Análise da modelagem experimental da perda de injetividade

Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different

Implementação experimental de filtro ativo paralelo de potência com aplicação a gerador de indução trifásico

This work describes the experimental implementation of a shunt active power filter applied to a three-phase induction generator. The control strategy of active filter turned to the excitation control of the machine and to decrease the harmonics in the generator output current. Involved the implementation of a digital PWM switching, and was made a comparison of two techniques for obtaining the reference currents. The first technique is based on the synchronous dq reference method and the second on the theory of instantaneous power. The comparison is performed via simulation and experimental results. To obtain the experimental results, was mounted a bench trial and the control and communications needed were implemented using DSP - MS320F2812. The simulation results and experimental data proved the efficiency of the filter to apply, highlighting the technique of instantaneous power

Determinação experimental e modelagem termodinâmica do ponto de turbidez de sistemas aquosos com tensoativos nonilfenolpolietoxilados

The nonionic surfactants are composed of substances whose molecules in solution, does not ionize. The solubility of these surfactants in water due to the presence of functional groups that have strong affinity for water. When these surfactants are heated is the formation of two liquid phases, evidenced by the phenomenon of turbidity. This study was aimed to determine the experimental temperature and turbidity nonilfenolpoliethoxyled subsequently perform a thermodynamic modeling, considering the models of Flory-Huggins and the empirical solid-liquid equilibrium (SLE). The method used for determining the turbidity point was the visual method (Inoue et al., 2008). The experimental methodology consisted of preparing synthetic solutions of 0,25%, 0,5%, 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 12,5%, 15%, 17% and 20% by weight of surfactant. The nonionic surfactants used according to their degree of ethoxylation (9.5, 10, 11, 12 and 13). During the experiments the solutions were homogenized and the bath temperature was gradually increased while the turbidity of the solution temperature was checked visually Inoue et al. (2003). These temperature data of turbidity were used to feed the models evaluated and obtain thermodynamic parameters for systems of surfactants nonilfenolpoliethoxyled. Then the models can be used in phase separation processes, facilitating the extraction of organic solvents, therefore serve as quantitative and qualitative parameters. It was observed that the solidliquid equilibrium model (ESL) was best represented the experimental data.

Comparação entre planejamento estatístico experimental e análise dimensional em operações de mistura e separação para sistema óleo-água

This work aims to determine a better methodology to help predicting some operational parameters to a new design of mixer-settler on treating wastewater produced by petroleum industry, called MDIF (Misturador-Decantador à Inversão de Fases/ Mixer-Settler based on Phase Inversion MSPI). The data from this research were obtained from the wastewater treatment unit, called MSPI-TU, installed on a wastewater treatment plant (WTP) of PETROBRAS/UO-RNCE. The importance in determining the better methodology to predict the results of separation and extraction efficiency of the equipment, contributes significantly to determine the optimum operating variables for the control of the unit. The study was based on a comparison among the experimental efficiency (E) obtained by operating MSPI-TU, the efficiency obtained by experimental design equation (Eplan) from the software Statistica Experimental Design® (version 7.0), and the other obtained from a modeling equation based on a dimensional analysis (Ecalc). The results shows that the experimental design equation gives a good prediction of the unit efficiencies with better data reliability, regarding to the condition before a run operation. The average deviation between the proposed by statistic planning model equation and experimental data was 0.13%. On the other hand, the efficiency calculated by the equation which represents the dimensional analysis, may result on important relative deviations (up 70%). Thus, the experimental design is confirmed as a reliable tool, with regard the experimental data processing of the MSPI-TU

Metodologia númerico-experimental para avaliação da espessura de filmes de nitreto de titânio obtidos por processamento a plasma

In recent decades, changes in the surface properties of materials have been used to improve their tribological characteristics. However, this improvement depends on the process, treatment time and, primarily, the thickness of this surface film layer. Physical vapor deposition (PVD) of titanium nitrate (TiN) has been used to increase the surface hardness of metallic materials. Thus, the aim of the present study was to propose a numerical-experimental method to assess the film thickness (l) of TiN deposited by PVD. To reach this objective, experimental results of hardness (H) assays were combined with a numerical simulation to study the behavior of this property as a function of maximum penetration depth of the indenter (hmax) into the film/substrate conjugate. Two methodologies were adopted to determine film thickness. The first consists of the numerical results of the H x hmax curve with the experimental curve obtained by the instrumental indentation test. This methodology was used successfully in a TiN-coated titanium (Ti) conjugate. A second strategy combined the numerical results of the Hv x hmax curve with Vickers experimental hardness data (Hv). This methodology was applied to a TiN-coated M2 tool steel conjugate. The mechanical properties of the materials studied were also determined in the present study. The thicknesses results obtained for the two conjugates were compatible with their experimental data.

Modelagem matemática e experimental da perda de injetividade em poços canhoneados

Water injection in oil reservoirs is a recovery technique widely used for oil recovery. However, the injected water contains suspended particles that can be trapped, causing formation damage and injectivity decline. In such cases, it is necessary to stimulate the damaged formation looking forward to restore the injectivity of the injection wells. Injectivity decline causes a major negative impact to the economy of oil production, which is why, it is important to foresee the injectivity behavior for a good waterflooding management project. Mathematical models for injectivity losses allow studying the effect of the injected water quality, also the well and formation characteristics. Therefore, a mathematical model of injectivity losses for perforated injection wells was developed. The scientific novelty of this work relates to the modeling and prediction of injectivity decline in perforated injection wells, considering deep filtration and the formation of external cake in spheroidal perforations. The classic modeling for deep filtration was rewritten using spheroidal coordinates. The solution to the concentration of suspended particles was obtained analytically and the concentration of the retained particles, which cause formation damage, was solved numerically. The acquisition of the solution to impedance assumed a constant injection rate and the modified Darcy´s Law, defined as being the inverse of the normalized injectivity by the inverse of the initial injectivity. Finally, classic linear flow injectivity tests were performed within Berea sandstone samples, and within perforated samples. The parameters of the model, filtration and formation damage coefficients, obtained from the data, were used to verify the proposed modeling. The simulations showed a good fit to the experimental data, it was observed that the ratio between the particle size and pore has a large influence on the behavior of injectivity decline.

Análise da modelagem experimental da perda de injetividade

Injectivity decline, which can be caused by particle retention, generally occurs during water injection or reinjection in oil fields. Several mechanisms, including straining, are responsible for particle retention and pore blocking causing formation damage and injectivity decline. Predicting formation damage and injectivity decline is essential in waterflooding projects. The Classic Model (CM), which incorporates filtration coefficients and formation damage functions, has been widely used to predict injectivity decline. However, various authors have reported significant discrepancies between Classical Model and experimental results, motivating the development of deep bed filtration models considering multiple particle retention mechanisms (Santos & Barros, 2010; SBM). In this dissertation, inverse problem solution was studied and a software for experimental data treatment was developed. Finally, experimental data were fitted using both the CM and SBM. The results showed that, depending on the formation damage function, the predictions for injectivity decline using CM and SBM models can be significantly different