Oil Flow Rate Research Articles

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.

Artificial Neural Network Modeling to Predict Thermal and Electrical Performances of Batteries with Direct Oil Cooling

The limitations of existing commercial indirect liquid cooling have drawn attention to direct liquid cooling for battery thermal management in next-generation electric vehicles. To commercialize direct liquid cooling for battery thermal management, an extensive database reflecting performance and operating parameters needs to be established. The development of prediction models could generate this reference database to design an effective cooling system with the least experimental effort. In the present work, artificial neural network (ANN) modeling is demonstrated to predict the thermal and electrical performances of batteries with direct oil cooling based on various operating conditions. The experiments are conducted on an 18650 battery module with direct oil cooling to generate the learning data for the development of neural network models. The neural network models are developed considering oil temperature, oil flow rate, and discharge rate as the input operating conditions and maximum temperature, temperature difference, heat transfer coefficient, and voltage as the output thermal and electrical performances. The proposed neural network models comprise two algorithms, the Levenberg–Marquardt (LM) training variant with the Tangential-Sigmoidal (Tan-Sig) transfer function and that with the Logarithmic-Sigmoidal (Log-Sig) transfer function. The ANN_LM-Tan algorithm with a structure of 3-10-10-4 shows accurate prediction of thermal and electrical performances under all operating conditions compared to the ANN_LM-Log algorithm with the same structure. The maximum prediction errors for the ANN_LM-Tan and ANN_LM-Log algorithms are restricted within ±0.97% and ±4.81%, respectively, considering all input and output parameters. The ANN_LM-Tan algorithm is suggested to accurately predict the thermal and electrical performances of batteries with direct oil cooling based on a maximum determination coefficient (R2) and variance coefficient (COV) of 0.99 and 1.65, respectively.

Experimental Evaluation of the Deposition Dynamics of Different Petroleum Blends in a Benchtop Heat Exchanger Test Instrument

The article delves into the intricate phenomenon of deposition in heat exchangers and how a piece of equipment known as the benchtop heat exchanger test instrument (BHETI) has been developed to expedite the examination of this phenomenon. The BHETI subjects samples to substantial stress, facilitating the assessment of an oil’s tendency to generate deposits. Tests were conducted on two crude oil blends referred to as blend A and blend B using a BHETI unit. This equipment permits testing under various controlled conditions, including temperature, pressure, and volumetric flow rate. The results indicated that blend A exhibited a higher susceptibility to deposition compared to blend B due to its elevated concentration of light hydrocarbons. The wall temperature exerted a significant influence on the deposition rate, with higher temperatures leading to elevated deposition rates. Conversely, lower oil flow rates resulted in increased deposition rates. Furthermore, extended-term tests unveiled fluctuations in deposition rates over time when blending the two oil samples, suggesting intermittent fouling processes, possibly attributable to thermodynamic imbalances induced by mixing, rendering the oil’s asphaltenes less stable. The outcomes were subjected to analysis employing the Colloidal Instability Index (CII), which indicated that the majority of samples exhibited values exceeding 0.9, signifying asphaltene instability. Additionally, the examination of saturated, aromatic, and NSO (nitrogen, sulfur, oxygen) fractions revealed decreased saturation and increased aromatics after the deposition tests.

Distribution law of Taylor bubble/liquid slug length in oil–gas–water slug flow and the measurement of gas/liquid flow rates based on thermal diffusion

A novel online, non-separation, non-intrusive method based on thermal diffusion is proposed to measure the gas and liquid flow rates of oil–gas–water slug flow in this paper. Temperature fluctuations of a heated pipe wall induced by Taylor bubbles (TB) and liquid slugs (LS) are presented, and velocities and lengths of TB and LS are measured based on these temperature fluctuations. Meanwhile, the number of slug units required to calculate the average TB/LS length is analyzed, and the effect of gas/liquid superficial velocity, oil cut, and gas–liquid ratio on the TB/LS length distribution are respectively presented. The length ratio of TB and LS is found to be linearly and positively correlated with the gas–liquid ratio, which is independent of gas/liquid superficial velocities and oil cuts. Moreover, a simple and reliable model is built to directly associate the TB/LS velocity and length with the gas/liquid flow rates. Experimental results indicate that this proposed method is effective and accurate with root-mean-square errors of 0.025 and 0.052 m3/h for the calculated gas and liquid flow rates, respectively. The flow rate method based on thermal diffusion is simple, cheap, and radiation-free, and it provides a potential solution for the gas/liquid flow rate measurement of oil–gas–water three-phase flows.

