Análise paramétrica da simulação composicional do processo de Drenagem Gravitacional Assistida por Gás (GAGD)

In Brazil and around the world, oil companies are looking for, and expected development of new technologies and processes that can increase the oil recovery factor in mature reservoirs, in a simple and inexpensive way. So, the latest research has developed a new process called Gas Assisted Gravity Drainage (GAGD) which was classified as a gas injection IOR. The process, which is undergoing pilot testing in the field, is being extensively studied through physical scale models and core-floods laboratory, due to high oil recoveries in relation to other gas injection IOR. This process consists of injecting gas at the top of a reservoir through horizontal or vertical injector wells and displacing the oil, taking advantage of natural gravity segregation of fluids, to a horizontal producer well placed at the bottom of the reservoir. To study this process it was modeled a homogeneous reservoir and a model of multi-component fluid with characteristics similar to light oil Brazilian fields through a compositional simulator, to optimize the operational parameters. The model of the process was simulated in GEM (CMG, 2009.10). The operational parameters studied were the gas injection rate, the type of gas injection, the location of the injector and production well. We also studied the presence of water drive in the process. The results showed that the maximum vertical spacing between the two wells, caused the maximum recovery of oil in GAGD. Also, it was found that the largest flow injection, it obtained the largest recovery factors. This parameter controls the speed of the front of the gas injected and determined if the gravitational force dominates or not the process in the recovery of oil. Natural gas had better performance than CO2 and that the presence of aquifer in the reservoir was less influential in the process. In economic analysis found that by injecting natural gas is obtained more economically beneficial than CO2

Análise e desenvolvimento de controladores preditivos multivariáveis baseados em multi-modelos bilineares

This work addresses issues related to analysis and development of multivariable predictive controllers based on bilinear multi-models. Linear Generalized Predictive Control (GPC) monovariable and multivariable is shown, and highlighted its properties, key features and applications in industry. Bilinear GPC, the basis for the development of this thesis, is presented by the time-step quasilinearization approach. Some results are presented using this controller in order to show its best performance when compared to linear GPC, since the bilinear models represent better the dynamics of certain processes. Time-step quasilinearization, due to the fact that it is an approximation, causes a prediction error, which limits the performance of this controller when prediction horizon increases. Due to its prediction error, Bilinear GPC with iterative compensation is shown in order to minimize this error, seeking a better performance than the classic Bilinear GPC. Results of iterative compensation algorithm are shown. The use of multi-model is discussed in this thesis, in order to correct the deficiency of controllers based on single model, when they are applied in cases with large operation ranges. Methods of measuring the distance between models, also called metrics, are the main contribution of this thesis. Several application results in simulated distillation columns, which are close enough to actual behaviour of them, are made, and the results have shown satisfactory

Aplicação de sistemas multi-classificadores no diagnóstico de falhas em motores de indução trifásicos

Equipment maintenance is the major cost factor in industrial plants, it is very important the development of fault predict techniques. Three-phase induction motors are key electrical equipments used in industrial applications mainly because presents low cost and large robustness, however, it isn t protected from other fault types such as shorted winding and broken bars. Several acquisition ways, processing and signal analysis are applied to improve its diagnosis. More efficient techniques use current sensors and its signature analysis. In this dissertation, starting of these sensors, it is to make signal analysis through Park s vector that provides a good visualization capability. Faults data acquisition is an arduous task; in this way, it is developed a methodology for data base construction. Park s transformer is applied into stationary reference for machine modeling of the machine s differential equations solution. Faults detection needs a detailed analysis of variables and its influences that becomes the diagnosis more complex. The tasks of pattern recognition allow that systems are automatically generated, based in patterns and data concepts, in the majority cases undetectable for specialists, helping decision tasks. Classifiers algorithms with diverse learning paradigms: k-Neighborhood, Neural Networks, Decision Trees and Naïves Bayes are used to patterns recognition of machines faults. Multi-classifier systems are used to improve classification errors. It inspected the algorithms homogeneous: Bagging and Boosting and heterogeneous: Vote, Stacking and Stacking C. Results present the effectiveness of constructed model to faults modeling, such as the possibility of using multi-classifiers algorithm on faults classification

