Modelagem analítica e experimental da filtração em meios porosos

Deep bed filtration occurs in several industrial and environmental processes like water filtration and soil contamination. In petroleum industry, deep bed filtration occurs near to injection wells during water injection, causing injectivity reduction. It also takes place during well drilling, sand production control, produced water disposal in aquifers, etc. The particle capture in porous media can be caused by different physical mechanisms (size exclusion, electrical forces, bridging, gravity, etc). A statistical model for filtration in porous media is proposed and analytical solutions for suspended and retained particles are derived. The model, which incorporates particle retention probability, is compared with the classical deep bed filtration model allowing a physical interpretation of the filtration coefficients. Comparison of the obtained analytical solutions for the proposed model with the classical model solutions allows concluding that the larger the particle capture probability, the larger the discrepancy between the proposed and the classical models

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

Planejamento experimental aplicada a um novo separador líquido-líquido utilizado no tratamento de águas residuais contaminadas com petróleo

The present work had as objective to apply an experimental planning aiming at to improve the efficiency of separation of a new type of mixer-settler applied to treat waste water contaminated with oil. An unity in scale of laboratory, was installed in the Post-graduation Program of Chemical Engineering of UFRN. It was constructed in partnership with Petrobras S.A. This called device Misturador-Decantador a Inversão de Fases (MDIF) , possess features of conventional mixer-settler and spray column type. The equipment is composed of three main parts: mixing chamber; chamber of decantation and chamber of separation. The efficiency of separation is evaluated analyzing the oil concentrations in water in the feed and the output of the device. For the analysis one used the gravimetric method of oil and greases analysis (TOG). The system in study is a water of formation emulsified with oil. The used extractant is a mixture of Turpentine spirit hydro-carbons, supplied for Petrobras. It was applied, for otimization of the efficiency of separation of the equipment, an experimental planning of the composite central type, having as factorial portion fractionary factorial planning 2 5-2, with the magnifying of the type star and five replications in the central point. In this work, the following independents variables were studied: contents of oil in the feed of the device; volumetric ratio (O/A); total flowrate ; agitation in the mixing chamber and height of the organic bed. Minimum and maximum limits for the studied variables had been fixed according previous works. The analysis of variance for the equation of the empirical model, revealed statistically significant and useful results for predictions ends. The variance analysis also presented the distribution of the error as a normal distribution and was observed that as the dispersions do not depend on the levels of the factors, the independence assumption can be verified. The variation around the average is explained by 98.98%, or either, equal to the maximum value, being the smoothing of the model in relation to the experimental points of 0,98981. The results present a strong interaction between the variable oil contents in the feed and agitation in the mixing chamber, having great and positive influence in the separation efficiency. Another variable that presented a great positive influence was the height of the organic bed. The best results of separation efficiency had been obtained for high flowrates when associates the high oil concentrations and high agitation. The results of the present work had shown excellent agreement with the results carried out through previous works with the mixer-settler of phase inversion

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.

Estudo da secagem do feijão verde (Vigna unguiculata L. Walp) - análise experimental do processo combinado leito fixo/leito de jorro

Green bean is considered as one of most traditional Brazilian Northeast dishes. Green beans drying preliminary experiments show that combine processes, fixed-bed/spouted bed, resulted in dehydrated beans with uniform humidity and the recovery of the beans properties after their rehydration. From this assays was defined an initial humidity suited for the spouted bed process. A fixed-bed pre-drying process until a level of 40% humidity gave the best results. The spouted bed characteristic hydrodynamic curves were presented for different beans loads, where changes in the respective beans physical properties were evidenced during the fluidynamic assay, due simultaneous drying process. One 22 factorial experimental design was carried out with three repetition in the central point, considering as entry variables: drying air velocity and temperature. The response variables were the beans brakeage, water fraction evaporated during 20 and 50 minutes of drying and the humidity ratio. They are presented still the modeling of the drying of the green beans in fine layer in the drier of tray and the modeling of the shrinking of the beans of the drying processes fixed-bed and spouted bed

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

Estudo experimental e modelagem do processo de sacarificação e fermentação simultânea utilizando bagaço de cana-de-açúcar para produção de etanol

Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq

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.

Modelagem analítica e experimental da filtração em meios porosos

Deep bed filtration occurs in several industrial and environmental processes like water filtration and soil contamination. In petroleum industry, deep bed filtration occurs near to injection wells during water injection, causing injectivity reduction. It also takes place during well drilling, sand production control, produced water disposal in aquifers, etc. The particle capture in porous media can be caused by different physical mechanisms (size exclusion, electrical forces, bridging, gravity, etc). A statistical model for filtration in porous media is proposed and analytical solutions for suspended and retained particles are derived. The model, which incorporates particle retention probability, is compared with the classical deep bed filtration model allowing a physical interpretation of the filtration coefficients. Comparison of the obtained analytical solutions for the proposed model with the classical model solutions allows concluding that the larger the particle capture probability, the larger the discrepancy between the proposed and the classical models

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