844 resultados para engenharia de petróleo


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Chemical admixtures, when properly selected and quantified, play an important role in obtaining adequate slurry systems for quality primary cementing operations. They assure the proper operation of a well and reduce costs attributed to corrective cementing jobs. Controlling the amount lost by filtering through the slurry to permeable areas is one of the most important requirements in an operation, commonly controlled by chemical admixtures, such as carboxymethylcellulose (CMC). However, problems related to temperature, salttolerance and the secundary retarding effect are commonly reported in the literature. According to the scenario described above, the use of an aqueous dispersion of non-ionic poliurethane was proposed to control the filter loss, given its low ionic interaction with the free ions present in the slurries in humid state. Therefore, this study aims at assessing the efficiency of poliurethane to reduce filter loss in different temperature and pressure conditions as well as the synergistic effect with other admixtures. The temperatures and pressures used in laboratory tests simulate the same conditions of oil wells with depths of 500 to 1200 m. The poliurethane showed resistance to thermal degradation and stability in the presence of salts. With the increase in the concentration of the polymer there was a considerable decrease in the volume lost by filtration, and this has been effective even with the increase in temperature

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The oil production in Brazil has been increasing each year. Consequently, increasing volumes of water produced are generated with large quantities of contaminants, which brings many problems in disposing of these waters. The concern that the concentrations of contaminants in water produced meet existing laws for disposal of effluents, has been extremely important for the development of different techniques for treatment of water produced. The study of clay minerals as adsorbents of organic contaminants has grown considerably so in order to combine the low cost with the efficiency of environmental preservation and health issues. Thus, this study aims to understand the characteristics of vermiculite clay, sodium bentonite, calcium bentonite and diatomite and evaluate their performance as adsorbents for phenol in the water produced. Through adsorption isotherms it was possible to observe the behavior of these adsorptive clay and diatomite for adsorption of phenol, the main phenolic compound found in water produced. Different concentrations of synthetic solutions of phenol were put in touch with these adsorbents under same conditions of agitation and temperature. The adsorbents were composted adsorptive favorable, but the vermiculite and diatomite showed little capacity for absorption, being suggested for absorbs small concentrations of phenol in the balance isothermal

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The new oil reservoirs discoveries in onshore and ultra deep water offshore fields and complex trajectories require the optimization of procedures to reduce the stops operation during the well drilling, especially because the platforms and equipment high cost, and risks which are inherent to the operation. Among the most important aspects stands out the drilling fluids project and their behavior against different situations that may occur during the process. By means of sedimentation experiments, a correlation has been validated to determe the sedimentation particles velocity in variable viscosity fluids over time, applying the correction due to effective viscosity that is a shear rate and time function. The viscosity evolution over time was obtained by carrying out rheologic tests using a fixed shear rate, small enough to not interfere in the fluid gelling process. With the sedimentation particles velocity and the fluid viscosity over time equations an iterative procedure was proposed to determine the particles displacement over time. These equations were implemented in a case study to simulate the cuttings sedimentation generated in the oil well drilling during stops operation, especially in the connections and tripping, allowing the drilling fluid project in order to maintain the cuttings in suspension, avoiding risks, such as stuck pipe and in more drastic conditions, the loss of the well

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With the new discoveries of oil and gas, the exploration of fields in various geological basins, imports of other oils and the development of alternative fuels, more and more research labs have evaluated and characterized new types of petroleum and derivatives. Therefore the investment in new techniques and equipment in the samples analysis to determine their physical and chemical properties, their composition, possible contaminants, especification of products, among others, have multiplied in last years, so development of techniques for rapid and efficient characterization is extremely important for a better economic recovery of oil. Based on this context, this work has two main objectives. The first one is to characterize the oil by thermogravimetry coupled with mass spectrometry (TG-MS), and correlate these results with from other types of characterizations data previously informed. The second is to use the technique to develop a methodology to obtain the curve of evaluation of hydrogen sulfide gas in oil. Thus, four samples were analyzed by TG-MS, and X-ray fluorescence spectrometry (XRF). TG results can be used to indicate the nature of oil, its tendency in coke formation, temperatures of distillation and cracking, and other features. It was observed in MS evaluations the behavior of oil main compounds with temperature, the points where the volatilized certain fractions and the evaluation gas analysis of sulfide hydrogen that is compared with the evaluation curve obtained by Petrobras with another methodology

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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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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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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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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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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

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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

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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

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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

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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

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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

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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