30 resultados para submarine pipeline

em Universidade Federal do Rio Grande do Norte(UFRN)


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Shadows and illumination play an important role when generating a realistic scene in computer graphics. Most of the Augmented Reality (AR) systems track markers placed in a real scene and retrieve their position and orientation to serve as a frame of reference for added computer generated content, thereby producing an augmented scene. Realistic depiction of augmented content with coherent visual cues is a desired goal in many AR applications. However, rendering an augmented scene with realistic illumination is a complex task. Many existent approaches rely on a non automated pre-processing phase to retrieve illumination parameters from the scene. Other techniques rely on specific markers that contain light probes to perform environment lighting estimation. This study aims at designing a method to create AR applications with coherent illumination and shadows, using a textured cuboid marker, that does not require a training phase to provide lighting information. Such marker may be easily found in common environments: most of product packaging satisfies such characteristics. Thus, we propose a way to estimate a directional light configuration using multiple texture tracking to render AR scenes in a realistic fashion. We also propose a novel feature descriptor that is used to perform multiple texture tracking. Our descriptor is an extension of the binary descriptor, named discrete descriptor, and outperforms current state-of-the-art methods in speed, while maintaining their accuracy.

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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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The scale is defined as chemical compounds from inorganic nature, initially soluble in salt solutions, which may precipitate accumulate in columns of production and surface equipment. This work aimd to quantify the crystalline phases of scale through the Rietveld method. The study was conducted in scale derived from columns production wells in development and recipients of pigs. After collecting samples of scale were performed the procedure for separations of inorganic and organic phase and preparation to be analyzed at the X-ray Laboratory. The XRD and XRF techniques were used to monitor whether identifying and quantifying crystalline phases present in the deposits. The SEM technique was used to visualize the morphology of the scales and assess their homogeneity after the milling process. XRD measurements were performed with and without milling and with or without the accessory spinner. For quantify crystalline phases the program DBWStools was used. The procedure for conducting the first refinement was instrumental in setting parameters, then the structural parameters of the phases in the sample and finally the parameters of the function profile used. In the diffraction patterns of samples of scale observed that the best measures were those that passed through the mill and used the accessory spinner. Through the results, it was noted that the quantitative analysis for samples of scale is feasible when need to monitor a particular crystalline phase in a well, pipeline or oil field. Routinely, the quantification of phases by the Rietveld method is hardwork because in many scale was very difficult to identify the crystalline phases present

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With the increasing of demand for natural gas and the consequent growth of the pipeline networks, besides the importance of transport and transfer of oil products by pipeline, and when it comes to product quality and integrity of the pipeline there is an important role regarding to the monitoring internal corrosion of the pipe. This study aims to assess corrosion in three pipeline that operate with different products, using gravimetric techniques and electrical resistance. Chemical analysis of residues originated in the pipeline helps to identify the mechanism corrosive process. The internal monitoring of the corrosion in the pipelines was carried out between 2009 and 2010 using coupon weight loss and electrical resistance probe. Physico-chemical techniques of diffraction and fluorescence X-rays were used to characterize the products of corrosion of the pipelines. The corrosion rate by weight loss was analyzed for every pipeline, only those ones that has revealed corrosive attack were analyzed located corrosion rate. The corrosion potential was classified as low to pipeline gas and ranged from low to severe for oil pipelines and the pipeline derivatives. Corrosion products were identified as iron carbonate, iron oxide and iron sulfide

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The petroleum production pipeline networks are inherently complex, usually decentralized systems. Strict operational constraints are applied in order to prevent serious problems like environmental disasters or production losses. This paper describes an intelligent system to support decisions in the operation of these networks, proposing a staggering for the pumps of transfer stations that compose them. The intelligent system is formed by blocks which interconnect to process the information and generate the suggestions to the operator. The main block of the system uses fuzzy logic to provide a control based on rules, which incorporate knowledge from experts. Tests performed in the simulation environment provided good results, indicating the applicability of the system in a real oil production environment. The use of the stagger proposed by the system allows a prioritization of the transfer in the network and a flow programming

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Actually in the oil industry biotechnological approaches represent a challenge. In that, attention to metal structures affected by electrochemical corrosive processes, as well as by the interference of microorganisms (biocorrosion) which affect the kinetics of the environment / metal interface. Regarding to economical and environmental impacts reduction let to the use of natural products as an alternative to toxic synthetic inhibitors. This study aims the employment of green chemistry by evaluating the stem bark extracts (EHC, hydroalcoholic extract) and leaves (ECF, chloroform extract) of plant species Croton cajucara Benth as a corrosion inhibitor. In addition the effectiveness of corrosion inhibition of bioactive trans-clerodane dehydrocrotonin (DCTN) isolated from the stem bark of this Croton was also evaluated. For this purpose, carbon steel AISI 1020 was immersed in saline media (3,5 % NaCl) in the presence and absence of a microorganism recovered from a pipeline oil sample. Corrosion inhibition efficiency and its mechanisms were investigated by linear sweep voltammetry and electrochemical impedance. Culture-dependent and molecular biology techniques were used to characterize and identify bacterial species present in oil samples. The tested natural products EHC, ECF and DCTN (DMSO as solvent) in abiotic environment presented respectively, corrosion inhibition efficiencies of 57.6% (500 ppm), 86.1% (500 ppm) and 54.5% (62.5 ppm). Adsorption phenomena showed that EHC best fit Frumkin isotherm and ECF to Temkin isotherm. EHC extract (250 ppm) dissolved in a polar microemulsion system (MES-EHC) showed significant maximum inhibition efficiency (93.8%) fitting Langmuir isotherm. In the presence of the isolated Pseudomonas sp, EHC and ECF were able to form eco-compatible organic films with anti-corrosive properties

