Crude Oil Blends Research Articles

Medición del riesgo de la cola en el mercado del petróleo mexicano aplicando la teoría de valores extremos condicional

This paper applies the extreme values theory to the conditional distribution of standardized residuals from the specifications GARCH, EGARCH and TGARCH, and proposes dynamic risk measures to estimate VaR and expected shortfall of long and short positions of the Mexican Blend crude oil from January 4, 1989 to December 31, 2013. The results of backtesting procedure show that the models based on the conditional extreme value theory and filtered historical simulation yield more accurate estimates of conditional VaR at all confidence levels although their performance is lowered significantly for the conditional expected shortfall prediction. At 99.5% and 99.9% confidence levels, the empirical findings reveal that the government is prone to experience a higher risk than the consumers of Mexican crude oil at the international market because the inferior tail of empirical distribution is more stable and heavier than the superior tail.

Effects of Surfactant Blend Formulation on Crude Oil-Brine Interaction and Wettability: An Experimental Study

Interfacial tension of reservoir fluids and wettability are important parameters in the process of enhanced oil recovery. These two parameters affect the fluid distribution within reservoir formation. The fluids distribution in the reservoir strongly affects the flow behavior and residual oil recovery. Interfacial tension plays an important role due to its relationship between foam surface energy and foam stability. The wettability by contact angle measurement provides a method for determining fluid interaction and is considered as a basic research than practical tool for analysis of reservoir formation. The main objective of this research study is to determine the effects of interfacial tension and wettability on foam surfactant blend formulations, brine and crude oil. Anionic and nonionic surfactant blend were selected. The interfacial tension test was performed at 85oC. Dynamic interfacial tension of blended surfactant formulations with Malaysian crude oil were measured in fixed brine salinity. The interfacial tension values of tested surfactant blends were found lower than the interfacial tension between brine and crude oil. Interracial tension between crude oil and foam forming surfactant was reduced by using different concentration of surfactant blend. Good values were obtained by the measurement of contact angle between solid and three foam surfactant blend formulations. The interfacial tension and contact angle experimental studies revealed that, the blend of Alpha Olefin Sulfonate and Sodium Dodecyl Sulfonate with Octylphenol Ethylene Oxide play an important role in reducing the interfacial tension at crude oil-brine interface. The reduced interfacial tension and more wetting surface effects indicated that, these foam surfactant formulations are of great importance in the process of residual oil recovery.

Least square neural network model of the crude oil blending process

In this paper, the recursive least square algorithm is designed for the big data learning of a feedforward neural network. The proposed method as the combination of the recursive least square and feedforward neural network obtains four advantages over the alone algorithms: it requires less number of regressors, it is fast, it has the learning ability, and it is more compact. Stability, convergence, boundedness of parameters, and local minimum avoidance of the proposed technique are guaranteed. The introduced strategy is applied for the modeling of the crude oil blending process.

Effect of citrus peel chemicals onBactrocera tryonilarval survival

Queensland fruit fly, Bactrocera tryoni (Froggatt) (Diptera: Tephritidae) is a major horticultural insect pest in Australia which significantly limits domestic and international market access for Australian horticultural produce. Citrus is one of the industries seriously affected by the fruit fly problem in Australia. This research investigated the effect of citrus peel essential oil chemicals on B. tryoni larval survival in five different commercially important Citrus species and cultivars as a way of better understanding fruit susceptibility. The fruits used were Murcott Mandarin, Navel orange, Eureka lemon, Valencia orange and yellow grapefruit. The essential oils of each citrus type were extracted using hydrodistillation and then mixed, at different concentrations, with artificial larval diets to which B. tryoni eggs were added. Surviving larvae were counted after five trial days. The same process was repeated for six essential oil components. Regression analysis of increasing oil concentration against larval survival showed that the crude oil blends of Navel orange, Eureka lemon and yellow grapefruit had significant negative effects on B. tryoni larval survival, but no such effects were seen for Murcott Mandarin and Valencia orange. Of the individual essential oil fractions, only D-limonene had a significant effect on B. tryoni larval survival, with this chemical being highly toxic at very low concentrations. The results of this study open up opportunities for incorporating B. tryoni resistance mechanisms into citrus through minor peel property changes which would not impact on the eating attributes of the fruit.

