Simulador de escoamento multifásico em poços de petróleo (SEMPP)

The multiphase flow occurrence in the oil and gas industry is common throughout fluid path, production, transportation and refining. The multiphase flow is defined as flow simultaneously composed of two or more phases with different properties and immiscible. An important computational tool for the design, planning and optimization production systems is multiphase flow simulation in pipelines and porous media, usually made by multiphase flow commercial simulators. The main purpose of the multiphase flow simulators is predicting pressure and temperature at any point at the production system. This work proposes the development of a multiphase flow simulator able to predict the dynamic pressure and temperature gradient in vertical, directional and horizontal wells. The prediction of pressure and temperature profiles was made by numerical integration using marching algorithm with empirical correlations and mechanistic model to predict pressure gradient. The development of this tool involved set of routines implemented through software programming Embarcadero C++ Builder® 2010 version, which allowed the creation of executable file compatible with Microsoft Windows® operating systems. The simulator validation was conduct by computational experiments and comparison the results with the PIPESIM®. In general, the developed simulator achieved excellent results compared with those obtained by PIPESIM and can be used as a tool to assist production systems development

Projeto de um sistema emulador de escoamentos e vaso de separação primária

The purpose of this study was to develop a pilot plant which the main goal is to emulate a flow peak pressure in a separation vessel. Effect similar that is caused by the production in a slug flow in production wells equipped with the artificial lift method plunger lift. The motivation for its development was the need to test in a plant on a smaller scale, a new technique developed to estimate the gas flow in production wells equipped with plunger lift. To develop it, studies about multiphase flow effects, operation methods of artificial lift in plunger lift wells, industrial instrumentation elements, control valves, vessel sizing separators and measurement systems were done. The methodology used was the definition of process flowcharts, its parameters and how the effects needed would be generated for the success of the experiments. Therefore, control valves, the design and construction of vessels and the acquisition of other equipment used were defined. One of the vessels works as a tank of compressed air that is connected to the separation vessel and generates pulses of gas controlled by a on/off valve. With the emulator system ready, several control experiments were made, being the control of peak flow pressure generation and the flow meter the main experiments, this way, it was confirmed the efficiency of the plant usage in the problem that motivated it. It was concluded that the system is capable of generate effects of flow with peak pressure in a primary separation vessel. Studies such as the estimation of gas flow at the exit of the vessel and several academic studies can be done and tested on a smaller scale and then applied in real plants, avoiding waste of time and money.

Sistema inteligente para detecção de vazamentos em dutos de petróleo usando transformada Wavelet e redes neurais

This work consists in the use of techniques of signals processing and artificial neural networks to identify leaks in pipes with multiphase flow. In the traditional methods of leak detection exists a great difficulty to mount a profile, that is adjusted to the found in real conditions of the oil transport. These difficult conditions go since the unevenly soil that cause columns or vacuum throughout pipelines until the presence of multiphases like water, gas and oil; plus other components as sand, which use to produce discontinuous flow off and diverse variations. To attenuate these difficulties, the transform wavelet was used to map the signal pressure in different resolution plan allowing the extraction of descriptors that identify leaks patterns and with then to provide training for the neural network to learning of how to classify this pattern and report whenever this characterize leaks. During the tests were used transient and regime signals and pipelines with punctures with size variations from ½' to 1' of diameter to simulate leaks and between Upanema and Estreito B, of the UN-RNCE of the Petrobras, where it was possible to detect leaks. The results show that the proposed descriptors considered, based in statistical methods applied in domain transform, are sufficient to identify leaks patterns and make it possible to train the neural classifier to indicate the occurrence of pipeline leaks

Controlador preditivo não linear aplicado ao controle de golfadas em processos de produção de petróleo

Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

Modelagem numérica de escoamento em padrão anular com transferência de calor e massa

Annular flow is the prevailing pattern in transport and energy conversion systems and therefore, one of the most important patterns in multiphase flow in ducts. The correct prediction of the pressure gradient and heat transfer coefficient is essential for optimizing the system s capacity. The objective of this work is to develop and implement a numerical algorithm capable of predicting hydrodynamic and thermal characteristics for upflow, vertical, annular flow. The numerical algorithm is then complemented with the physical modeling of phenomena that occurs in this flow pattern. These are, turbulence, entrainment and deposition and phase change. For the development of the numerical model, axial diffusion of heat and momentum is neglected. In this way the time-averaged equations are solved in their parabolic form obtaining the velocity and temperature profiles for each axial step at a time, together with the global parameters, namely, pressure gradient, mean film thickness and heat transfer coefficient, as well as their variation in the axial direction. The model is validated for the following conditions: fully-developed laminar flow with no entrainment; fully developed laminar flow with heat transfer, fully-developed turbulent flow with entrained drops, developing turbulent annular flow with entrained drops, and turbulent flow with heat transfer and phase change

Simulação do escoamento multifásico no interior de bombas de cavidades progressivas metálicas

The progressing cavity pumping (PCP) is one of the most applied oil lift methods nowadays in oil extraction due to its ability to pump heavy and high gas fraction flows. The computational modeling of PCPs appears as a tool to help experiments with the pump and therefore, obtain precisely the pump operational variables, contributing to pump s project and field operation otimization in the respectively situation. A computational model for multiphase flow inside a metallic stator PCP which consider the relative motion between rotor and stator was developed in the present work. In such model, the gas-liquid bubbly flow pattern was considered, which is a very common situation in practice. The Eulerian-Eulerian approach, considering the homogeneous and inhomogeneous models, was employed and gas was treated taking into account an ideal gas state. The effects of the different gas volume fractions in pump volumetric eficiency, pressure distribution, power, slippage flow rate and volumetric flow rate were analyzed. The results shown that the developed model is capable of reproducing pump dynamic behaviour under the multiphase flow conditions early performed in experimental works

Simulador de escoamento multifásico em poços de petróleo (SEMPP)

The multiphase flow occurrence in the oil and gas industry is common throughout fluid path, production, transportation and refining. The multiphase flow is defined as flow simultaneously composed of two or more phases with different properties and immiscible. An important computational tool for the design, planning and optimization production systems is multiphase flow simulation in pipelines and porous media, usually made by multiphase flow commercial simulators. The main purpose of the multiphase flow simulators is predicting pressure and temperature at any point at the production system. This work proposes the development of a multiphase flow simulator able to predict the dynamic pressure and temperature gradient in vertical, directional and horizontal wells. The prediction of pressure and temperature profiles was made by numerical integration using marching algorithm with empirical correlations and mechanistic model to predict pressure gradient. The development of this tool involved set of routines implemented through software programming Embarcadero C++ Builder® 2010 version, which allowed the creation of executable file compatible with Microsoft Windows® operating systems. The simulator validation was conduct by computational experiments and comparison the results with the PIPESIM®. In general, the developed simulator achieved excellent results compared with those obtained by PIPESIM and can be used as a tool to assist production systems development