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Pipeline leak detection is a matter of great interest for companies who transport petroleum and its derivatives, in face of rising exigencies of environmental policies in industrialized and industrializing countries. However, existing technologies are not yet fully consolidated and many studies have been accomplished in order to achieve better levels of sensitivity and reliability for pipeline leak detection in a wide range of flowing conditions. In this sense, this study presents the results obtained from frequency spectrum analysis of pressure signals from pipelines in several flowing conditions like normal flowing, leakages, pump switching, etc. The results show that is possible to distinguish between the frequency spectra of those different flowing conditions, allowing recognition and announce of liquid pipeline leakages from pressure monitoring. Based upon these results, a pipeline leak detection algorithm employing frequency analysis of pressure signals is proposed, along with a methodology for its tuning and calibration. The proposed algorithm and its tuning methodology are evaluated with data obtained from real leakages accomplished in pipelines transferring crude oil and water, in order to evaluate its sensitivity, reliability and applicability to different flowing conditions

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This work consists in the use of techniques of signals processing and artificial neural networks to identify leaks in pipes with multiphase flow. In the traditional methods of leak detection exists a great difficulty to mount a profile, that is adjusted to the found in real conditions of the oil transport. These difficult conditions go since the unevenly soil that cause columns or vacuum throughout pipelines until the presence of multiphases like water, gas and oil; plus other components as sand, which use to produce discontinuous flow off and diverse variations. To attenuate these difficulties, the transform wavelet was used to map the signal pressure in different resolution plan allowing the extraction of descriptors that identify leaks patterns and with then to provide training for the neural network to learning of how to classify this pattern and report whenever this characterize leaks. During the tests were used transient and regime signals and pipelines with punctures with size variations from ½' to 1' of diameter to simulate leaks and between Upanema and Estreito B, of the UN-RNCE of the Petrobras, where it was possible to detect leaks. The results show that the proposed descriptors considered, based in statistical methods applied in domain transform, are sufficient to identify leaks patterns and make it possible to train the neural classifier to indicate the occurrence of pipeline leaks

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Visual Odometry is the process that estimates camera position and orientation based solely on images and in features (projections of visual landmarks present in the scene) extraced from them. With the increasing advance of Computer Vision algorithms and computer processing power, the subarea known as Structure from Motion (SFM) started to supply mathematical tools composing localization systems for robotics and Augmented Reality applications, in contrast with its initial purpose of being used in inherently offline solutions aiming 3D reconstruction and image based modelling. In that way, this work proposes a pipeline to obtain relative position featuring a previously calibrated camera as positional sensor and based entirely on models and algorithms from SFM. Techniques usually applied in camera localization systems such as Kalman filters and particle filters are not used, making unnecessary additional information like probabilistic models for camera state transition. Experiments assessing both 3D reconstruction quality and camera position estimated by the system were performed, in which image sequences captured in reallistic scenarios were processed and compared to localization data gathered from a mobile robotic platform

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Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

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The continuous gas lift method is the main artificial lifting method used in the oil industry for submarine wells, due to its robustness and the large range of flow rate that the well might operate. Nowadays, there is a huge amount of wells producing under this mechanism. This method of elevation has a slow dynamics due to the transients and a correlation between the injected gas rate and the of produced oil rate. Electronics controllers have been used to adjust many parameters of the oil wells and also to improve the efficiency of the gas lift injection system. This paper presents a intelligent control system applied to continuous gas injection in wells, based in production s rules, that has the target of keeping the wells producing during the maximum period of time, in its best operational condition, and doing automatically all necessary adjustments when occurs some disturbance in the system. The author also describes the application of the intelligent control system as a tool to control the flow pressure in the botton of the well (Pwf). In this case, the control system actuates in the surface control valve

