The electrical submersible pump (ESP) plays a crucial role in artificial lift operations in the oil and gas industry.
The viscosity of the pumped fluid significantly influences the flow dynamics within the ESP, thereby impacting
the performance of the machine. In this context, flow visualization techniques can unveil intricate details of the
flow in ESP impellers, thus providing a deeper understanding of the relationship between flow behavior and
pump performance. This is the main idea of the present document, which utilizes the particle image velocimetry
(PIV) technique to experimentally investigate a mineral oil flow, 𝜇 = 14 𝑐𝑃, in a transparent prototype of a real
impeller, P23 model. The paper reports insights into the flow in the pump’s rotating component at different flow
rates that correspond to percentages of the best efficiency point (BEP). Average velocity fields and turbulent
kinetic energy plots indicate that flow dynamics are highly dependent on the operating conditions of the ESP.
A comparison between results for oil and water completes the analysis, as it highlights the effects of viscosity
on the flow characteristics. This type of study is useful to validate numerical simulations, support mathematical
models, and develop improved impeller designs.
Tag: Electrical Submersible Pump
Experimental study of electrical submersible pump performance under water-in-oil emulsion flow
Electrical Submersible Pump (ESP) systems are currently one of the best artificial lift methods in terms of production rate. The presence of complex fluid systems such as stabilized emulsions difficult its performance, causing the increase in required power and operational instabilities. Both the emulsions stability and the catastrophic phase inversion (CPI) are related to the droplet size distribution. This work aims to investigate how the droplet size distribution of water-in-oil flow within ESP systems is affected by rotational speed and flow rate. An ESP flow loop was designed to test emulsion flow with several rotational speeds and a range of flow rates that covers almost the entire performance curve. The droplet size distribution was evaluated by the Focused Beam Reflectance Measurement (FBRM) technic. The Sauter mean diameter shown a decreasing trend as the dimensionless flow rate increases.
Learning characteristic parameters and dynamics of centrifugal pumps under multiphase flow using physics-informed neural networks
Electrical submersible pumps (ESPs) are prevalently utilized as artificial lift systems in the oil and gas industry. These pumps frequently encounter multiphase flows comprising a complex mixture of hydrocarbons, water, and sediments. Such mixtures lead to the formation of emulsions, characterized by an effective viscosity distinct from that of the individual phases. Traditional multiphase flow meters, employed to assess these conditions, are burdened by high operational costs and susceptibility to degradation. To this end, this study introduces a physics-informed neural network (PINN) model designed to indirectly estimate the fluid properties, dynamic states, and crucial parameters of an ESP system. A comprehensive structural and practical identifiability analysis was performed to delineate the subset of parameters that can be reliably estimated through the use of intake and discharge pressure measurements from the pump. The efficacy of the PINN model was validated by estimating the unknown states and parameters using these pressure measurements as input data. Furthermore, the performance of the PINN model was benchmarked against the particle filter method utilizing both simulated and experimental data across varying water content scenarios. The comparative analysis suggests that the PINN model holds significant potential as a viable alternative to conventional multiphase flow meters, offering a promising avenue for enhancing operational efficiency and reducing costs in ESP applications.
Development of a transparent pump prototype for flow visualization purposes
The presence of emulsions in centrifugal pumps has always been a top issue for oil and gas exploration companies. These oil-water mixtures cause financial losses along the production chain, as they often induce pumps to operate in an unstable and inefficient manner. As there is a clear dependence between the pump performance and the flow arrangement in the impellers, this current paper aims to broaden the understanding on the behavior of emulsions inside the stage of a centrifugal pump. Thus, the paper describes the design and fabrication of a new transparent pump prototype for visualization purposes focused on academic studies. The new prototype is completely transparent, so it enables visual access and light entrance from the front and sides. Besides, the new pump is able to operate with twophase flows, since the dispersed phase can be injected directly into the impeller channels, through the shaft. Some tests were then conducted with this new prototype. They provided successful results which are presented and discussed here. Therefore, the new transparent prototype is an innovative alternative to help engineers and researchers investigate twophase flows in rotating and stationary pump parts.
Experimental Investigation Of The Shear Effect On Oil-Water Emulsion Flow In Pipelines
Emulsion flows have been a severe flow assurance issue, mainly in mature oil fields. Its formation occurs due to shear on oil-water flows caused by artificial lift methods, such as Electrical Submersible Pumps (ESP), and/or valves. The shear rate has an important role in emulsion flow behavior related to its relative viscosity and phase inversion. Therefore, this work presented an experimental investigation of the shear effect on three emulsion systems flowing in a pipeline. The shear element used was a combination of an 8-stage ESP and a glob valve. The emulsion systems analyzed were unstable emulsion and stable emulsion with and without a demulsifier. The experimental investigation was carried out for two ESP rotational speeds, 2400 and 3500 rpm, and one total volumetric flow rate, varying the water cut. From this study, it was observed that phase inversion occurred with increasing shear. Moreover, the effective viscosity was the same regardless of the surfactant presence for the three emulsion systems tested.