Exploring Potential of Gellan Gum for Enhanced Oil Recovery.

Extensive laboratory and field tests have shown that the gelation response of gellan gum to saline water makes it a promising candidate for enhanced oil recovery (EOR). The objective of this mini-review is to evaluate the applicability of gellan gum in EOR and compare its efficiency to other precursors, in particular, hydrolyzed polyacrylamide (HPAM). At first, the "sol-gel" phase transitions of gellan gum in aqueous-salt solutions containing mono- and divalent cations are considered. Then the rheological and mechanical properties of gellan in diluted aqueous solutions and gel state are outlined. The main attention is paid to laboratory core flooding and field pilot tests. The plugging behavior of gellan in laboratory conditions due to "sol-gel" phase transition is discussed in the context of conformance control and water shut-off. Due to its higher strength, gellan gum gel provided ~6 times greater resistance to the flow of brine in a 1 mm-width fracture compared to HPAM gel. The field trials carried out in the injection and production wells of the Kumkol oilfield, situated in Kazakhstan, demonstrated that over 6 and 11 months, there was an incremental oil recovery of 3790 and 5890 tons, respectively. To put it into perspective, using 1 kg of dry gellan resulted in the incremental production of 3.52 m3 (or 22 bbls) of oil. The treatment of the production well with 1 wt.% gellan solution resulted in a considerable decrease in the water cut up to 10-20% without affecting the oil flow rate. The advantages and disadvantages of gellan compared to HPAM are analyzed together with the economic feasibility of gellan over HPAM. The potential for establishing gellan production in Kazakhstan is emphasized. It is anticipated that gellan gum, manufactured through fermentation using glucose-fructose syrup from Zharkent and Burunday corn starch plants, could be expanded in the future for applications in both the food industry and oil recovery.

Machine Learning-Based Optimizer for Tilting Pad Journal Bearing Inlet Flowrate

Abstract In view of the green economy and energy transition, the reduction of the environmental impact of the power generation sector plays a key role. Fluid film bearings are the most common bearing for industrial turbomachinery and new design requirements have a direct impact on bearings operation. In fact, to achieve higher levels of efficiency, bearings must support higher specific loads and higher peripheral speeds. Furthermore, there is great interest in reducing the oil flowrate required for the bearing operation as much as possible. In this work, an optimization strategy for reducing the flowrate fed to tilting pad journal bearings (TPJBs) is proposed. An artificial neural network (ANN) is trained to estimate the static and dynamic performance of the bearings. The training dataset is built with a Reynolds-based thermo-hydrodynamic model. The trained ANN is then used in a constrained optimization that has the goal of minimizing the oil flowrate while ensuring safe bearing operation. Predictions are compared with experimental data from compressor mechanical running tests. The proposed model is an effective tool that can help industry achieve the goals required by the energy transition and can help in the development of optimized fluid film bearings.