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In the last decades there was a significant increasing of the numbers of researchers that joint efforts to find alternatives to improve the development of low environmental impact technology. Materials based on renewable resources have enormous potentials of applications and are seen as alternatives for the sustainable development. Within other parameters, the sustainability depends on the energetic efficiency, which depends on the thermal insulation. Alternative materials, including vegetal fibers, can be applied to thermal insulation, where its first goal is to minimize the loss of energy. In the present research, it was experimentally analyzed the thermal behavior of fiber blankets of sisal (Agave sisalana) with and without surface treatment with oxide hidroxide (NaOH). Blankets with two densities (1100/1200 and 1300/1400 g/m2) were submitted to three rates of heat transfer (22.5 W, 40 W and 62.5 W). The analysis of the results allowed comparing the blankets treated and untreated in each situation. Others experiments were carried out to obtain the thermal conductivity (k), heat capacity (C) and the thermal diffusivity (α) of the blankets. Thermo gravimetric analyses were made to the verification of the thermal stability. Based on the results it was possible to relate qualitatively the effect of the heat transfer through the sisal blankets subjected to three heat transfer rates, corresponding to three temperature values (77 °C, 112 °C e 155 °C). To the first and second values of temperature it was verified a considerable reduction on the rate of heat transfer; nevertheless, to the third value of temperature, the surface of the blankets (treated and untreated) in contact with the heated surface of the tube were carbonized. It was also verified, through the analyses of the results of the measurements of k, C e α, that the blankets treated and untreated have values near to the conventional isolating materials, as glass wool and rock wool. It could be concluded that is technically possible the use of sisal blankets as constitutive material of thermal isolation systems in applications where the temperature do not reach values greater than 112 ºC

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The modern technology of materials and structural integrity of pipelines requests the use of inspection tools named inspection pigs to detect, localize and measure the length, width and depth dimensions of the thickness losses of walls of buried and underwater pipelines in service. These tools run them internally, performing and recording measurements, with performance that varies according to the pig s technology. It has been developed recently an instrumented pig technology, called feller pig. This work aims to indicate factors that influence the feller pig technology performance in the detection and in the accuracy of measurement of the length, width and depth dimensions of the thickness losses on the internal surface of an oil pipeline wall under normal conditions of oil pipe inspection with pig. In this work, is made a collection of factors and an analyses of the technology based on the available literature, as well as an experiment to observe the technology and the factors operating. In the experiment, a feeler pig is used in a pipeline built in carbon steel and in operation that flows petroleum, in witch are observed areas with internal thickness losses occurred naturally. Some of these areas and their dimensions taken by automated ultra-sound scanner are compared with the ones indicated by the feller pig. Based on the data collection, on the analysis and on the experiment, the influence of factors object of this research is discussed. It is concluded that, among these, there are factors related to pipe fabrication tolerances, to wear of pig components, to internal adhesive wear of pipeline, to other pipeline damages and to technology characteristics. Finally, actions are suggested to know better, improve and define the applicability of this technology

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It is analyzed through the concepts of tribology and mechanical contact and damage the suggestion of implementing a backup system for traction and passage of Pipeline Inspection Gauge (Pig) from the inside of pipelines. In order to verify the integrity of the pipelines, it is suggested the possibility of displacement of such equipment by pulling wires with steel wires. The physical and mechanical characteristics of this method were verified by accelerated tests in the laboratory in a tribological pair, wire versus a curve 90. It also considered the main mechanisms of wear of a sliding system with and without lubricant, in the absence and presence of contaminants. To try this, It was constructed a test bench able to reproduce a slip system, work on mode back-and-forth ("reciprocation"). It was used two kinds of wires, a galvanized steel and other stainless steel and the results achieved using the two kinds of steel cables were compared. For result comparative means, it was used steel cables with and without coating of Poly Vinyl Chloride (PVC). The wires and the curves of the products were characterized using metallographic analysis, microhardness Vickers tests, X-ray diffraction (XRD), X-Ray Refraction (XRF) and tensile tests. After the experiments were analyzed some parameters that have been measurable, it demonstrates to the impracticality of this proposed method, since the friction force and the concept of alternating request at the contact between the strands of wire and the inner curves that are part ducts caused severe wear. These types of wear are likely to cause possible failures in future products and cause fluid leaks

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To enhance the maintenance practices, Oil and Gas Pipelines are inspected from the inside by automated systems called PIG (Pipeline Inspection Gauge). The inspection and mapping of defects, as dents and holes, in the internal wall of these pipelines are increasingly put into service toward an overall Structural Integrity Policy. The residual life of these structures must be determined such that minimize its probability of failure. For this reason, the investigation on the detection limits of some basic topological features constituted by peaks or valleys disposed along a smooth surface is of great value for determining the sensitivity of the measurements of defects from some combinations of circumferential, axial and radial extent. In this investigation, it was analyzed an inductive profilometric sensor to scan three races, radius r1, r2, r3, in a circular surface of low carbon steel, equipped with eight consecutive defects simulated by bulges and holes by orbit, equally spaced at p/4 rad. A test rig and a methodology for testing in laboratory were developed to evaluate the sensor response and identify their dead zones and jumps due to fluctuations as a function of topological features and scanning velocity, four speeds different. The results are presented, analyzed and suggestions are made toward a new conception of sensor topologies, more sensible to detect these type of damage morphologies