467 resultados para Consórcio Brasileiro de Pesquisa e Desenvolvimento do Café
Resumo:
The thermoelectric energy conversion can be performed directly on generators without moving parts, using the principle of SEEBECK effect, obtained in junctions of drivers' thermocouples and most recently in semiconductor junctions type p-n which have increased efficiency of conversion. When termogenerators are exposed to the temperature difference (thermal gradient) eletromotriz a force is generated inducing the appearance of an electric current in the circuit. Thus, it is possible to convert the heat of combustion of a gas through a burner in power, being a thermoelectric generator. The development of infrared burners, using porous ceramic plate, is possible to improve the efficiency of heating, and reduce harmful emissions such as CO, CO2, NOx, etc.. In recent years the meliorate of thermoelectric modules semiconductor (TEG's) has stimulated the development of devices generating and recovery of thermal irreversibility of thermal machines and processes, improving energy efficiency and exergy these systems, especially processes that enable the cogeneration of energy. This work is based on the construction and evaluation of a prototype in a pilot scale, for energy generation to specific applications. The unit uses a fuel gas (LPG) as a primary energy source. The prototype consists of a porous plate burner infrared, an adapter to the module generator, a set of semiconductor modules purchased from Hi-Z Inc. and a heat exchanger to be used as cold source. The prototype was mounted on a test bench, using a system of acquisition of temperature, a system of application of load and instrumentation to assess its functioning and performance. The prototype had an efficiency of chemical conversion of 0.31% for electrical and heat recovery for cogeneration of about 33.2%, resulting in an overall efficiency of 33.51%. The efficiency of energy exergy next shows that the use of primary energy to useful fuel was satisfactory, although the proposed mechanism has also has a low performance due to underuse of the area heated by the small number of modules, as well as a thermal gradient below the ideal informed by the manufacturer, and other factors. The test methodology adopted proved to be suitable for evaluating the prototype
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In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means
Resumo:
Among the many types of noise observed in seismic land acquisition there is one produced by surface waves called Ground Roll that is a particular type of Rayleigh wave which characteristics are high amplitude, low frequency and low velocity (generating a cone with high dip). Ground roll contaminates the relevant signals and can mask the relevant information, carried by waves scattered in deeper regions of the geological layers. In this thesis, we will present a method that attenuates the ground roll. The technique consists in to decompose the seismogram in a basis of curvelet functions that are localized in time, in frequency, and also, incorporate an angular orientation. These characteristics allow to construct a curvelet filter that takes in consideration the localization of denoise in scales, times and angles in the seismogram. The method was tested with real data and the results were very good
Resumo:
The objective of reservoir engineering is to manage fields of oil production in order to maximize the production of hydrocarbons according to economic and physical restrictions. The deciding of a production strategy is a complex activity involving several variables in the process. Thus, a smart system, which assists in the optimization of the options for developing of the field, is very useful in day-to-day of reservoir engineers. This paper proposes the development of an intelligent system to aid decision making, regarding the optimization of strategies of production in oil fields. The intelligence of this system will be implemented through the use of the technique of reinforcement learning, which is presented as a powerful tool in problems of multi-stage decision. The proposed system will allow the specialist to obtain, in time, a great alternative (or near-optimal) for the development of an oil field known
Resumo:
One of the main activities in the petroleum engineering is to estimate the oil production in the existing oil reserves. The calculation of these reserves is crucial to determine the economical feasibility of your explotation. Currently, the petroleum industry is facing problems to analyze production due to the exponentially increasing amount of data provided by the production facilities. Conventional reservoir modeling techniques like numerical reservoir simulation and visualization were well developed and are available. This work proposes intelligent methods, like artificial neural networks, to predict the oil production and compare the results with the ones obtained by the numerical simulation, method quite a lot used in the practice to realization of the oil production prediction behavior. The artificial neural networks will be used due your learning, adaptation and interpolation capabilities
Resumo:
The transport of fluids through pipes is used in the oil industry, being the pipelines an important link in the logistics flow of fluids. However, the pipelines suffer deterioration in their walls caused by several factors which may cause loss of fluids to the environment, justifying the investment in techniques and methods of leak detection to minimize fluid loss and environmental damage. This work presents the development of a supervisory module in order to inform to the operator the leakage in the pipeline monitored in the shortest time possible, in order that the operator log procedure that entails the end of the leak. This module is a component of a system designed to detect leaks in oil pipelines using sonic technology, wavelets and neural networks. The plant used in the development and testing of the module presented here was the system of tanks of LAMP, and its LAN, as monitoring network. The proposal consists of, basically, two stages. Initially, assess the performance of the communication infrastructure of the supervisory module. Later, simulate leaks so that the DSP sends information to the supervisory performs the calculation of the location of leaks and indicate to which sensor the leak is closer, and using the system of tanks of LAMP, capture the pressure in the pipeline monitored by piezoresistive sensors, this information being processed by the DSP and sent to the supervisory to be presented to the user in real time