Multiphase flow rate prediction using chained multi-output regression models

Virtual flow meters (VFM) are emerging as an attractive and cost-effective alternative to traditional multiphase flow meters to meet monitoring demands, reduce operational costs, and improve oil recovery efficiency. However, no previous studies have accounted for the correlations between the oil, water, and gas flow rates when developing machine learning models. This study proposes a chained regression model for multiphase flow rate prediction to account for such relationships. Real-field data consists of 375 data points for sensory measurements, including pressure, temperature, and choke opening levels, and 42 data points for oil, water, and gas flow rates that were measured downstream of the wellhead, which was acquired over one month. Two robust algorithms, Support Vector Machine (SVM) and Gaussian Process (GP), were employed to develop the chained regression model. The evaluation metrics such as mean absolute percentage error (MAPE) for all the models were estimated using a repeated hold-out approach of cross-validation. The response variables, i.e., the three flow rates, were moderate to strongly correlated. The results showed that the GP-based chain regression model was significantly better than the direct model using the GP algorithm for oil (MAPE: 2.07% vs. 2.27%) and gas (MAPE: 2.5% vs. 2.65%) flow rate prediction (p < 0.01). Overall, the chained model is generally superior to the direct model for flow rate prediction, which was supported by the ranking scores, consistently outperforming the latter in both SVM (79 vs. 87) and GP (64 vs. 70) based approaches. The sensitivity analysis showed that the GP-based chained model accurately predicted oil, water, and gas flow rates within 39.45 m3/day, 14.69 m3/day, and 5.63 m3/day, respectively, of the actual values for approximately 92% of the data points. This study’s findings can be instrumental in designing and developing practical and accurate VFM for multiphase flow rate prediction.

Oil And Gas Flow Rate Prediction for African Oilfields: An Overview of Existing Models, Data and Uncertainties

Oil And Gas Flow Rate Prediction for African Oilfields: An Overview of Existing Models, Data and Uncertainties

METHODOLOGY FOR DETERMINING THE MAXIMUM ANHYDROUS FLOW RATE OF A HORIZONTAL OIL WELL IN DEPOSITS WITH PLANTAR WATER

The article is devoted to the use of approximate methods for determining the productivity of horizontal oil wells and comparing the results of flow rate calculations by these methods on the example of an oil facility of the Karachaganak field. Watering or gassing of the oil-bearing interval significantly reduces the phase permeability of oil and leads to a very significant decrease in oil flow rate. Therefore, technologies that minimize the process of cone formation are of great practical importance. From the point of view of the influence of flooding on the technological mode of operation of a horizontal oil well and the possibility of determining the anhydrous flow rate, it follows that the following possible options are proposed to avoid flooding of the well:- the use of horizontal wells with the appropriate location of the horizontal trunk, depending on the proximity to the oil-water contact (VNK), taking into account the magnitude of the depression created on the formation; - selection of the appropriate design of the well, the length and diameter of the fountain pipes in the horizontal part of the trunk, providing the amount of depression necessary to slow down the pace of movement of plantar water.

Evaluation of a hollow fiber membrane contactor reactor for reactive extraction in biodiesel production

A polypropylene hollow fiber membrane contactor reactor (HF-MCR) was used to evaluate the performance of a reactive extraction process for biodiesel production. The process involved the transesterification of soybean oil with methanol, catalyzed by sodium hydroxide. The experimental methodology assessed the impact of oil flow rate and methanol/oil molar ratio on the biodiesel (FAME) production rate, triglyceride reaction rate, and glycerin concentration in the final biodiesel product. The results demonstrated that, by employing a countercurrent configuration, is possible to extract the glycerin from the biodiesel-rich phase with methanol, achieving both the reaction and the separation stages in the same equipment. The best results were obtained at a methanol/oil molar ratio of 4:1 and an oil flow rate of 0.4 L h−1, leading to a triglyceride conversion rate of 0.14 mol h−1 and a FAME production rate of 0.24 mol h−1, equivalent to 34 % conversion and 56 % yield, respectively. The final biodiesel product showed a low concentration of glycerin, measuring only 0.06 % wt. This investigation highlights the potential of employing membrane contactors technology for the biodiesel production process, reducing the processing time by eliminating the biodiesel/glycerol separation stage, and therefore bringing down the load of downstream purification operations.

Improving the flow and thermal uniformities of transformer disc-type windings using a self-blocking oil circuit

The design of winding oil circuits is of great significance for improving the reliability, lifetime and loading capability of power transformers. Given the limited cooling capacity and local hot spot problems of the traditional oil circuits, a self-blocking oil circuit was introduced in this work. This study focused on exploring the potential advantages of this self-blocking oil circuit over the traditional ones in terms of the flow and thermal performance. To this end, the winding heat losses, flow and temperature were first calculated using a multi-physics coupling numerical model. Subsequently, the flow and heat transfer mechanisms of the winding were studied. Then, the flow and heat transfer performance of the winding with the self-blocking and traditional oil circuits were evaluated and compared. Furthermore, the effects of blocking degrees and oil flow rates on the winding flow and thermal performance were investigated. The results showed that compared with the traditional oil circuits, the self-blocking oil circuit exhibited a significant potential to improve the flow uniformity of transformer disc-type windings. It owned a larger cooling potential and the ability to lower winding hot spot temperature.