Effect of Temperature and Composition on the Stability of Crude Oil Blends Studied with Chemical Imaging in Situ

Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic imaging approach has been applied in situ to investigate the behavior of crude oil blends at different conditions. The ratio between mixed crude oils and temperature has been varied to study how these factors influence the stability of the blends. Obtained spectroscopic results have been used to correlate the composition of the blends with respect to the incompatibility of crude oils. The chemical compositions of precipitates formed from the blends at 60 and 200 °C have been examined by FTIR spectroscopy. The change of asphaltene solubility in crude oil blends as well as the precipitation of inorganic salts, sulfates, have been observed at higher temperature. Based on available spectroscopic data, the formation of hydrogen bonds between sulfoxide groups of precipitated inorganic sulfates and hydroxy groups of asphaltenes or similar condensed aromatic species has been proposed.

Sulfide promoted chronic fouling in a refinery: A broad phenomenon spanning a range of heat transfer surfaces and oil types

Fouling of metal heat-transfer surfaces employed in crude oil refining operations, driven by inorganic corrosion products, is not well understood. Here we employ a range of advanced analytical techniques, including TEM, SEM, FIB and XRD to systematically document the interdependent corrosion – fouling processes of three refinery metallurgies: a carbon steel, a (P91) 9Cr–1Mo steel, and a 347 stainless steel. We utilize two representative crude oil blends, testing at a metal surface temperature of 490°C and an oil bath temperature of 290°C. For the three metallurgies there is a mechanistic similarity of the fouling phenomenon, which begins with sulfidic corrosion of the metal surface and progresses to coking. It is observed that after 1h of testing, carbon steel samples actually fouled somewhat less than the P91, which was initially unexpected since the latter is considered a more sulfidic corrosion resistant alloy. TEM and SEM analyses demonstrate that there is poor adhesion of the sulfide layer on the carbon steel, which we hypothesize results in the metal surface effectively self-cleaning. Despite being the most resistant to sulfidic corrosion and to fouling, the stainless steel nevertheless forms a thin Fe–Cr–Mn rich inner sulfide and a thicker Fe-rich outer sulfide. We also examine the role of volatiles (reactor pressure), and demonstrate that fouling rates drop off with successive tests on the same oil batch. This is attributed to a gradual exhaustion of S-containing species that react at high temperature to sulfide the metal surface, which in turn catalyze the growth of the organic coke.

PERFORMANCE AND EMISSIONS CHARACTERISTICS OF CRUDE JATROPHA OIL BIODIESEL BLENDS IN A DIESEL ENGINE

Biofuels based on vegetable oils offer the advantages of being sustainable, annually renewable sources of automobile fuel. Despite many years of improvement, use of vegetable-oil-based fuels still has issues, such as oxidation, the stoichiometric point, bio-fuel composition, antioxidants on degradation and the volume of oxygen compared to diesel. Thus, improvements in the emissions from diesel engines fueled by a blend of crude jatropha oil with diesel could be the requirement to meet the reduced emissions regulations in the future. The purpose of this study is to investigate the effects on the vehicle’s performance and exhaust emissions of the combustion process of blended crude jatropha oil and palm oil with different ratios. The engine speed was varied from 1500~3000 rpm, the load test condition was varied from 0~100% using a Dynapack chassis dynamometer and crude jatropha oil with a diesel blending ratio from 5~15vol% (CJO5~CJO15) was used. A decrease in HC emissions was found in the combustion process as the ratio of the blend of crude jatropha oil with diesel was increased and also with nearly equal engine performance. The increase in the jatropha oil biodiesel blending ratio promoted the reduction of HC, CO and CO2 emissions in the range 10vol% to 15vol% of the blends. The improvement in the combustion process with the higher blending ratio is expected to be strongly influenced by the oxygen contained in the blended crude jatropha oil.

