796 resultados para Oil pipeline


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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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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Os rios e lagos de várzea da província petrolífera de Urucu, na Amazônia Central, são amplamente colonizados por macrófitas aquáticas, que podem ser afetadas por acidentes durante a exploração e o transporte de petróleo. Entre as macrófitas, a espécie flutuante Eichhornia crassipes (aguapé) ocorre abundantemente na região; OBJETIVO: O objetivo desse estudo foi verificar o efeito de diferentes dosagens do petróleo de Urucu (0; 0,5; 1,5 e 3,0 L.m-2) na biomassa viva e morta de E. crassipes e em algumas características físicas e químicas da água; MÉTODOS: O experimento teve oitenta e quatro dias de duração. A cada sete dias foi determinada a biomassa (viva e morta) de E. crassipes e os valores de temperatura, pH, condutividade elétrica e oxigênio dissolvido da água; RESULTADOS: A dosagem de 0,5 L.m-2 foi suficiente para causar mortalidade parcial (48%) em E. crassipes após trinta e cinco dias de exposição ao petróleo. A dosagem de 3,0 L.m-2 causou mortalidade total (100%) em E. crassipes em oitenta e quatro dias de exposição. A decomposição do petróleo e da biomassa morta de E. crassipes provocam a redução do oxigênio dissolvido e do pH, e aumento da condutividade elétrica e de fósforo total na água; CONCLUSÕES: Nós concluímos que um derramamento de petróleo pode provocar mortalidade total em uma população de uma espécie de macrófita, mas não em uma outra. Isto pode alterar a diversidade de espécies de macrófitas na região impactada. No caso de Eichhornia crassipes e Pistia stratiotes, um derramamento de petróleo de Urucu pode favorecer E. crassipes, a espécie menos sensível ao petróleo.

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Biosurfactants are bioactive agents that can be produced by many different microorganisms. Among those, special attention is given to yeasts, since they can produce many types of biosurfactants in large scale, using several kinds of substrates, justifying its use for industrial production of those products. For this production to be economically viable, the use of residual carbon sources is recommended. The present study isolated yeasts from soil contaminated with petroleum oil hydrocarbons and assessed their capacity for producing biosurfactants in low cost substrates. From a microbial consortium enriched, seven yeasts were isolated, all showing potential for producing biosurfactants in soybean oil. The isolate LBPF 3, characterized as Candida antarctica, obtained the highest levels of production - with a final production of 13.86 g/L. The isolate LBPF 9, using glycerol carbon source, obtained the highest reduction in surface tension in the growth medium: approximately 43% of reduction after 24 hours of incubation. The products obtained by the isolates presented surfactant activity, which reduced water surface tension to values that varied from 34 mN/m, obtained from the product of isolates LBPF 3 and 16 LBPF 7 (respectively characterized as Candida antarctica and Candida albicans) to 43 mN/m from the isolate LPPF 9, using glycerol as substrate. The assessed isolates all showed potential for the production of biosurfactants in conventional sources of carbon as well as in agroindustrial residue, especially in glycerol.

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Pseudomonas aeruginosa LBI produced surface active rhamnolipids when cultivated on waste from the sunflower-oil process under different conditions. These biosurfactants, which reduce the superficial and interfacial tensions between fluids, offer advantages over their chemical counterparts, especially because of their ecological acceptability. These molecules can be used in fields as diverse as chemical, pharmaceutical and petrochemical industries. In this work, we present the effect of C/N ratio on growth and production yield. The best production yields (Y-P/S) were achieved for C/N ratios (in g/g) of 8/1 (0.22) and 6.4/1 (0.23). The product concentration was very satisfactory (7.3 g/L) at C/N ratio of 8/1, especially when considering that the substrate was basically composed of wastes that would otherwise constitute an environmental disposal problem. (c) 2007 Elsevier Ltd. All rights reserved.

