999 resultados para pesquisa e desenvolvimento
Resumo:
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
Resumo:
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
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
Resumo:
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
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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:
Produced water is the main effluent linked to the activity of extraction of oil and their caring management is necessary due to the large volume involved, to ensure to minimize the negative impacts of discharges of these waters in the environment. This study aimed to analyze the use of retorted shale, which is a reject from the pyrolysis of pirobituminous shale, as adsorbent for the removal of phenols in produced water. The material was characterized by different techniques (grain sized analysis, thermal analysis, BET, FRX, FT-IR, XRD and SEM), showing the heterogeneity in their composition, showing its potential for the removal of varied compounds, as well as the phenols and their derivatives. For the analysis of the efficiency of the oil shale for the adsorption process, assays of adsorption balance were carried through, and also kinetic studies and dynamics adsorption, in the ETE of the UTPF of Petrobras, in Guamaré-RN. The balance assays shown a bigger conformity with the model of Langmuir and the kinetic model more adjusted to describe the adsorption of phenols in retorted shale was of pseudo-second order. The retorted shale presented a low capacity of adsorption of phenols (1,3mg/g), when related to others conventional adsorbents, however it is enough to the removal of these composites in concentrations presented in the produced water of the UTPF of Guamaré. The assays of dynamics adsorption in field had shown that the concentration of phenol in the effluent was null until reaching its rupture (58 hours). The results showed the possibility of use of the reject for removal of phenols in the final operations of the treatment process, removing as well, satisfactorily, the color and turbidity of the produced water, with more than 90% of removal
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:
Electrical resistive heating (ERH) is a thermal method used to improve oil recovery. It can increase oil rate and oil recovery due to temperature increase caused by electrical current passage through oil zone. ERH has some advantage compared with well-known thermal methods such as continuous steam flood, presenting low-water production. This method can be applied to reservoirs with different characteristics and initial reservoir conditions. Commercial software was used to test several cases using a semi-synthetic homogeneous reservoir with some characteristics as found in northeast Brazilian basins. It was realized a sensitivity analysis of some reservoir parameters, such as: oil zone, aquifer presence, gas cap presence and oil saturation on oil recovery and energy consumption. Then it was tested several cases studying the electrical variables considered more important in the process, such as: voltage, electrical configurations and electrodes positions. Energy optimization by electrodes voltage levels changes and electrical settings modify the intensity and the electrical current distribution in oil zone and, consequently, their influences in reservoir temperature reached at some regions. Results show which reservoir parameters were significant in order to improve oil recovery and energy requirement in for each reservoir. Most significant parameters on oil recovery and electrical energy delivered were oil thickness, presence of aquifer, presence of gas cap, voltage, electrical configuration and electrodes positions. Factors such as: connate water, water salinity and relative permeability to water at irreducible oil saturation had low influence on oil recovery but had some influence in energy requirements. It was possible to optimize energy consumption and oil recovery by electrical variables. Energy requirements can decrease by changing electrodes voltages during the process. This application can be extended to heavy oil reservoirs of high depth, such as offshore fields, where nowadays it is not applicable any conventional thermal process such as steam flooding
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:
Neste trabalho, o pacote Climatol-R foi aplicado a 122 séries mensais de temperatura mínima, cobrindo o interior do estado de São Paulo para os anos 1940 até 2012.
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:
Continuous steam injection is one of heavy oil thermal recovery methods used in the Brazilian Northeast because of high occurrence of heavy oil reservoir. In this process, the oil into the reservoir is heated while reduces, substantially, its viscosity and improves the production. This work analyzed how the shaly sand layers influenced in the recovery. The studied models were synthetics, but the used reservoir data can be extrapolated to real situations of Potiguar Basin. The modeling was executed using the STARS - Steam Thermal and Advanced Process Reservoir Simulator - whose version was 2007.10. STARS is a tool of CMG Computer Modeling Group. The study was conducted in two stages, the first we analyzed the influence of reservoir parameters in the thermal process, so some of these were studied, including: horizontal permeability of the reservoir and the layer of shaly sand, ratio of horizontal permeability to vertical permeability, the influence of capillary pressure layer of shaly sand and as the location and dimensions of this heterogeneity can affect the productivity of oil. Among the parameters studied the horizontal permeability of the reservoir showed the most significant influence on the process followed by diversity. In the second stage three models were selected and studied some operational parameters such as injection rate, distance between wells, production time and completion intervals. Among the operating parameters studied the low rate and intermediate distances between wells showed the best recoveries