75 resultados para Oil shales


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The upstream oil & gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data”—that is, the ability to apply more sophisticated types of analytical tools to information in a way that extracts new insights or creates new forms of value—is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil & gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This paper examines existing data management practices in the upstream oil & gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the Big Data revolution. The comparison shows that, in companies that are leading the Big Data revolution, data is regarded as a valuable asset. The presented evidence also shows, however, that this is usually not true within the oil & gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how upstream oil & gas companies could potentially extract more value from data, and concludes with a series of specific technical and management-related recommendations to this end.

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The upstream oil and gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data” is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil and gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This viewpoint examines existing data management practices in the upstream oil and gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the way in Big Data. The comparison shows that, in companies that are widely considered to be leaders in Big Data analytics, data is regarded as a valuable asset—but this is usually not true within the oil and gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how the industry could potentially extract more value from data, and concludes with a series of policy-related questions to this end.

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The research introduces a promising technique for monitoring the degradation status of oil-paper insulation systems of large power transformers in an online mode and innovative enhancements are also made on the existing offline measurements, which afford more direct understanding of the insulation degradation process. Further, these techniques benefit from a quick measurement owing to the chirp waveform signal application. The techniques are improved and developed on the basis of measuring the impedance response of insulation systems. The feasibility and validity of the techniques was supported by the extensive simulation works as well as experimental investigations.

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A series of macro–mesoporous TiO2/Al2O3 nanocomposites with different morphologies were synthesized. The materials were calcined at 723 K and were characterized by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscope (TEM), N2 adsorption/desorption, Infrared Emission Spectroscopy (IES), X-ray photoelectron spectroscopy (XPS) and UV–visible spectroscopy (UV–visible). A modified approach was proposed for the synthesis of 1D (fibrous) nanocomposite with higher Ti/Al molar ratio (2:1) at lower temperature (<100 °C), which makes it possible to synthesize such materials on industrial scale. The performance–morphology relationship of as-synthesized TiO2/Al2O3 nanocomposites was investigated by the photocatalytic degradation of a model organic pollutant under UV irradiation. The samples with 1D (fibrous) morphology exhibited superior catalytic performance than the samples without, such as titania microspheres.

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A 60-year-old male experienced a marked unilateral myopic shift of 20 D following attempted removal of intravitreal heavy silicone oil (HSO) used in the treatment of inferior proliferative vitreous retinopathy following retinal detachment. Examination revealed HSO adherent to the corneal endothelium forming a convex interface with the aqueous, obscuring the entire pupil, which required surgical intervention to restore visual acuity. This case highlights the potential ocular complications associated with silicone oil migration into the anterior chamber, which include corneal endothelial decompensation and a significant increase in myopia.

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This study explores the potential use of empty fruit bunch (EFB) residues from palm oil processing residues, as an alternative feedstock for microbial oil production. EFB is a readily available, lignocellulosic biomass that provides cheaper substrates for oil production in comparison to the use of pure sugars. In this study, potential oleaginous microorganisms were selected based on a multi-criteria analysis (MCA) framework which utilised Analytical Hierarchy Process (AHP) with Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) aided by Geometrical Analysis for Interactive Aid (GAIA). The MCA framework was used to evaluate several strains of microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa) and fungi (Aspergillus oryzae and Mucor plumbeus) on glucose, xylose and glycerol. Based on the results of PROMETHEE rankings and GAIA plane, fungal strains A. oryzae and M. plumbeus and yeast strain R. mucilaginosa showed great promise for oil production from lignocellulosic hydrolysates. The study further cultivated A. oryzae, M. plumbeus and R. mucilaginosa on EFB hydrolysates for oil production. EFB was pretreated with dilute sulfuric acid, followed by enzymatic saccharification of solid residue. Hydrolysates tested in this study are detoxified liquid hydrolysates (LH) and enzymatic hydrolysate (EH).