Simulation Study on the Motion Characteristics and Influencing Factors of Fiber Impurity Particles in Oil Flow in a Typical Distributed Electric Field

There have been many studies on the motion and aggregation characteristics of fiber impurities in insulation oil under static conditions. However, there are few studies on the motion characteristics of fiber impurities in insulation oil under flow conditions. In large power transformers, insulation oil is constantly in a state of flow. As a result, the motion characteristics of fiber impurities suspended in the insulation oil are even more complex due to the effects of oil flow. This study constructed a multi-physics field model for single-particle fibrous impurities in solid-liquid two-phase flow and systematically analyzed its motion characteristics. The study shows that the collision frequency between fiber impurity particles and electrodes with the same effective area is negatively correlated with the degree of electric field distortion. The maximum particle velocity and collision frequency of fibrous impurities in both uniform and slightly non-uniform electric fields show an almost linear relationship with the particle size radius. Additionally, the slope of the relationship decreases gradually with an increase in oil flow rate. With the increase of particle size, under the same flow velocity, an increase in the maximum velocity of the fibrous particles and the number of collisions with the electrodes. thereby increasing the probability of fibrous impurities transferring charge between the electrodes. Compared to the motion characteristics of fibrous impurity particles under static conditions, oil flow mainly affects the collision frequency between fibrous impurity particles and electrodes, reducing the probability of particle transfer.

Analysis of Well Performance Based on Bottom Hole Pressure Calculations for Gas Lift Application

This paper focuses on optimizing gas lift techniques in four wells located in the North Sea to overcome the common issue of low reservoir pressure. Gas lift is a common artificial lift technique used in wells with low reservoir pressure where the natural pressure of the reservoir is insufficient to bring the oil to the surface. The success of gas lift optimization depends on identifying the deepest injection point, gas injection rate, and pressure of the gas injected. The paper proposes the deepest injection points for wells A-03, A-09A, A-10T2, and A-12BT2 as 3809.38 ft, 6649.7 ft, 3559.88 ft, and 3979.04 ft, respectively. The injection rates analyzed in this paper range from 1-10 mmscf/day, and injection pressures of 500 psia, 1000 psia, and 1500 psia were used. The response of each well to gas lift was analyzed, and increasing injection rate and pressure were found to increase oil production rate. The optimal gas injection rate and pressure for wells A-03, A-09A, and A-12BT2 were found to be 10 mmscf/day and 1500 psia, while for well A-12BT2, the best oil recovery was obtained at an injection rate of 3 mmcsf/day and injection pressure of 1500 psia. Tubing size within the range of 1-5.5 inch was examined, and it was found that increasing tubing size enhances oil flow rate. The optimal tubing size for the wells was found to be 5.5 inch, taking into consideration factors such as flow rate, pressure, temperature requirements, and fluid type.

Forecasting the dynamics of oil flow rate changes using machinne learning methods

Forecasting the dynamics of oil flow rate changes using machinne learning methods

Вероятностная оценка эффективности применения метода циклического заводнения нефтяных пластов

