhole core samples taken from Mahu’s tight conglomerate reservoirs was analyzed in detail, and a two-scale digital core pore network model with both a wide field of view and high resolution was constructed based on these pore structure data; the digital pore model was corrected according to the mercury intrusion pore size distribution date. Finally, we simulated flow characteristics within the digital model and compared the calculated permeability with the indoor permeability test date to verify the dependability of the pore network. The results indicated that the pore–throat of the conglomerate reservoir in Mahu was widely distributed and exhibited significant bimodal characteristics, with main throat channels ranging from 0.5 to 4 μm. The pore structure showed pronounced microscopic heterogeneity and intricate modalities, mainly consisting of dissolved pores, intergranular pores, and microfractures. These pores were primarily strip-like, isolated, and played a more crucial role in enhancing pore connectivity rather than contributing to the overall porosity. The matrix pores depicted by the MAPS were relatively smaller in size and more abundant in number, with no individual pore type forming a functional seepage channel. The permeability parameters obtained from the two-scale coarse-fine coupled pore network aligned with the laboratory experimental results, displaying an average coordination number of two. Flow simulation results indicated that the core’s microscopic pore structure affected the shape of the displacement leading edge, resulting in a tongue-in phenomenon during oil–water flow. The dominant flow channel was mainly dominated by water, while tongue-in and by-pass flow were the primary microscopic seepage mechanisms hindering oil recovery. These findings lay a foundation for characterizing and analyzing pore structure as well as investigating flow mechanisms in conglomerate reservoirs.

Numerical Studies On the Oil Film Thickness in the Case of Stratified Flow with Different Oil-Water Flow Combinations Through Sudden Contraction Tube

Abstract Most of the oil transportation industries deal with liquid-liquid flow considering the adiabatic situation. In such applications, film thickness measurement plays a very significant role in understanding the flow characteristics. The distribution of phases for efficient wall treatment and to understand the phase distribution, measurement of film thickness is very important. Among different flow patterns, stratified flow is most common for low and medium viscous oil-water flow. At lower oil velocities, stratified flow is observed downstream of singularity whereas in the upstream section, stratified flow is observed for low to medium oil velocities and high-water superficial velocity. Variation of oil film thickness for stratified flow has been analyzed in the present study. Results show that oil film thickness decreases with the increase in the superficial velocity of water (Us-Water) for a constant oil superficial velocity (Us-Oil). With the increase in the volume fraction of one phase, the film thickness of that phase increases. As Us-Oil increases, the film thickness of oil also increases for a constant Us-Water. Oil film thickness is directly proportional to the viscosity of oils. This means, the more the viscosity of the oil, the more will be the oil film thickness.

A Comparative Study of Oil–Water Two-Phase Flow Pattern Prediction Based on the GA-BP Neural Network and Random Forest Algorithm

As global oil demand continues to increase, in recent years, countries have continued to expand the development of oil reserves, highlighting the importance of oil. In order to adapt to different strata distribution conditions, domestic drilling technology is becoming more and more perfect, resulting in a gradual increase in horizontal and inclined wells. Because of the influence of various downhole factors, the flow pattern in the wellbore will be more complex. Accurately identifying the flow pattern of multiphase flow under different well deviation conditions is very important to interpreting the production log output profile accurately. At the same time, in order to keep up with the footsteps of artificial intelligence, big data and artificial intelligence algorithms are applied to the oil industry. This paper uses the GA-BP neural network and random forest algorithm to conduct fluid flow pattern prediction research on the logging data of different water cuts at different inclinations and flow rates. It compares the predicted results with experimental fluid flow patterns. Finally, we can determine the feasibility of these two algorithms for predicting flow patterns. We use the multiphase flow simulation experiment device in the experiment. During the process, the flow patterns are observed and recorded by visual inspection, and the flow pattern is distinguished by referring to the theoretical diagram of the oil-water two-phase flow pattern. The prediction results show that the accuracy of these two algorithms can reach 81.25% and 93.75%, respectively, which verifies the effectiveness of these two algorithms in the prediction of oil–water two-phase flow patterns and provides a new idea for the prediction of oil–water two-phase flow patterns and other phases.