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Statistical comparison of oil samples is an integral part of oil spill identification, which deals with the process of linking an oil spill with its source of origin. In current practice, a frequentist hypothesis test is often used to evaluate evidence in support of a match between a spill and a source sample. As frequentist tests are only able to evaluate evidence against a hypothesis but not in support of it, we argue that this leads to unsound statistical reasoning. Moreover, currently only verbal conclusions on a very coarse scale can be made about the match between two samples, whereas a finer quantitative assessment would often be preferred. To address these issues, we propose a Bayesian predictive approach for evaluating the similarity between the chemical compositions of two oil samples. We derive the underlying statistical model from some basic assumptions on modeling assays in analytical chemistry, and to further facilitate and improve numerical evaluations, we develop analytical expressions for the key elements of Bayesian inference for this model. The approach is illustrated with both simulated and real data and is shown to have appealing properties in comparison with both standard frequentist and Bayesian approaches

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Gac fruits were physically measured and stored under ambient conditions for up to 2 weeks to observe changes in carotenoid contents (lycopene and beta carotene) in its aril. Initial concentrations in the aril of lycopene were from 2.378 mg/g fresh weight (FW) to 3.728 mg/g FW and those of beta carotene were from 0.257 to 0.379 mg/g FW. Carotenoid concentrations in the aril remained stable after 1 week but sharply declined after 2 weeks of storage. Gac oil, pressed from gac aril, has similar concentrations of lycopene and beta carotene (2.436 and 2.592 mg/g, respectively). Oil was treated with 0.02% of butylated hydroxytoluene, or with a stream of nitrogen or untreated then stored in the dark for up to 15 or 19 weeks under different temperatures (5 °C, ambient, 45 and 60 °C). Lycopene and beta carotene in control gac oil degraded following the first-order kinetic model. The degradation rate of lycopene and beta carotene in the treated oil samples were lower than that in the control oil but the first-order kinetic was not always followed. However, both lycopene and beta carotene degraded quickly in gac oil with the first-order kinetic under high temperature conditions (45 and 60 °C) regardless of the treatments used. © 2009 Elsevier Ltd. All rights reserved.

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Correlations between oil and agricultural commodities have varied over previous decades, impacted by renewable fuels policy and turbulent economic conditions. We estimate smooth transition conditional correlation models for 12 agricultural commodities and WTI crude oil. While a structural change in correlations occurred concurrently with the introduction of biofuel policy, oil and food price levels are also key influences. High correlation between biofuel feedstocks and oil is more likely to occur when food and oil price levels are high. Correlation with oil returns is strong for biofuel feedstocks, unlike with other agricultural futures, suggesting limited contagion from energy to food markets.

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Despite considerable effort and a broad range of new approaches to safety management over the years, the upstream oil & gas industry has been frustrated by the sector’s stubbornly high rate of injuries and fatalities. This short communication points out, however, that the industry may be in a position to make considerable progress by applying “Big Data” analytical tools to the large volumes of safety-related data that have been collected by these organizations. Toward making this case, we examine existing safety-related information management practices in the upstream oil & gas industry, and specifically note that data in this sector often tends to be highly customized, difficult to analyze using conventional quantitative tools, and frequently ignored. We then contend that the application of new Big Data kinds of analytical techniques could potentially reveal patterns and trends that have been hidden or unknown thus far, and argue that these tools could help the upstream oil & gas sector to improve its injury and fatality statistics. Finally, we offer a research agenda toward accelerating the rate at which Big Data and new analytical capabilities could play a material role in helping the industry to improve its health and safety performance.

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This work reports on the fabrication of a superhydrophobic nylon textile based on the organic charge transfer complex CuTCNAQ (TCNAQ = 11,11,12,12-tetracyanoanthraquinodimethane). The nylon fabric that is metallized with copper undergoes a spontaneous chemical reaction with TCNAQ dissolved in acetonitrile to form nanorods of CuTCNAQ that are intertwined over the entire surface of the fabric. This creates the necessary micro and nanoscale roughness that is required for the Cassie-Baxter state thereby achieving a superhydrophobic/superoleophilic surface without the need for a fluorinated surface. The material is characterised with SEM, FT-IR and XPS spectroscopy and investigated for its ability to separate oil and water in two modes, namely under gravity and as an absorbent. It is found that the fabric can separate dichloromethane, olive oil and crude oil from water and in fact reduce the water content of the oil during the separation process. The fabric is reusable and tolerant to conditions such as seawater, hydrochloric acid and extensive time periods on the shelf. Given that CuTCNAQ is a copper based semiconductor may also open up the possibility of other applications in areas such as photocatalysis and antibacterial applications.