Acompanhamento coletivo do crescimento e desenvolvimento infantil: participação de mães/cuidadores

This study aimed to analyze the participation of mothers/caregivers from the perspective of the health care model that directs the collective monitoring of child growth and development. This is an exploratory and descriptive research with qualitative approach, carried out in two Family Health Units located in the city of Natal/RN. Data were collected between August and September 2014, through participant observation and semi-structured interview technique, with mothers of infants seen at follow-up visits collective child growth and development. A total of 13 mothers were included who met the following inclusion criteria: being a mother/caregiver responsible for the care of children who have attended one or more meeting of collective monitoring of child growth and development. Exclusion criteria was established: users outside the area covered by the Health Unit Family and who did not use the National Health System as the primary health care service. For the treatment of the collected material, the content analysis was used, thematic Bardin. The study followed the ethical and legal principles governing the scientific research on human subjects recommended by Resolution nº. 466/2012 of the National Health Council and its realization occurred with the approval of the project in the Research Ethics Committee of the Federal University of Rio Grande do North, which was approved by Opinion Embodied nº. 719 949, of June 27, 2014, and Certificate Presentation of Findings Ethics No 32510514.7.0000.5537. Although not conceptualize theoretically mothers demonstrated that collective consultations of child growth and development are actions aimed at health surveillance model, since most pointed monitoring your child to actions that can be measured. Even with that, it was established the existence of health promotion actions by reporting the exchange of experience and leadership of the subjects in collective action, factor facilitated by the link established between users and professionals and users. In this action there is the induction of permanent horizontal relationship where we seek to combine popular knowledge to scientific knowledge in order to promote the integral care for the child. However, it is still possible to find professionals who directs its assistance only to pathological processes and fail to create comprehensive care alternatives. In addition, there is still embezzlement in multi that should provide care to the child population. This factor may be related to their professional training, and thus an issue that can last for a few years. We conclude that it is necessary to incorporate alternatives and models of care that support overcoming limitations and enhancing the health of the population, involving it in the prospect of a better quality of life and therefore health.

Análise paramétrica da simulação composicional do processo de Drenagem Gravitacional Assistida por Gás (GAGD)

In Brazil and around the world, oil companies are looking for, and expected development of new technologies and processes that can increase the oil recovery factor in mature reservoirs, in a simple and inexpensive way. So, the latest research has developed a new process called Gas Assisted Gravity Drainage (GAGD) which was classified as a gas injection IOR. The process, which is undergoing pilot testing in the field, is being extensively studied through physical scale models and core-floods laboratory, due to high oil recoveries in relation to other gas injection IOR. This process consists of injecting gas at the top of a reservoir through horizontal or vertical injector wells and displacing the oil, taking advantage of natural gravity segregation of fluids, to a horizontal producer well placed at the bottom of the reservoir. To study this process it was modeled a homogeneous reservoir and a model of multi-component fluid with characteristics similar to light oil Brazilian fields through a compositional simulator, to optimize the operational parameters. The model of the process was simulated in GEM (CMG, 2009.10). The operational parameters studied were the gas injection rate, the type of gas injection, the location of the injector and production well. We also studied the presence of water drive in the process. The results showed that the maximum vertical spacing between the two wells, caused the maximum recovery of oil in GAGD. Also, it was found that the largest flow injection, it obtained the largest recovery factors. This parameter controls the speed of the front of the gas injected and determined if the gravitational force dominates or not the process in the recovery of oil. Natural gas had better performance than CO2 and that the presence of aquifer in the reservoir was less influential in the process. In economic analysis found that by injecting natural gas is obtained more economically beneficial than CO2