EN 
BR Mixed finite element computations arise in the simulation of multiple physical phenomena. Due to its characteristics, such as the strong coupling between the approximated variables, the solution of such class of prob- lems may suffer from numerical instabilities as well as a computational cost. The de Rham diagram is a standard tool to provide approximation spaces for the solution of mixed problems as it relates H1 -conforming spaces with H(curl) and H(div)-conforming elements in a simple way by means of differential operators. This work presents an alternative for accelerating the computation of mixed problems by exploring the de Rham sequence to derive divergence-free functions in a robust fashion. The formulation is numerically verified for the 2D case by means of benchmark cases to confirm the theoretical regards.
Author: EPIC Energy
Avaliação do efeito da variação de dimensionalidade na seleção de realizações geoestatísticas representativas para quantificação de risco, usando o método de Análise de Componente Principal
A etapa de seleção de modelos representativos (MRs) para tomada de decisão sob incerteza tem, muitas vezes, um elevado custo computacional gasto em simulações de escoamento (Schiozer et al., 2019). Como forma de reduzir este custo, Mahjour et al. (2020) simplificaram as 300.000 dimensões das realizações geoestatísticas do modelo benchmark UNISIM-II-D em duas, utilizando redução de dimensionalidade. Contudo, tal simplificação tem como consequência a perda da variabilidade do conjunto de dados. Assim, esse trabalho utiliza Análise de Componente Principal (PCA, na sigla em inglês) para redução de dimensionalidade, variando o número de dimensões geradas para avaliar a quantidade de informação capturada no sistema simplificado, e buscar a melhor configuração do fluxo de trabalho para quantificação de risco. Foi observado que, para o caso estudado, as dimensões geradas pela PCA capturam pouca variabilidade e de forma heterogenia em relação às propriedades que as dimensões representam, como porosidade. Dessa forma, um sistema simplificado com poucas dimensões, além de pouca informação, fica enviesado. Em relação à quantificação de risco, independentemente do número de MRs e técnicas de clusterização, o aumento do número de dimensões geradas não só não favoreceu os resultados como aumentou os erros relacionados à representação do risco. Este fenômeno é explicado pela literatura como a “maldição da dimensionalidade”. Recomenda- se a aplicação do fluxo de trabalho usando poucas dimensões (entre 2 e 4), Kmeans como método de clusterização para seleção de MRs e o maior número de MRs possível.
A Study on Image Pre-Processing and PIV Processing Techniques for Fluid Flows
Particle Image Velocimetry (PIV) is a non-intrusive and quantitative technique used for the visualization and measurement of deformation rates in fluid flows. The performance of the PIV technique is determined by the quality of the recorded images and treatment of the data obtained after the acquisition. The PIV technique heavily depends on the quality of the acquired images, i.e., homogeneous lighting, good contrast, low background noise, and suitable particle displacement. However, these conditions cannot always be achieved, and image pre-processing becomes an important tool for an accurate analysis of the problem. In the PIV pre-processing step, the aim is to enhance the correlation signal (displacement peak) and, therefore, produce higher quality vector fields based on contrast improvement, brightness correction, and noise removal. After the pre-processing step, the displacement vector is computed using a PIV correlation algorithm to obtain the velocity field in the next step. This work aims to evaluate and compare the performance of PIV image pre-processing and processing techniques. For this, two types of flows were used, Poiseuille flow and Rankine vortex, created from a PIV image generator and processed using the PIVlab toolbox, both coded in MATLAB. Three image pre-processing methods are analyzed: i) Contrast Limited Adaptive Histogram Equalization (CLAHE); ii) intensity high-pass and; iii) intensity capping. The accuracy of the DCC (Direct-Cross-Correlation) and DFT (Discrete Fourier Transform) algorithms are also evaluated and discussed.
Development of a Particle Tracking Velocimetry (PVT) Measurement Technique for the Experimental Investigation of Oil Drops Behavior in Dispersed Oil-Water Two-Phase Flow within a Centrifugal Pump Impeller
The objective of the current work is to present the development of a robust Particle Tracking Velocimetry (PTV) software for the analysis of oil drops behaviour in dispersed oil-water two-phase flow within a centrifugal pump impeller. The oil drop tracking was realized through high-speed camera acquisitions in a transparent pump prototype, which enabled the visualization of oil drops dispersed in water in all the impeller channels. The PTV software is based on a U-NET and standard convolutional networks, which detects oil drop contours in each frame of the high-speed camera videos. In order to assess the PTV software capabilities, a single experiment was analyzed in detail. In this experiment, due to the pump rotation speed and the water flow rate, intense transient fluctuations on the dispersed oil size distribution were observed in the recorded acquisitions. This procedure completely characterized instantaneous drop dynamics in the impeller channel. According to the results, there is a strong dependence between the oil injection flow rate, the instantaneous drop size distribution and the average velocity field.
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.
3rd EPIC Conference
Entre os dias 09 e 11 de novembro de 2021 foi realizada, virtualmente, a 3rd. EPIC Conference, evento anual voltado à divulgação dos trabalhos em desenvolvimento no centro. Mais informações podem ser obtidas no Programa da Conferência, apresentado abaixo.
A novel criterion based on slip ratio to assess the flow behavior of W/O emulsions within centrifugal pumps
Water-in-oil emulsions usually present complex rheological behavior that depends on the physicochem-ical properties of both phases, the presence of surfactants, and the flow conditions. Thereby, this paperaims to propose a criterion to characterize the rheological behavior of stable and unstable water-in-oil emulsions within the centrifugal pumps. This criterion is based on the slip ratio between the dispersedand continuous phases. For this, the droplet size distribution was measured at the ESP outlet and the slipratio was estimated based on the centrifugal buoyancy-induced flow. A new model was proposed todetermine the Sauter mean diameter for different systems of the water-in-oil emulsion flows withinthe ESP based on operational conditions, which presents good agreement with the experimental data(12.6% of error). Finally, a new dimensionless number parameter named Slip Relevance number was pro-posed to separate the different emulsion flow behaviors within the ESP and its critical value was obtained.
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.
Flow visualization in centrifugal pumps: A review of methods and experimental studies
Methods for flow visualization have been decisive for the historical development of fluid mechanics. In recent years, technological advances in cameras, lasers, and other devices improved the accuracy and reliability of methods such as High-Speed Imaging (HSI) and Particle Image Velocimetry (PIV), which have become more efficient in visualizing complex transient flows. Thus, the study of centrifugal pumps now relies on experimental techniques that enable a quantitative characterization of single- and two-phase flows within impellers and diffusers. This is particularly important for oil production, which massively employs the so-called Electrical Submersible Pump (ESP), whose performance depends on the behavior of bubbles and drops inside its impellers. Visualization methods are frequently used to study gas-liquid flows in pumps; however, the visualization of liquid-liquid dispersions is complex and less common, with few publications available. Methods to characterize the motion of gas bubbles are often unsuitable for liquid drops, especially when these drops are arranged as emulsions. In this context, there is room to expand the use of visualization techniques to study liquid-liquid mixtures in pumps, in order to improve the comprehension of phenomena such as effective viscosity and phase inversion with focus on the proposition of mathematical models, for example. This is a main motivation for this paper, which presents a review of researches available in the literature on flow visualization in centrifugal pumps. A broad set of studies are reported to provide the reader with a complete summary of the main practices adopted and results achieved by scientists worldwide. The paper compares the methods, investigates their advantages and limitations, and suggests future studies that may complement the knowledge and fill the current gaps on the visualization of single-phase flows, gas-liquid, and liquid-liquid mixtures.