Extraction of hard-to-recover hydrocarbons is becoming an urgent task for the entire world oil community. The development of new technologies and methods, as well as the improvement of existing ones, have become the main issue in the extraction of hydrocarbons at existing fields. The aim of the work was to develop the technology of hydrodynamic impact on the hydrocarbon deposit. The process of oil reservoirs flooding is one of the most widespread and traditional in the application of extraction of hard–to-recover oil. The most effective in terms of impact is the cyclic regime of flooding of oil reservoirs – periodic changes in fluid flow rates at injection and production wells with a phase shift of oscillations for individual groups of wells. The use of cyclic flooding in combination with an increase in the average level of injection pressures can give a significant increase in the coefficient of reservoir coverage in power. The degree of hydrodynamic connectivity of the layers along the section has a significant impact on the effectiveness of cyclic flooding. The coefficient of lithological connectivity of formations is determined by the ratio of the area of the reservoir confluence to the total area of the deposit and can characterize the hydrodynamic connectivity of formations along the section. Using the example of the D3 of the Korotkoye field, an assessment of the start-up of the wells of the PPD system was done as well as the analysis of the nature of its influence on the volume and water content of the extracted products of the D3 formation of the Korotkoye field under various injection modes using cyclic flooding. It is determined that when both injection wells are stopped for a long period, the output of the produced products decreases to 25%. The analysis of the total oil flow rate showed that in the variants with well shutdowns there is a stronger decrease in oil flow rate than in the variants with cyclic injection, in the variants with cyclic operation of the PPD system the highest indicators of accumulated oil production are achieved for a certain period.

Pores collapse hysteresis damage evaluation in depletion-dependent oil reservoirs using an asymptotic-integro-differential perturbation method

This work proposes a new asymptotic-perturbative solution for transient pores collapse hysteresis modeling in depletion-dependent oil reservoirs with compaction effects during alternating loading/unloading cycles. The nonlinear hydraulic diffusivity equation (NHDE) is perturbed through a first-order expansion technique using the depletion-dependent permeability, k(p) as a perturbation parameter, ϵ. A new hysteretic deviation factor is presented for flow (drawdown) and well-shut (buildup) periods. This factor represents the permeability deviation during the drawdown and its partial restoration in the buildup period. The model calibration is performed by a porous media numerical oil flow simulator named IMEX®, and the results presented high accuracy for the drawdown and buildup of hysteretic and non-hysteretic cases (when the pores collapse did not occur yet). The practical uses of the model developed in this work are related to identifying flow regimes and hysteresis responses in pressure-sensitive reservoirs, estimating buildup pressure, and oil flow rates specification to prevent severe hysteretic behavior and history matching during reservoir surveillance. Two case studies related to different reservoir layers are researched, and for both cases, the results from the log–log plots analysis have shown that the infinite-acting-radial oil flow (1/2 value of the slope of the pseudo-pressure derivative) was identified. In addition, the log–log analysis also shows that the shut-in pressure has an influence on permeability loss. The main advantages of the solution derived in this work are the simple implementation, practical graphical analysis of the pores collapse hysteresis effect, the possibility of simulating different boundary conditions and well-reservoir settings, and the requirements of only a few pressure and permeability field data to input in the deviation factor. The solution proposed can be applied to choose the production time to shut the well and monitor the adequate oil flow rate during the production curve.

A New Experimental Methodology to Study Convective Heat Transfer in Oil Jet Lubricated Gear Units

The purpose of this study is to generate some experimental data associated with the thermal heat exchange between an oil jet flow and a rotating gear. To this end, a specific test bench was designed. The principle of this test bench is to inject oil heated to a temperature of about 80 °C onto a rotating test sample at ambient temperature. Temperature measurements of the oil via injection nozzles and the rotating component allow the determination of the heat flow between these elements using a numerical method developed to this end. This test rig enables the study of the parameters that may affect heat exchange, such as oil flow rate and injection temperature, nozzle geometry and position, gear rotational speed and tooth geometry, or oil characteristics. In this study, three of these parameters were investigated, namely the test sample rotational speed, the oil flow rate, and the oil jet velocity. The experiments were conducted on an aluminum disc and spur gear. Subsequently, the experimental results were compared with existing models that represent the convective exchanges between oil and a gear. Some discrepancies between existing models and experimental results appear at high rotational speeds, underlining that the convective heat transfer does not always increase with this parameter.

