626 resultados para CNPQ::ENGENHARIAS::ENGENHARIA QUIMICA::TECNOLOGIA QUIMICA::PETROLEO E PETROQUIMICA


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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

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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

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In the present study we elaborated algorithms by using concepts from percolation theory which analyze the connectivity conditions in geological models of petroleum reservoirs. From the petrophysical parameters such as permeability, porosity, transmittivity and others, which may be generated by any statistical process, it is possible to determine the portion of the model with more connected cells, what the interconnected wells are, and the critical path between injector and source wells. This allows to classify the reservoir according to the modeled petrophysical parameters. This also make it possible to determine the percentage of the reservoir to which each well is connected. Generally, the connected regions and the respective minima and/or maxima in the occurrence of the petrophysical parameters studied constitute a good manner to characterize a reservoir volumetrically. Therefore, the algorithms allow to optimize the positioning of wells, offering a preview of the general conditions of the given model s connectivity. The intent is not to evaluate geological models, but to show how to interpret the deposits, how their petrophysical characteristics are spatially distributed, and how the connections between the several parts of the system are resolved, showing their critical paths and backbones. The execution of these algorithms allows us to know the properties of the model s connectivity before the work on reservoir flux simulation is started

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The artificial lifting of oil is needed when the pressure of the reservoir is not high enough so that the fluid contained in it can reach the surface spontaneously. Thus the increase in energy supplies artificial or additional fluid integral to the well to come to the surface. The rod pump is the artificial lift method most used in the world and the dynamometer card (surface and down-hole) is the best tool for the analysis of a well equipped with such method. A computational method using Artificial Neural Networks MLP was and developed using pre-established patterns, based on its geometry, the downhole card are used for training the network and then the network provides the knowledge for classification of new cards, allows the fails diagnose in the system and operation conditions of the lifting system. These routines could be integrated to a supervisory system that collects the cards to be analyzed

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This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is developed to reproduce the sensor output dynamic behavior, in such a way that its output is compared to the real sensor output. A recurrent neural network is used for this purpose, because of its ability to deal with dynamic information. The real sensor output and the estimated predictor output work as the basis for the creation of possible sensor fault detection and diagnosis strategies. Two competitive neural network architectures are investigated and their capabilities are used to classify different kinds of faults. The prediction algorithm and the fault detection classification strategies, as well as the obtained results, are presented

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The petrochemical industry has as objective obtain, from crude oil, some products with a higher commercial value and a bigger industrial utility for energy purposes. These industrial processes are complex, commonly operating with large production volume and in restricted operation conditions. The operation control in optimized and stable conditions is important to keep obtained products quality and the industrial plant safety. Currently, industrial network has been attained evidence when there is a need to make the process control in a distributed way. The Foundation Fieldbus protocol for industrial network, for its interoperability feature and its user interface organized in simple configuration blocks, has great notoriety among industrial automation network group. This present work puts together some benefits brought by industrial network technology to petrochemical industrial processes inherent complexity. For this, a dynamic reconfiguration system for intelligent strategies (artificial neural networks, for example) based on the protocol user application layer is proposed which might allow different applications use in a particular process, without operators intervention and with necessary guarantees for the proper plant functioning

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This work proposes an environment for programming programmable logic controllers applied to oil wells with BCP type method of artificially lifting. The environment will have an editor based in the diagram of sequential functions for programming of PLCs. This language was chosen due to the fact of being high-level and accepted by the international standard IEC 61131-3. The use of these control programs in real PLC will be possible with the use of an intermediate level of language based on XML specification PLCopen T6 XML. For the testing and validation of the control programs, an area should be available for viewing variables obtained through communication with a real PLC. Thus, the main contribution of this work is to develop a computational environment that allows: modeling, testing and validating the controls represented in SFC and applied in oil wells with BCP type method of artificially lifting

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Cementation operation consists in an extremely important work for the phases of perforation and completion of oil wells, causing a great impact on the well productivity. Several problems can occur with the cement during the primary cementation, as well as throughout the productive period. The corrective operations are frequent, but they are expensive and demands production time. Besides the direct cost, prejudices from the interruption of oil and gas production till the implementation of a corrective operation must be also taken into account. The purpose of this work is the development of an alternative cement paste constituted of Portland cement and porcelainized stoneware residue produced by ceramic industry in order to achieve characteristics as low permeability, high tenacity, and high mechanical resistance, capable of supporting various operations as production or oil wells recuperation. Four different concentration measures of hydrated paste were evaluated: a reference paste, and three additional ones with ceramic residue in concentrations of the order of 10%, 20% and 30% in relation to cement dough. High resistance and low permeability were found in high concentration of residues, as well as it was proved the pozolanic reactivity of the residue in relation to Portland cement, which was characterized through x-ray and thermogravimetry assays. It was evident the decrease of calcium hydroxide content, once it was substituted by formation of new hydrated products as it was added ceramic residue