Marine biodegradation of crude oil in temperate and Arctic water samples

Despite increased interest in marine oil exploration in the Arctic, little is known about the fate of Arctic offshore oil pollution. Therefore, in the present study, we examine the oil degradation potential for an Arctic site (Disko Bay, Greenland) and discuss this in relation to a temperate site (North Sea, Denmark). Biodegradation was assessed following exposure to Oseberg Blend crude oil (100mgL−1) in microcosms. Changes in oil hydrocarbon fingerprints of polycyclic aromatic hydrocarbons (PAHs), alkyl-substituted PAHs, dibenzothiophenes, n-alkanes and alkyltoluenes were measured by gas chromatography-mass spectrometry (GC–MS). In the Disko Bay sample, the degradation order was n-alkanes>alkyltoluenes (para->meta->ortho-isomers)>PAHs and dibenzothiophenes, whereas, the degradation order in the North Sea samples was PAHs and dibenzothiophenes>alkyltoluenes>n-alkanes. These differences in degradation patterns significantly affect the environmental risk of oil spills and emphasise the need to consider the specific environmental conditions when conducting risk assessments of Arctic oil pollution.

Use of dispersant in mudflat oil-contaminated sediment: behavior and effects of dispersed oil on micro- and macrobenthos.

The present study aimed to examine whether the use of dispersant would be suitable for favoring the hydrocarbon degradation in coastal marine sediments without impacting negatively micro- and macrobenthic organisms. Mudflat sediments, maintained during 286 days in mesocosms designed to simulate natural conditions, were contaminated or not with Ural blend crude oil (REBCO) and treated or not with third-generation dispersant (Finasol OSR52). While the dispersant did not lead to an increase of hydrocarbon biodegradation, its use enables an attenuation of more than 55 % of the sediment concentration of total petroleum hydrocarbons (TPH). Canonical correspondence analysis (CCA) correlating T-RFLP patterns with the hydrocarbon content and bacterial abundance indicated weak differences between the different treatments except for the mesocosm treated with oil and dispersant for which a higher bacterial biomass was observed. The use of the dispersant did not significantly decrease the macrobenthic species richness or macroorganisms' densities in uncontaminated or contaminated conditions. However, even if the structure of the macrobenthic communities was not affected, when used in combination with oil, biological sediment reworking coefficient was negatively impacted. Although the use of the dispersant may be worth considering in order to accelerate the attenuation of hydrocarbon-contaminated mudflat sediments, long-term effects on functional aspects of the benthic system such as bioturbation and bacterial activity should be carefully studied before.

Experimental and Modeling Investigations of the Viscosity of Crude Oil Binary Blends: New Models Based on the Genetic Algorithm Method

Achieving an estimation of viscosity in crude oil binary mixtures is often difficult because the relationship of viscosity, to the fraction of each crude oil, and many other parameters and constants is comply. This relationship can be expressed by mathematical models with different variables. Besides the known models for predicting the viscosity of crude oil mixtures, the petroleum industry demands other models which give accurate predictions. In this work, two new empirical models have been developed for the calculation of the viscosity of binary crude oil blends. Two techniques—least square (LS) and genetic algorithm (GA)—were used to determine the parameters of the proposed models. Dynamic viscosity of 12 sets of crude oil blends at 298.15 K and 25 different shear rates were measured, resulting in 300 sets of binary data. Moreover, 700 sets of kinematic viscosity binary data were collected from literature sources and used along with 200 of the 300 sets of experimental binary data with a wide range of American Petroleum Institute (API) gravity (9.89–41.2) and viscosity (1.054–165,860 cSt) to examine existing available models as well as the newly developed models in this study. The remaining 100 experimental data points which were not used in the regression process were used for validating the models. The results in terms of the absolute average relative deviation (AARD%) were 33.546 and 14.195 for the LS method and 13.113 and 13.672 for the GA method for proposed models one and two, respectively. The results of statistical parameters based on the GA and LS methods showed that the GA is a superior method for new model parameter estimation as compared with the traditional LS technique. The GA-based models developed in this study provided the highest accuracy for viscosity calculation of the crude oil blends over all existing models in the literature.

Calculating the Viscosity of Crude Oil Blends by Binary Interaction Parameters Using Literature Data

Even though several blending rules have been developed to estimate viscosity of crude oil blends, most of them present significant deviations from real viscosity values. However, blending rules based on interaction parameters have shown to offer better predictions. In this work, experimental data reported in literature were used to calculate binary interaction parameters, while validation of the blending rule was performed with a different set of data to that employed for deriving such parameters. Comparison of experimental viscosity data and those calculated with the blending rule showed excellent prediction capability with minimal error. The values of the interaction parameters exhibited a clear relationship with temperature, thus they can be used to estimate viscosity of crude oil blends at different temperature.

Effect of physical sediments reworking on hydrocarbon degradation and bacterial community structure in marine coastal sediments.