ESP Design Optimization and Sensitivity Analysis for Oil Well (E-05) using Prosper software

The natural reservoir pressure is often sufficient to lift the fluids to the surface. However, when excessive water and gas production occurs, the reservoir pressure may no longer be sufficient. In such cases, an artificial lift method is required to lift the fluids to the surface. The objective of this study is to improve the efficiency of the ESP system and to identify the critical parameters that affect the system's performance of oil well E.05 using Prosper software. Results were obtained and analyzed to determine the optimal design for the well. In this paper, we discussed the ESP model and its impact on productivity. The ESP model is designed to optimize parameters such as reservoir pressure, pump sitting depth, operation frequency, and number of stages. Specifically, the model recommends a reservoir pressure of 3100 psi, a pump sitting depth of 5000 ft, an operation frequency of 60 HZ, and number of stages of 225 stages. By implementing these parameters, the ESP model has been shown to significantly improve productivity. This model boasts best pump and motor efficiency, making it a reliable choice for optimizing production. The oil flow rate for the well has increased from 916 STB / D to 1008 STB / D, indicating a successful current design for the well. Further research is needed to better understand the factors that affect ESP performance, such as wellbore conditions, fluid properties, and pump design.&#x0D;

Numerical and experimental investigation of the droplet size for MQL aerosol under different operating parameters with Flow visualization

Minimum quantity lubrication (MQL) is a sustainable machining process in which oil and air are mixed to form a spray that can be directed to the cutting zone. MQL spray factors like droplet size and velocity and their effect on machining remain unclear, especially when employing diverse oils and operating settings. Mist formation factors determine how well spray droplets lubricate the targeted area during machining. Numerical and Experimental studies were conducted with different values for MQL parameters like cutting oil type, air pressure and oil flow rate, to establish the best possible combination to give the ideal droplet size and surface roughness. The study utilized three types of oils and varied air pressures to evaluate the cooling effectiveness of MQL spray during end milling operations. Experimental droplet size and velocity measurements were obtained using ‘Phase Doppler Anemometry (PDA)’ and ‘Particle Image Velocimetry (PIV)’ techniques. A numerical model within ANSYS Fluent software, employing computational fluid dynamics (CFD), predicted spray flow properties and was validated using PIV data. Raising the air pressure decreased the droplet size, while increasing velocity to achieve greater overall speed and enhanced lubrication in the cutting region. Changing the coolant flow rate or the compressed air pressure affected the Sauter mean diameter (SMD) of oil particles. The research showed that increasing air pressure from 1 bar to 3 bar reduced surface roughness by 55.40 percent and SMD by 24.58 percent for 120V oil. Among the three cutting oils tested, the 120V oil achieved the lowest surface roughness at 0.227μm under specific conditions: a flow rate of 150 ml hr−1, pressure of 3 bars, and SMD of 35.5 μm. These findings provide valuable insights into improving MQL efficiency for machining operations.

Research on Oil–Gas Two-Phase Flow Characteristics and Improvement of Aero-Engine Bearing Chamber

In order to study the oil–gas two-phase flow characteristics of an aero-engine bearing chamber and improve the scavenge effect of lubricating oil, the two-phase flow solution model of a bearing chamber based on the Euler–Euler method was established. Three improvement schemes were proposed for the ventilation structure and scavenge structure of the bearing chamber. The flow characteristics and scavenge characteristics of a conventional bearing chamber and three improvement schemes under different working conditions were analyzed in depth. The results show that after the conventional bearing chamber ventilation structure is embedded (Embed) and improved, with the increase in the embedding depth, the oil in the cavity is further blocked in the cavity, the amount of oil flowing out from the vent is further reduced, and the scavenge efficiency is further improved. After the slope improvement of the scavenge structure of the conventional bearing chamber, due to the increase in the depth of the oil return groove, the drag effect of the air shear force in the cavity on the oil in the oil return groove is further weakened, and the oil accumulation area on the right side of the scavenge port is further suppressed. The volume fraction of the oil in the cavity is further reduced, and the scavenge efficiency is further improved. The combined improvement scheme (ES) can take into account the advantages of embedding and slope improvement schemes, and further improve the scavenge efficiency. Compared to the conventional bearing chamber, when the oil flow rate is 200 L/h and the speed is 15,000 r/min, the oil return efficiency of the embedded (h = 12 mm), slope (l = 56 mm) and combined improvement schemes are increased by 20.19%, 13.43%, and 37.94%, respectively.