941 resultados para Petroleum refineries


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Refiners today operate their equipment for prolonged periods without shutdown. This is primarily due to the increased pressures of the market resulting in extended shutdown-to-shutdown intervals. This places extreme demands on the reliability of the plant equipment. The traditional methods of reliability assurance, like Preventive Maintenance, Predictive Maintenance and Condition Based Maintenance become inadequate in the face of such demands. The alternate approaches to reliability improvement, being adopted the world over are implementation of RCFA programs and Reliability Centered Maintenance. However refiners and process plants find it difficult to adopt this standardized methodology of RCM mainly due to the complexity and the large amount of analysis that needs to be done, resulting in a long drawn out implementation, requiring the services of a number of skilled people. These results in either an implementation restricted to only few equipment or alternately, one that is non-standard. The paper presents the current models in use, the core requirements of a standard RCM model, the alternatives to classical RCM, limitations in the existing model, classical RCM and available alternatives to RCM and will then go on to present an ‗Accelerated‘ approach to RCM implementation, that, while ensuring close conformance to the standard, does not place a large burden on the implementers

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"June 1995."

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Bit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates tend to follow the projects-demand and barrel-price rises. A methodology to model and predict one of the drilling bit performance evaluator, the Rate of Penetration (ROP), is presented herein. As the parameters affecting the ROP are complex and their relationship not easily modeled, the application of a Neural Network is suggested. In the present work, a dynamic neural network, based on the Auto-Regressive with Extra Input Signals model, or ARX model, is used to approach the ROP modeling problem. The network was applied to a real oil offshore field data set, consisted of information from seven wells drilled with an equal-diameter bit.

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This dissertation addresses the risk of lung cancer associated with occupational exposures in the petroleum refining and petrochemical industries. Earlier epidemiologic studies of this association did not adjust for cigarette smoking or have specific exposure classifications. The Texas EXposure Assessment System (TEXAS) was developed with data from a population-based, case-comparison study conducted in five southeast Texas counties between 1976 and 1980. The Texas Exposure Assessment System uses job and process categories developed by the American Petroleum Institute, as well as time-oriented variables to identify high risk groups.^ An industry-wide, increased risk for lung cancer was associated with jobs having low-level hydrocarbon exposure that also include other occupational inhalation exposures (OR = 2.0--adjusted for smoking and latency effects). The prohibition of cigarette smoking for jobs with high-level hydrocarbon exposure might explain part of the increased risk for jobs with low-level hydrocarbon exposures. Asbestos exposure comprises a large part of the risk associated with jobs having other inhalation exposures besides hydrocarbons. Workers in petroleum refineries were not shown to have an increased, occupational risk for lung cancer. The increased risk for lung cancer among petrochemical workers (OR = 3.1--smoking and latency adjusted) is associated with all jobs that involve other inhalation exposure characteristics (not only low-level hydrocarbon exposures). Findings for contract workers and workers exposed to specific chemicals were inconclusive although some hypotheses for future research were identified.^ The study results demonstrate that the predominant risk for lung cancer is due to cigarette smoking (OR = 9.8). Cigarette smoking accounts for 86.5% of the incident lung cancer cases within the study area. Workers in the petroleum industry smoke significantly less than persons employed in other industries (p << 0.001). Only 2.2% of the incident lung cancer cases may be attributed to petroleum industry jobs; lifestyle factors (e.g., nutrition) may be associated with the balance of the cases. The results from this study also suggest possible high risk time periods (OR = 3.9--smoking and occupation adjusted). Artifacts in time-oriented findings may result because of the latency interval for lung cancer, secular peaks in age-, sex-specific incidence rates, or periods of hazardous exposures in the petroleum industry. ^

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Mode of access: Internet.

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In petroleum refineries, water is used in desalting units to remove the salt contained in crude oil. Typically, 7% of the volume of hot crude oil is water, forming a water-and-oil emulsion. The emulsion flows between two electrodes and is subjected to an electric field. The electrical forces promote the coalescence of small droplets of water dispersed in crude oil, and these form bigger droplets. This paper calculates the forces acting on the droplets, highlighting particularly the mechanisms proposed for droplet-droplet coalescence under the influence of an applied electric field. Moreover, a model is developed in order to calculate the displacement speed of the droplets and the time between droplet collisions. Thus, it is possible to simulate and optimize the process by changing the operational variables (temperature, electrical field, and water quantity). The main advantage of this study is to show that it is feasible to increase the volume of water recycled in desalting processes, thus reducing the use of freshwater and the generation of liquid effluents in refineries.

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Supervising and controlling the many processes involved in petroleum production is both dangerous and complex. Herein, we propose a multiagent supervisory and control system for handle continuous processes like those in chemical and petroleum industries In its architeture, there are agents responsible for managing data production and analysis, and also the production equipments. Fuzzy controllers were used as control agents. The application of a fuzzy control system to managing an off-shore installation for petroleum production onto a submarine separation process is described. © 2008 IEEE.

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Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of São Paulo, in the city of Cubatão, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar. © 2011 SPIE.

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Reuse of industrial and agricultural wastes as supplementary cementitious materials (SCMs) in concrete and mortar productions contribute to sustainable development. In this context, fluid catalytic cracking catalyst residue (spent FCC), a byproduct from the petroleum industry and petrol refineries, have been studied as SCM in blended Portland cement in the last years. Nevertheless, another environmental friendly alternative has been conducted in order to produce alternative binders with low CO2 emissions. The use of aluminosilicate materials in the production of alkali-activated materials (AAMs) is an ongoing research topic which can present low CO2 emissions associated. Hence, this paper studies some variables that can influence the production of AAM based on spent FCC. Specifically, the influence of SiO 2/Na2O molar ratio and the H2O/spent FCC mass ratio on the mechanical strength and microstructure are assessed. Some instrumental techniques, such as SEM, XRD, pH and electrical conductivity measurements, and MIP are performed in order to assess the microstructure of formed alkali-activated binder. Alkali activated mortars with compressive strength up to 80 MPa can be formed after curing for 3 days at 65°C. The research demonstrates the potential of spent FCC to produce alkali-activated cements and the importance of SiO2/Na2O molar ratio and the H2O/spent FCC mass ratio in optimising properties and microstructure. © 2013 Elsevier Ltd. All rights reserved.

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Mode of access: Internet.

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"A (ER) 75-66."

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Mode of access: Internet.