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Oil palm empty fruit bunch (EFB) is a readily available, lignocellulosic biomass that has potential to be utilized as a carbon substrate for microbial oil production. In order to evaluate the production of microbial oil from EFB, a technical study was performed through the cultivation of oleaginous micro-organisms (Rhodotorula mucilaginosa, Aspergillus oryzae, and Mucor plumbeus) on EFB hydrolyzates. EFB hydrolyzates were prepared through dilute acid pre-treatment of the biomass, where the liquid fraction of pre-treatment was detoxified and used as an EFB liquid hydrolyzate (EFBLH). The solid residue was enzymatically hydrolyzed prior to be used as an EFB enzymatic hydrolyzate (EFBEH). The highest oil concentrations were obtained from M. plumbeus (1.9 g/L of oil on EFBLH and 4.7 g/L of oil on EFBEH). In order to evaluate the feasibility of large-scale microbial oil production, a techno-economic study was performed based on the oil yields of M. plumbeus per hectare of plantation, followed by the estimation of the feedstock cost for oil production. Other oil palm biomasses (frond and trunk) were also included in this study, as it could potentially improve the economics of large-scale microbial oil production. Microbial oil from oil palm biomasses was estimated to potentially increase oil production in the palm oil industry up to 25%, at a cheaper feedstock cost. The outcome of this study demonstrates the potential integration of microbial oil production from oil palm biomasses with existing palm oil industry (biodiesel, food and oleochemicals production), that could potentially enhance sustainability and profitability of microbial oil production.

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This study investigated the potential use of sugarcane bagasse as a feedstock for oil production through microbial cultivation. Bagasse was subjected to dilute acid pretreatment with 0.4 wt% H2SO4 (in liquid) at a solid/liquid ratio of 1:6 (wt/wt) at 170 °C for 15 min, followed by enzymatic hydrolysis of solid residue. The liquid fractions of the pretreatment process and the enzymatic hydrolysis process were detoxified and used as liquid hydrolysate (SCBLH) and enzymatic hydrolysate (SCBEH) for the microbial oil production by oleaginous yeast (Rhodotorula mucilaginosa) and filamentous fungi (Aspergillus oryzae and Mucor plumbeus). The results showed that all strains were able to grow and produce oil from bagasse hydrolysates. The highest oil concentrations produced from bagasse hydrolysates were by M. plumbeus at 1.59 g/L (SCBLH) and 4.74 g/L (SCBEH). The microbial oils obtained have similar fatty acid compositions to vegetable oils, indicating that the oil can be used for the production of second generation biodiesel. On the basis of oil yields obtained by M. plumbeus, from 10 million t (wet weight) of bagasse generated annually from sugar mills in Australia, it is estimated that the total biodiesel that could be produced would be equivalent to about 9% of Queensland’s diesel consumption.

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Porous titanium dioxide synthesized with a bicontinuous surfactant template is a promising method that leads to a high active surface area electrode. The template used is based on a water/isooctane/dioctyl sodium sulfosuccinate salt together with lecithin. Several parameters were varied during the synthesis to understand and optimize channel formation mechanisms. The material is patterned in stacked conical channels, widening towards the centre of the grains. The active surface area increased by 116% when the concentration of alkoxide precursors was decreased and increased by 241% when the template formation temperature was decreased to 10C. Increasing the oil phase viscosity tends to widen the pore aperture, thus decreasing the overall active surface area. Changing the phase proportions alters the microemulsion integrity and disrupts channel formation.