Resumo:
On Rio Grande do Norte northern coast the process of sediment transport are intensely controlled by wind and sea (waves and currents) action, causing erosion and shoreline morphological instability. Due to the importance of such coastal zone it was realized the multi-spectral mapping and physical-chemical characterization of mudflats and mangroves aiming to support the mitigating actions related to the containment of the erosive process on the oil fields of Macau and Serra installed at the study area. The multi-spectral bands of 2000 and 2008 LANDSAT 5 TM images were submitted on the several digital processing steps and RGB color compositions integrating spectral bands and Principal Components. Such processing methodology was important to the mapping of different units on surface, together with field works. It was possible to make an analogy of the spectral characteristics of wetlands with vegetations areas (mangrove), showing the possibility to make a restoration of this area, contributing with the environmental monitoring of that ecosystem. The maps of several units were integrated in GIS environment at 1:60,000 scale, including the classification of features according to the presence or absence of vegetation cover. Thus, the strategy of methodology established that there are 10.13 km2 at least of sandy-muddy and of these approximately 0.89 km2 with the possibility to be used in a reforestation of typical flora of mangrove. The physical-chemical characterization showed areas with potential to introduce local species of mangrove and they had a pH above neutral with a mean of 8.4. The characteristic particle size is sand in the fine fractions, the high levels of carbonate, organic matter and major and trace element in general are concentrated where the sediment had the less particles size, showing the high correlation that those elements have with smaller particles of sediment. The application of that methodological strategy is relevant to the better understanding of features behavior and physical-chemical data of sediment samples collected on field allow the analysis of efficiency/capability of sandy-muddy to reforestation with local mangrove species for mitigation of the erosive action and coastal processes on the areas occupied by the oil industry
Resumo:
This work presents a proposal to detect interface in atmospheric oil tanks by installing a differential pressure level transmitter to infer the oil-water interface. The main goal of this project is to maximize the quantity of free water that is delivered to the drainage line by controlling the interface. A Fuzzy Controller has been implemented by using the interface transmitter as the Process Variable. Two ladder routine was generated to perform the control. One routine was developed to calculate the error and error variation. The other was generate to develop the fuzzy controller itself. By using rules, the fuzzy controller uses these variables to set the output. The output is the position variation of the drainage valve. Although the ladder routine was implemented into an Allen Bradley PLC, Control Logix family it can be implemented into any brand of PLCs
Resumo:
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
Resumo:
The oscillations presents in control loops can cause damages in petrochemical industry. Canceling, or even preventing such oscillations, would save up to large amount of dollars. Studies have identified that one of the causes of these oscillations are the nonlinearities present on industrial process actuators. This study has the objective to develop a methodology for removal of the harmful effects of nonlinearities. Will be proposed an parameter estimation method to Hammerstein model, whose nonlinearity is represented by dead-zone or backlash. The estimated parameters will be used to construct inverse models of compensation. A simulated level system was used as a test platform. The valve that controls inflow has a nonlinearity. Results and describing function analysis show an improvement on system response
Resumo:
This work aims to study the fluctuation structure of physical properties of oil well profiles. It was used as technique the analysis of fluctuations without trend (Detrended Fluctuation Analysis - DFA). It has been made part of the study 54 oil wells in the Campo de Namorado located in the Campos Basin in Rio de Janeiro. We studied five sections, namely: sonic, density, porosity, resistivity and gamma rays. For most of the profiles , DFA analysis was available in the literature, though the sonic perfile was estimated with the aid of a standard algorithm. The comparison between the exponents of DFA of the five profiles was performed using linear correlation of variables, so we had 10 comparisons of profiles. Our null hypothesis is that the values of DFA for the various physical properties are independent. The main result indicates that no refutation of the null hypothesis. That is, the fluctuations observed by DFA in the profiles do not have a universal character, that is, in general the quantities display a floating structure of their own. From the ten correlations studied only the profiles of density and sonic one showed a significant correlation (p> 0.05). Finally these results indicate that one should use the data from DFA with caution, because, in general, based on geological analysis DFA different profiles can lead to disparate conclusions
Resumo:
The use of infrared burners in industrial applications has many advantages in terms of technical-operational, for example, uniformity in the heat supply in the form of radiation and convection, with greater control of emissions due to the passage of exhaust gases through a macro-porous ceramic bed. This paper presents an infrared burner commercial, which was adapted an experimental ejector, capable of promoting a mixture of liquefied petroleum gas (LPG) and glycerin. By varying the percentage of dual-fuel, it was evaluated the performance of the infrared burner by performing an energy balance and atmospheric emissions. It was introduced a temperature controller with thermocouple modulating two-stage (low heat / high heat), using solenoid valves for each fuel. The infrared burner has been tested and tests by varying the amount of glycerin inserted by a gravity feed system. The method of thermodynamic analysis to estimate the load was used an aluminum plate located at the exit of combustion gases and the distribution of temperatures measured by a data acquisition system which recorded real-time measurements of the thermocouples attached. The burner had a stable combustion at levels of 15, 20 and 25% of adding glycerin in mass ratio of LPG gas, increasing the supply of heat to the plate. According to data obtained showed that there was an improvement in the efficiency of the 1st Law of infrared burner with increasing addition of glycerin. The emission levels of greenhouse gases produced by combustion (CO, NOx, SO2 and HC) met the environmental limits set by resolution No. 382/2006 of CONAMA
Resumo:
With the high oil price variability, the petroleum and the reservoir engineers are usually face to face on how they can evaluate the well performance and productivity. They can improve high productivity from the well construction to the secondary recoveries, but they have never tried a measurement in the drilling operations about the lower productivity index. As a rule, frequently the drilling operations hear from the reservoir engineering and geology that, if there is a formation damage, probably some drilling operations practices were not done properly or the good practice in petroleum engineering or mud engineering were not observed. The study in this working search is an attempt of how to measure a formation damage just from the project drilling to the drilling operations, with datum from the fields in Brazilian northeast and putting into practice a Simulator developed from the modeling on the theory offered by different experts and sources in formation damage
Resumo:
A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um sistema SISO (Single Input - Single Output). O controle de pH é um processo de grande importância na indústria petroquímica, onde se deseja manter constante o nível de acidez de um produto ou neutralizar o afluente de uma planta de tratamento de fluidos. O processo de controle de pH exige robustez do sistema de controle, pois este processo pode ter ganho estático e dinâmica nãolineares. O controlador preditivo neural envolve duas outras teorias para o seu desenvolvimento, a primeira referente ao controle preditivo e a outra a redes neurais artificiais (RNA s). Este controlador pode ser dividido em dois blocos, um responsável pela identificação e outro pelo o cálculo do sinal de controle. Para realizar a identificação neural é utilizada uma RNA com arquitetura feedforward multicamadas com aprendizagem baseada na metodologia da Propagação Retroativa do Erro (Error Back Propagation). A partir de dados de entrada e saída da planta é iniciado o treinamento offline da rede. Dessa forma, os pesos sinápticos são ajustados e a rede está apta para representar o sistema com a máxima precisão possível. O modelo neural gerado é usado para predizer as saídas futuras do sistema, com isso o otimizador calcula uma série de ações de controle, através da minimização de uma função objetivo quadrática, fazendo com que a saída do processo siga um sinal de referência desejado. Foram desenvolvidos dois aplicativos, ambos na plataforma Builder C++, o primeiro realiza a identificação, via redes neurais e o segundo é responsável pelo controle do processo. As ferramentas aqui implementadas e aplicadas são genéricas, ambas permitem a aplicação da estrutura de controle a qualquer novo processo
Resumo:
The production of heavy oil fields, typical in the Northeastern region, is commonly stimulated by steam injection. High bottom hole temperatures are responsible not only for the development of deleterious stresses of the cement sheath but also for cement strength retrogression. To overcome this unfavorable scenario, polymeric admixtures can be added to cement slurries to improve its fracture energy and silica flour to prevent strength retrogression. Therefore, the objective of the present study was to investigate the effect of the addition of different concentrations of polyurethane (5-25%) to cement slurries containing 40% BWOC silica flour. The resulting slurries were characterized using standard API (American Petroleum Institute) laboratory tests. In addition to them, the mechanical properties of the slurries, including elastic modulus and microhardness were also evaluated. The results revealed that density, free water and stability of the composite cement/silica/polyurethane slurries were within acceptable limits. The rheological behavior of the slurries, including plastic viscosity, yield strength and gel strength increased with the addition of 10% BWOC polyurethane. The presence of polyurethane reduced the fluid loss of the slurries as well as their elastic modulus. Composite slurries also depicted longer setting times due to the presence of the polymer. As expected, both the mechanical strength and microhardness of the slurries decreased with the addition of polyurethane. However, at high bottom hole temperatures, the strength of the slurries containing silica and polyurethane was far superior than that of plain cement slurries. In summary, the use of polyurethane combined with silica is an interesting solution to better adequate the mechanical behavior of cement slurries to heavy oil fields subjected to steam injection