Model and Analysis of Pump-Stopping Pressure Drop with Consideration of Hydraulic Fracture Network in Tight Oil Reservoirs

The existing pump-stopping pressure drop models for the hydraulic fracturing operation of tight oil reservoirs only consider the main hydraulic fracture and the single-phase flow of fracturing fluid. In this paper, a new pump-stopping pressure drop model for fracturing operation based on coupling calculation of the secondary fracture and oil-water two-phase flow is proposed. The physical model includes the horizontal wellbore, the fracture network and the tight oil reservoir. Through the numerical simulation and calculation, the wellbore afterflow performance, the crossflow performance between the main hydraulic fracture and the secondary fracture, the fracturing fluid leakoff and the oil-water replacement after termination of pumping are obtained. The pressure drop characteristic curve is drawn out by the bottom-hole flow pressure calculated through the numerical simulation, and a series of analyses are carried out on the calculated pressure drop curve, which is helpful to diagnose the -oil-water two-phase flow state and the fracture closure performance under the control of the fracture network after hydraulic fracturing pumping. Finally, taking a multi-stage fractured horizontal well in a tight oil reservoir in the Junggar basin, China as an example, the pump-stopping pressure drop data of each stage after hydraulic fracturing are analyzed. Through the history fitting of the pressure drop characteristic curve, the key parameters such as fracture network parameters, which include the half-length of main hydraulic fracture, the conductivity of main hydraulic fracture and the density of secondary fracture, the fracture closure pressure are obtained by inversion, thus, the hydraulic fracturing effect of fractured horizontal well in tight oil reservoirs is further quantified.

Analytical models and experimental verifications for relative permeabilities of oil-water two-phase flow in fractures

The relative permeabilities of oil-water two-phase flow in fractures attract increasing attention in reservoir engineering. In this work, two analytical models were developed for the relative permeabilities of oil-water flow in fractures. One of the models, developed without considering oil-water interface slip, demonstrates that the relative permeabilities of oil-water flow are only dependent on saturation and wetted perimeter. The other one, developed from considering oil-water interface slip, implies that the relative permeabilities of oil-water flow are not only related to saturation and wetting perimeter, but also related to interface coefficients. Comparative experiments were conducted to verify. The experimental rectangular fractures, which were made of polymethyl methacrylate, had different hydraulic diameters from 2.06 to 5.71 mm and height-width ratios from 0.115 to 8.696. The oil-water flow was horizontal and laminar in fractures, with oil-water viscosity ratios ranged from 7.3 to 29.6. Stratified flow and dispersed flow were observed in the experiments. The analytical models developed show that oil-water interface slip has little influence on the relative permeability of oil phase, but has significant effect on the relative permeability of water phase. Both analytical models and experimental results indicate that the sum of relative permeabilities can be greater than 1.

Numerical well test model of oil-water two-phase flow in fractured and vuggy carbonate reservoir

Numerical well test model of oil-water two-phase flow in fractured and vuggy carbonate reservoir

CFD Simulation with Experimental Validation for Heavy Oil-Water Flow in Horizontal Pipe

CFD Simulation with Experimental Validation for Heavy Oil-Water Flow in Horizontal Pipe

Fluid identification and tight oil layer classification for the southwestern Mahu Sag, Junggar Basin using NMR logging-based spectrum decomposition

The intricate distribution of oil and water in tight rocks makes pinpointing oil layers challenging. While conventional identification methods offer potential solutions, their limited accuracy precludes them from being effective in their applications to unconventional reservoirs. This study employed nuclear magnetic resonance (NMR) spectrum decomposition to dissect the NMR T2 spectrum into multiple sub-spectra. Furthermore, it employed laboratory NMR experiments to ascertain the fluid properties of these sub-spectra, aiming to enhance identification accuracy. The findings indicate that fluids of distinct properties overlap in the T2 spectra, with bound water, movable water, bound oil, and movable oil appearing sequentially from the low-value zone to the high-value zone. Consequently, an oil layer classification scheme was proposed, which considers the physical properties of reservoirs, oil-bearing capacity, and the characteristics of both mobility and the oil-water two-phase flow. When applied to tight oil layer identification, the scheme's outcomes align closely with actual test results. A horizontal well, deployed based on these findings, has produced high-yield industrial oil flow, underscoring the precision and dependability of this new approach.

FPRnet: A lightweight multi-domain multi-stream network for complex horizontal oil-water two-phase flow pattern recognition

The complicated spatio-temporal structure of horizontal oil-water flows renders the identification of flow patterns exceedingly challenging, owing to the presence of interfacial waves and droplet entrainment. In this study, a multi-domain fusion feature (MFF) as flow pattern descriptors (FPD) and a lightweight multi-stream networks (LMN) as flow pattern classifier (FPC) are proposed to identify the flow patterns of horizontal oil-water two-phase flow. MFF can map time series into different domains and compactly encode them into higher dimensional expressions, thus displaying implicit flow pattern signals incorporating nonlinear, time-frequency, and probabilistic transition domain features. Finally, the comparison of LMN, variational and other networks is evaluated on the horizontal oil-water flows pattern identification task. Extensive comparison experiments show that the time-frequency feature exhibits optimal characterization for the D O/W flow pattern, the URP feature is most accurately characterized for the D W/O and D O/W flow patterns, and the MTF feature exhibits superior characterization for the remaining three flow patterns. The 98.40 % recognition accuracy demonstrates that MFF has a good representation of flow patterns and the proposed LMN outperforms existing classifiers in flow pattern recognition.