The present study aimed to examine whether the physical reworking of sediments by harrowing would be suitable for favouring the hydrocarbon degradation in coastal marine sediments. Mudflat sediments were maintained in mesocosms under conditions as closer as possible to those prevailing in natural environments with tidal cycles. Sediments were contaminated with Ural blend crude oil, and in half of them, harrowing treatment was applied in order to mimic physical reworking of surface sediments. Hydrocarbon distribution within the sediment and its removal was followed during 286 days. The harrowing treatment allowed hydrocarbon compounds to penetrate the first 6 cm of the sediments, and biodegradation indexes (such as n-C18/phytane) indicated that biodegradation started 90 days before that observed in untreated control mesocosms. However, the harrowing treatment had a severe impact on benthic organisms reducing drastically the macrofaunal abundance and diversity. In the harrowing-treated mesocosms, the bacterial abundance, determined by 16S rRNA gene Q-PCR, was slightly increased; and terminal restriction fragment length polymorphism (T-RFLP) analyses of 16S rRNA genes showed distinct and specific bacterial community structure. Co-occurrence network and canonical correspondence analyses (CCA) based on T-RFLP data indicated the main correlations between bacterial operational taxonomic units (OTUs) as well as the associations between OTUs and hydrocarbon compound contents further supported by clustered correlation (ClusCor) analysis. The analyses highlighted the OTUs constituting the network structural bases involved in hydrocarbon degradation. Negative correlations indicated the possible shifts in bacterial communities that occurred during the ecological succession.

The optimization and prediction of properties for crude oil blending

Research into the properties of mixed crude oils has been the most important research for refineries and oil transportation. Because the desirable nature of mixed crude oils is a powerful guarantee for normal operations and corporate earnings. In this paper, the optimization and prediction model for Shanbei crude oil blending is established. The objectives were to improve the total yield of fractions and the compatibility and to reduce the viscosity of the mixed crude oils. After solving the model, two applicable proportions for mixed crude oils were given. With these proportions, two samples of mixed oils were prepared and distilled. The test results showed that the model was valid. The study of the viscosity and compatibility index was introduced to the optimization model because forecasting those properties in mixed crude oils has a certain significance.

An Optimization Model for Shanbei Crude Oil Blending

The basic properties of the Shanbei crude oils and its mixed were studied first. Then, a hybrid coefficient function for the viscosity of the mixed oils was introduced. With these, an optimization model of the proportion for the crude oils blending was established and solved. An applicable proportion for six Shanbei crude oils’ blending was given. With the proportion, one mixed oil was prepared and distilled. Fouling and coking are discussed with the simulation in the distillation to assist the optimization. The experiment results showed that the model was valid for the oils blending.

Incompatibility Determination of Crude Oil Blends from Experimental Viscosity and Density Data

In this work, a study to determine the incompatibility phenomenon in blends of crude oils mixed with a liquid hydrocarbon from experimental viscosity and density information is presented. The effect of the temperature and composition on asphaltene aggregates and asphaltene precipitation onset was investigated for two crude oil blends mixed with a refinery stream liquid hydrocarbon containing high isopentane and n-pentane concentrations. Dynamic viscosities of the system (crude oil containing asphaltenes and toluene) + n-heptane were measured to assess the changes of aggregation occurring in a crude oil under the influence of the temperature to determine the incompatible asphaltenes in the oil fraction of the liquid hydrocarbon. The method to detect the incompatibility of crude oil blends was based on experimental observations of an increase in the viscosity and density of the crude oil blends mixed with a liquid hydrocarbon, in which asphaltene particle aggregation occurs. From experimental determination of viscosities and densities, it was possible to determine an incompatibility region for the crude oil blends.

Global Optimal Scheduling of Crude Oil Blending Operations with RTN Continuous-time and Multiparametric Disaggregation

This paper addresses the modeling of crude oil operations in refineries assuming that all properties blend linearly. Guidelines are given on how to generate a Resource-Task Network superstructure that implicitly handles the complex logistics, while extending the scope of a well-known continuous-time formulation to variable recipe tasks with multiple input materials. The new single time grid formulation has the advantage of avoiding computationally inefficient big-M constraints, unlike previously proposed unit-specific and priority-slot based models. Through the solution of a set of test problems from the literature, we show that the resulting mixed-integer nonlinear programs can be solved close to global optimality by the commercial solver GloMIQO for the objective of gross margin maximization but not for operating cost minimization. We also show that adopting a two-step MILP-NLP algorithm where the mixed-integer linear relaxation is derived from multiparametric disaggregation can reduce the optimality ga...

