Otimização de vazão de poços injetores em projeto de injeção de água utilizando simulação por linhas de fluxo

Until the early 90s, the simulation of fluid flow in oil reservoir basically used the numerical technique of finite differences. Since then, there was a big development in simulation technology based on streamlines, so that nowadays it is being used in several cases and it can represent the physical mechanisms that influence the fluid flow, such as compressibility, capillarity and gravitational segregation. Streamline-based flow simulation is a tool that can help enough in waterflood project management, because it provides important information not available through traditional simulation of finite differences and shows, in a direct way, the influence between injector well and producer well. This work presents the application of a methodology published in literature for optimizing water injection projects in modeling of a Brazilian Potiguar Basin reservoir that has a large number of wells. This methodology considers changes of injection well rates over time, based on information available through streamline simulation. This methodology reduces injection rates in wells of lower efficiency and increases injection rates in more efficient wells. In the proposed model, the methodology was effective. The optimized alternatives presented higher oil recovery associated with a lower water injection volume. This shows better efficiency and, consequently, reduction in costs. Considering the wide use of the water injection in oil fields, the positive outcome of the modeling is important, because it shows a case study of increasing of oil recovery achieved simply through better distribution of water injection rates

Controle preditivo bilinear aplicado a um motor de indução

The present work is based on the applied bilinear predictive control applied to an induction motor. As in particular case of the technique based on predictive control in nonlinem systems, these have desperted great interest, a time that present the advantage of being simpler than the non linear in general and most representative one than the linear one. One of the methods, adopted here, uses the linear model "quasi linear for step of time" based in Generalized Predictive Control. The modeling of the induction motor is made by the Vectorial control with orientation given for the indirect rotor. The system is formed by an induction motor of 3 cv with rotor in squirregate, set in motion for a group of benches of tests developed for this work, presented resulted for a variation of +5% in the value of set-point and for a variation of +10% and -10% in the value of the applied nominal load to the motor. The results prove a good efficiency of the predictive bilinear controllers, then compared with the linear cases

Sistema Híbrido de Inferência Baseado em Análise de Componentes Principais e Redes Neurais Artificiais Aplicado a Plantas de Processamento de Gás Natural

Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study

Ecologia humana e manejo participativo da pesca do búzio Anomalocardia brasiliana (Gmelin, 1791) (Bivalvia: Veneridae) na Reserva de Desenvolvimento Sustentável Estadual Ponta do Tubarão (RN)

Coastal and marine protected areas are created to protect habitat, avoid biodiversity loss, and to help maintain viable fisheries. However, most of these areas in tropical countries occurs in impoverished regions and directly affect the livelihood and survival of coastal communities which directly depend on fisheries and shellfisheries. Therefore, socioeconomic and conservation goals overlap. In this context, fishers should have a central place in resource management. They are critical resource users and their behavior directly affects the system. Shellfish resources are important sources of food, employment and income to fishing communities in Latin America. But despite its widespread use for food and income, there is an urgent need of more research on shellfish management. This research discusses the artisanal fisheries of Venus clam (Anomalocardia brasiliana) (Gmelin, 1791) (Bivalvia: Veneridae) in Brazil, and points out strategies to improve the system. Venus clam is a small and commonly exploited species for food and income on the Brazilian coast. This research was carried out at Ponta do Tubarão Sustainable Development Reserve (Brazilian Northeast coast), where there was no information available about who harvest, where or how much Venus clam has been harvested, despite this resource being exploited for generations. Clam fishery follows the pattern of socio-economic invisibility that general clam exploitation has in Brazil. Methods used were interviews, participatory monitoring and focal follow observation from January 2010 to May 2011. Results include: (a) the identification of shell fishers, (b) how harvest and meat processing are performed (mollusk beds, time spent, gross and net production), (c) the analisis of shell fisher income and their economic sustentability, and (d) the involvement of shell fisher families in data gathering and analyses for the first time. Based on the acquired knowledge, we propose a new institutional arrangement for clam fishery including co-management, fisheries agreement, compensatory arrangements and improvements for the Venus clam value chain such as the establishment of a minimum price for clam meat. This research also includes two other results: a general description for Venus clam harvesting in the Brazilian Northeast coast and a specific discussion about co-management of Venus clam in Brazil. The first one was possible through the meeting of several shell fisherwomen from other states during activities promoted by People of the Tides (PoT) project. PoT was an international initiative aiming to develop coastal communities that depend on mollusk for their livelihood. The second one is a comparison between PoT and Venus clam management at Pirajubaé Marine Extractive Reserve (Santa Catarina). It evaluates the success and failures of these only two initiatives involving co-management of A. brasiliana in Brazil

Otimização de vazão de poços injetores em projeto de injeção de água utilizando simulação por linhas de fluxo

Until the early 90s, the simulation of fluid flow in oil reservoir basically used the numerical technique of finite differences. Since then, there was a big development in simulation technology based on streamlines, so that nowadays it is being used in several cases and it can represent the physical mechanisms that influence the fluid flow, such as compressibility, capillarity and gravitational segregation. Streamline-based flow simulation is a tool that can help enough in waterflood project management, because it provides important information not available through traditional simulation of finite differences and shows, in a direct way, the influence between injector well and producer well. This work presents the application of a methodology published in literature for optimizing water injection projects in modeling of a Brazilian Potiguar Basin reservoir that has a large number of wells. This methodology considers changes of injection well rates over time, based on information available through streamline simulation. This methodology reduces injection rates in wells of lower efficiency and increases injection rates in more efficient wells. In the proposed model, the methodology was effective. The optimized alternatives presented higher oil recovery associated with a lower water injection volume. This shows better efficiency and, consequently, reduction in costs. Considering the wide use of the water injection in oil fields, the positive outcome of the modeling is important, because it shows a case study of increasing of oil recovery achieved simply through better distribution of water injection rates