Experimental Investigation on Velocity Fields, Vorticity, and Turbulence within the Stage of an Electrical Submersible Pump (ESP)
This paper presents an experimental study on the flow dynamics within an Electrical Submersible Pump (ESP) stage. An ESP prototype with transparent impeller and diffuser was designed and manufactured to allow flow visualization, which was achieved by using a Time-Resolved Particle Image Velocimetry (TR-PIV) system. Single-phase water flow tests were conducted in various flow rates corresponding to percentages of the Best Efficiency Point (BEP). The average velocity fields, vorticity contours, and turbulent kinetic energy values obtained in the whole impeller reveal that the flow behaviour is very dependent on the ESP operational condition. Energy losses due to turbulence are lower when the pump works at the BEP. But when the device operates at off-design conditions, the flow becomes complex, with high vorticity and turbulence which cause a reduction in the performance. This type of investigation may be useful to validate numerical simulations, support the proposition of mathematical models, or help create improved impeller designs.
Experimental investigation of the Electrical Submersible Pump’s energy consumption under unstable and stable oil/water emulsions: A catastrophic phase inversion analysis
The presence of water in crude oil exploitation by the Electrical Submersible Pump (ESP) systems may cause several problems in energy consumption and operational instabilities due to emulsion formation. Indigenous surfactants in crude oil also contribute to emulsion stabilization, which can exacerbate these problems. In this paper will be experimentally investigated the influence of the emulsion stability on ESP energy consumption and operational instabilities through an 8-stage ESP operating with unstable and stable emulsions, with and without a demulsifier. The experimental tests were performed for one oil viscosity, a constant total flow rate, and two ESP rotational speeds. Initially, the ESP relative dimensionless power (RDP) was analyzed along with the emulsion system and the droplet size distribution (DSD). An interesting difference regarding the presence of surfactants was observed experimentally in the RDP and phase inversion points. The relationship among the ESP dimensionless power, torque, and electrical current with maximum droplet size allowed to conclude that these parameters can be related to the start of the coalescence process, i. e, able to predict the catastrophic phase inversion (CPI) point.
Water Cut Estimation in Electrical Submersible Pumps Using Artificial Neural Networks
An artificial lift is a method used to obtain a higher oil flow rate from the well, through some scheme that reduces the pressure at the bottomhole. Electrical submersible pumping is a common method in petroleum industry. The main component of this method is the electrical submersible pump (ESP), that can operate with complex flows involving mixtures of oil, water and gas. The presence of water in oil fields is a problem because it favors the formation of emulsions, which are the mixture of oil and water. Emulsions can be found in the form of oil-in-water and water-in-oil emulsions, depending on which phase is the continuous one and which is the dispersed one. Water-in-oil emulsions increase considerably the viscosity of the mixture and affect the pump’s efficiency, diminishing its pumping capacity. The increase or decrease of the water fraction in the process may cause the phenomenon called catastrophic phase inversion (CPI), in which the
dispersed phase becomes the continuous one and rapidly alters the physical properties of the flow, causing operational instability throughout the production system. In order to identify and predict this important phenomenon in complex multiphase flows, the usage of advanced identification tools, based on experimental data, has been used in recent years. In this work, artificial neural networks are used to estimate the water fraction in a flow that runs through an ESP. For that, data like inlet and outlet pressures, temperature, vibration and the correspondent water cut values, among others, were collected from an ESP operating with water and oil. Single-phase and two-phase tests were performed with the purpose of collecting data with different water cut values, ranging from 0% (single-phase oil) to 100% (two-phase water and oil). From the laboratory experiments, it was possible to build a data-driven computational tool capable of estimating the water fraction that runs through the pump, based on an optimized artificial neural network structure, which achieved an R-score of 0.9987.
Relative Viscosity Model for Oil/Water Stable Emulsion Flow within Electrical Submersible Pumps
Electrical Submersible Pumps (ESP) have been used in several scenarios, including water/crude oil emulsion production. The estimation of the emulsion effective viscosity within the ESP is still under discussion due to its complex flow behavior. This work proposes, for the first time, a model to predict the relative viscosity of stable emulsion within an ESP considering the continuous phase properties and ESP operational parameters. The viscosity model was compared to the relative viscosity models for emulsion flow in pipelines and the mean absolute percentage error (MAPE) was 14% and 8% for the stable emulsions without and with demulsifier, respectively. For the same emulsion systems, the relative viscosity model was applied to the unidimensional model to predict the ESP performance with the MAPE of 4% and 2% for the stable emulsions without and with demulsifier, respectively. Furthermore, ESP head degradation operating with stable emulsion with and without demulsifier was investigated experimentally.