Photometric Study of the Compatibility of Crude-Oil Blends

The results of photometric studies of solutions of various crude oil blends in aromatic and aliphatic solvents are reported. Compatible and incompatible combinations of components are indicated and a quantitative correlation between the optical density of the solutions and the composition of the crude oil blends is established. It is demonstrated that regardless of the nature of the solvent, the light absorption coefficient K of compatible blends is inversely proportional to the percentage ratio between resins and sum of paraffins and asphaltenes (R/P + As) and directly proportional to the density of the blends.

Stability of Real Asphaltene-Containing Systems in Presence of Bioadditives

The influence of synthetic surfactants and vegetable oils and their derivatives on the stability of Ashal’cha (Tatarstan) crude oil asphaltenes against precipitation is studied by methods of titration with n-heptane and determination of the quantity of the precipitate separated by reducing the dissolving power of the dispersion fluid. It is found that bioadditives containing –COOH and –OH groups in the molecule enhance crude oil stability most effectively. It is proved that loss of crude oil stability occurs upon injection of certain additives containing several polar groups in the molecule, which facilitates formation of bonds between asphaltene aggregates. In experiments simulating compounding of heavy and light paraffinous crude oils it is shown that addition of surfactants to crude oil blends, rather than to heavy crude, is most effective.

Heavy Crude Oil Viscosity Reduction and the Impact of Asphaltene Precipitation

One of the main challenges associated with the production of heavy or extra-heavy crude oil is transportation of the oil by pipelines, particularly without the prior reduction of the oil viscosity to acceptable values to ensure oil fluidity in the pipelines. The reduction of viscosity can be obtained by various sophisticated methods. In this study, we investigated different blending techniques to reduce the viscosity of heavy crude oil. The blending of Middle East heavy crude oil with light crude oil or with one of its distillates, such as kerosene or diesel, as diluents was conducted over the entire range of weight fractions at 20 °C and atmospheric pressure. The heavy oil viscosity was decreased from 4000 to 500 cP, representing an 88% reduction. The experimental data were fitted with an empirical equation, and the results were satisfactory, with an average absolute value of the deviation of 0.0015 cP. A negative performance of the heavy oil with diluent mixtures was identified based on the asphaltene precipitation phenomenon, which was found to depend on not only the type and composition of the diluents used but also the concentration of each diluent. To obtain additional insight into asphaltene precipitation, qualitative studies were performed with scanning electron microscopy imaging and dynamic light scattering. Compared to the other diluents, kerosene distillates performed well with a specific heavy crude oil sample under our testing conditions. The addition of 0.5–2 wt % of a solvent mixture of polar protic hexane-1-ol and nonpolar toluene to the crude oil and diluent mixture was found to successfully delay the precipitation of asphaltene in these low-viscosity mixtures.

Optimization Model of Crude Oil Distillation Units for Optimal Crude Oil Blending and Operating Conditions

This work presents the mathematical formulation of a nonlinear programming (NLP) model which optimizes simultaneously crude oil blending and operating conditions for a system of several crude oil distillation units (CDUs) at a Colombian refinery. The CDU system consists of three industrial units processing a blending of five extra-heavy crude oils and producing two commercial fuels, Jet-1A and Diesel. The NLP model involves typical restrictions (e.g., flow rate according to capacity of pumps, distillation columns, etc.) and the heat integration of streams from atmospheric distillation towers (ADTs) and vacuum distillation towers (VDTs) with the heat exchanger networks for crude oil preheating. A metamodeling approach is used so as to represent the ADTs. Preheating networks are modeled with mass, energy balances, and design equations of each heat exchanger. The NLP model has been implemented in GAMS using CONOPT as solver. Different cases are solved by the NLP model such that the optimal case with less profit increment had an economical benefit of 13% with respect to its case without optimization. In each optimal case the extra-heavy crude oils in the feed blending of each CDU required more severe operating conditions such as higher temperature of the crude oil at the entrance to the towers, greater flow rate of stripping steam at the bottom, and minor pressure of the tower tops.