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Exploration of heavy oil reservoirs is increasing every year in worldwide, because the discovery of light oil reservoirs is becoming increasingly rare. This fact has stimulated the research with the purpose of becoming viable, technically and economically, the exploration of such oil reserves. In Brazil, in special in the Northeast region, there is a large amount of heavy oil reservoir, where the recovery by the so called secondary methods Water injection or gas injection is inefficient or even impracticable in some reservoirs with high viscosity oils (heavy oils). In this scenario, steam injection appears as an interesting alternative for recover of these kinds of oil reservoirs. Its main mechanism consists of oil viscosity reduction through steam injection, increasing reservoir temperature. This work presents a parametric simulation study of some operational and reservoir variables that had influence on oil recovery in thin reservoirs typically found in Brazilian Northeast Basins, that use the steam injection as improved oil recovery method. To carry out simulations, it was used the commercial software STARS (Steam, Thermal, and Advanced Processes Reservoir Simulator) from CMG (Computer Modeling Group) version 2007.11. Reservoirs variables studied were horizontal permeability, vertical and horizontal permeability ratio, water zone and pay zone thickness ratio, pay zone thickness and thermal conductivity of the rock. Whereas, operational parameters studied were distance between wells and steam injection rate. Results showed that reservoir variables that had more influence on oil recovery were horizontal permeability and water zone and pay zone thickness ratio. In relation to operational variables, results showed that short distances between wells and low steam injection rates improved oil recovery

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Due to reservoirs complexity and significantly large reserves, heavy oil recovery has become one of the major oil industry challenges. Thus, thermal methods have been widely used as a strategic method to improve heavy oil recovery. These methods improve oil displacement through viscosity reduction, enabling oil production in fields which are not considered commercial by conventional recovery methods. Among the thermal processes, steam flooding is the most used today. One consequence in this process is gravity segregation, given by difference between reservoir and injected fluids density. This phenomenon may be influenced by the presence of reservoir heterogeneities. Since most of the studies are carried out in homogeneous reservoirs, more detailed studies of heterogeneities effects in the reservoirs during steam flooding are necessary, since most oil reservoirs are heterogeneous. This paper presents a study of reservoir heterogeneities and their influence in gravity segregation during steam flooding process. In this study some heterogeneous reservoirs with physical characteristics similar those found in the Brazilian Northeast Basin were analyzed. To carry out the simulations, it was used the commercial simulator STARS by CMG (Computer Modeling Group) - version 2007.11. Heterogeneities were modeled with lower permeability layers. Results showed that the presence of low permeability barriers can improve the oil recovery, and reduce the effects of gravity segregation, depending on the location of heterogeneities. The presence of these barriers have also increased the recovered fraction even with the reduction of injected steam rate

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The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis

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The biofilms microbial forms of association are responsible for generating, accelerating and / or induce the process of corrosion. The damage generated in the petroleum industry for this type of corrosion is significatives, representing major investment for your control. The aim of this study was to evaluate such tests antibiograms the effects of extracts of Jatropha curcas and essential oil of Lippia gracilis Schauer on microrganisms isolated from water samples and, thereafter, select the most effective natural product for further evaluation of biofilms formed in dynamic system. Extracts of J. curcas were not efficient on the complete inhibition of microbial growth in tests type antibiogram, and essential oil of L. gracilis Schauer most effective and determined for the other tests. A standard concentration of essential oil of 20 μL was chosen and established for the evaluation of the biofilms and the rate of corrosion. The biocide effect was determined by microbial counts of five types of microorganisms: aerobic bacteria, precipitating iron, total anaerobic, sulphate reducers (BRS) and fungi. The rate of corrosion was measured by loss of mass. Molecular identification and scanning electron microscopy (SEM) were performed. The data showed reduction to zero of the most probable number (MPN) of bacteria precipitating iron and BRS from 115 and 113 minutes of contact, respectively. There was also inhibited in fungi, reducing to zero the rate of colony-forming units (CFU) from 74 minutes of exposure. However, for aerobic and anaerobic bacteria there was no significant difference in the time of exposure to the essential oil, remaining constant. The rate of corrosion was also influenced by the presence of oil. The essential oil of L. gracilis was shown to be potentially effective

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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

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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