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Diesel oil is a compound derived from petroleum, consisting primarily of hydrocarbons. Poor conditions in transportation and storage of this product can contribute significantly to accidental spills causing serious ecological problems in soil and water and affecting the diversity of the microbial environment. The cloning and sequencing of the 16S rRNA gene is one of the molecular techniques that allows estimation and comparison of the microbial diversity in different environmental samples. The aim of this work was to estimate the diversity of microorganisms from the Bacteria domain in a consortium specialized in diesel oil degradation through partial sequencing of the 16S rRNA gene. After the extraction of DNA metagenomics, the material was amplified by PCR reaction using specific oligonucleotide primers for the 16S rRNA gene. The PCR products were cloned into a pGEM-T-Easy vector (Promega), and Escherichia coli was used as the host cell for recombinant DNAs. The partial clone sequencing was obtained using universal oligonucleotide primers from the vector. The genetic library obtained generated 431 clones. All the sequenced clones presented similarity to phylum Proteobacteria, with Gammaproteobacteria the most present group (49.8 % of the clones), followed by Alphaproteobacteira (44.8 %) and Betaproteobacteria (5.4 %). The Pseudomonas genus was the most abundant in the metagenomic library, followed by the Parvibaculum and the Sphingobium genus, respectively. After partial sequencing of the 16S rRNA, the diversity of the bacterial consortium was estimated using DOTUR software. When comparing these sequences to the database from the National Center for Biotechnology Information (NCBI), a strong correlation was found between the data generated by the software used and the data deposited in NCBI.

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Broiler digestive tract fungal communities have gained far less scrutiny than that given corresponding bacterial communities. Attention given poultry-associated fungi have focused primarily on feed-associated toxin-producers, yeast, and yeast products. The current project focused on the use of pyrosequencing and denaturing gradient gel electrophoresis (DGGE) to identify and monitor broiler digestive fungal communities. Eight different treatments were included. Four controls were an Uninfected-Unmedicated Control, an Unmedicated-Infected Control, the antibiotic bacitracin methylene disalicylate plus the ionophore monensin as Positive Control, and the ionophore monensin alone as a Negative Control. Four treatments were two probiotics (BC-30 and Calsporin) and two specific essential oil blends (Crina Poultry Plus and Crina Poultry AF). All chickens except the Unmedicated-Uninfected Control were given, at 15 days of age, a standard oral Eimeria inoculum of sporulated oocysts. Ileal and cecal digesta were collected at pre-Eimeria infection at 14 days of age and at 7 days post-Eimeria infection at 22 days of age. Extracted cecal DNA was analyzed by pyrosequencing to examine the impact of diet supplements and Eimeria infection on individual constituents in the fungal community, while DGGE was used to compare more qualitative changes in ileal and cecal communities. Pyrosequencing identified three phyla, seven classes, eight orders, 13 families, 17 genera, and 23 fungal species. Ileal and cecal DGGE patterns showed fungal communities were clustered mainly into pre- and post-infection patterns. Post-infection Unmedicated-Uninfected patterns were clustered with pre-infection groups demonstrating a strong effect of Eimeria infection on digestive fungal populations. These combined techniques offered added versatility towards unraveling the effects of enteropathogen infection and performance enhancing feed additives on broiler digestive microflora.

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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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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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This work reports the chemical characterization of Eremanthusgoyzensis essential oil and its toxic effect over Brevipalpus phoenicis. The essential oil displayed a major composition of sesquiterpenes (61.87%) including trans-caryophillene (26.81%) and germacrene-D (13.31%). The fumigation test indicated a promising bioactivity over adult B. phoenicis individuals at 24 h (2.03 µL/L of air) and 48 h (1.08 µL/L of air) of exposition. A brief discussion of essential oils composition and their singular role on the toxic effect over B. phoenicis is provided here. Our results may contribute to a new and profitable use of a species of Brazilian flora on agribusiness.

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The essential oil of the leaves and branches obtained by hydrodistillation of Lychnophora ericoides, collected in the Reserve of Furnas - MG, Brazil, was analyzed by CG/EM (Shimadzu QP2010). The major parts of the volatile components identified in the essential oil of leaves were monoterpenes (44.02%) and the sesquiterpene [alpha]-bisabolol (2.05%). The major acaricidal activity of the essential oil from L. ericoides was observed at 48 (14.55 [mu]L/L of air) and 72 h (8.01 [mu]L/L of air) of exposition. The oviposition of T. urticae oviposition was influenced by the essential oil, but the eclosion of eggs was not affected.