Physicochemical Properties Of Crude Oil Research Articles

Impact of Different Oil Extraction Techniques on the Physicochemical Properties of Adansonia digitata Seed.

The seeds of baobab were found to have both industrial and domestic uses due to their essential oil qualities for topical medication. However, the seeds found in this study area in Ghana are underutilised and sometimes thrown away after being taken off the pulp. The present study is aimed at examining the impact of the two predominant techniques used for oil extraction from nonoily seeds, namely, mechanical extraction and Soxhlet (n-hexane) extraction, on both the oil yield and physicochemical properties of crude oil derived from baobab seeds. The study looked at the iodine value, peroxide value, acid value, colour, density, and other variables. Refractometers, chroma meters, and titration techniques were used for the determination of specific properties using standard methods. The Soxhlet method of oil extraction was superior in terms of maximum oil recovery, recording a value of 27.75%, in contrast to the mechanical method, which yielded a significantly lower recovery rate of 5.422%. The peroxide and iodine values were found to be 15.09 and 11.89 mEq/g and 85.89 and 88.45 g/100 g for the mechanical and Soxhlet extraction methods, respectively. Statistically significant differences (p ≤ 0.05) were observed between the two oil extraction methods in some of the properties measured. The study discussed the impact of these oil properties on the application of both food and nonfood products. Finally, the study has provided an essential set of data and information to enable product initiators in the cosmetic, food, and other industries to make informed decisions regarding the utilisation of baobab oil as a constituent in the formulation of products.

Deep chemometrics using one‐dimensional convolutional neural networks for predicting crude oil properties from FTIR spectral data

AbstractThe determination of physicochemical properties of crude oils is a very important and time‐intensive process that needs elaborate laboratory procedures. Over the last few decades, several correlations have been developed to estimate these properties, but they have been very limited in their scope and range. In recent years, methods based on spectral data analysis have been shown to be very promising in characterizing petroleum crude. In this work, the physicochemical properties of crude oils using Fourier transform infrared (FTIR) spectrums are predicted. A total of 107 samples of FTIR spectral data consisting of 6840 wavenumbers is used. One dimensional convolutional neural networks (CNNs) were used employing FTIR spectral data as the one‐dimensional input and Keras and TensorFlow were used for model building. The Root Mean Square Error decreased from 160 to around 60 for viscosity when compared to previous machine learning methods like partial least squares (PLS), principal component regression (PCR), and partial least squares regression with genetic algorithm (PLS‐GA) on the same data. The important hyper‐parameters of the CNN were optimized. In addition, a comparison of results obtained with different neural network architectures is presented. Some common preprocessing techniques were also tested on the spectral data to determine their impact on model performance. To increase interpretability, the intermediate neural network layers were analyzed to reveal what the convolutions represented, and sensitivity analysis was done to gather key insights about the wavenumbers that were the most important for prediction of the crude oil properties using the neural network.

ANALYSIS OF THE COMPOSITION AND STRUCTURE OF HEAVY OILS ACCORDING TO NMR SPECTROSCOPY

The results of studies of 1H and 13C NMR spectroscopy of heavy oil samples from the Timan Pechersk, Volga Ural oil and gas basins are presented. Knowledge of the chemical composition and physicochemical properties of crude oil, along with the particularities of geological and geochemical conditions is of paramount importance for solving the problems of the origin of crude oil and its subsequent processing. Information on the chemical composition of oil allows you to combine samples of crude oil from various fields before refining to achieve the necessary commercial and technical characteristics. 59.7-60.5% of β-CH3 groups were found in the samples, in β-CH2 and CH-groups to the aromatic ring, as well as the content of CH2- and CH-groups of saturated compounds. Dividing 13C NMR spectra into ranges shows a high content of methyl groups with the number of CH-groups in the alkyl fragments and CH and CH2-alkyl groups of naphthenic moieties attached to CH-group being 14.37-24.17%. A specific range of values is from 9.4 to 11.4 ppm. indicates methyl substituted octane, nonane or decane. It was found that the content of primary and secondary carbon atoms was in the range from 59.4-60.7%. The studied samples possess branched alkane chains. Comparison of the content of aromatic / aliphatic components allows us to determine the sample of the Volga Ural basin as a sample with a high content of aromatic component. The content of aromatic fragments varies in a wider range of 17-25.9%. From the data of 1H NMR-spectra of samples of heavy oils with different origin, viscosity and treatment it was found that crude and refined oils can differ in the content of olefin signals. For citation: Kolchina G.Yu., Poletaeva O.Yu., Leontev A.Yu., Movsumzade E.M., Loginova M.E., Kolchin A.V. Analysis of the composition and structure of heavy oils according to NMR spectroscopy. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2023. V. 66. N 6. P. 94-101. DOI: 10.6060/ivkkt.20236606.6783.

Physico-chemical properties of crude oil of Khaya senegalensis (Desr.) A. Juss according to bioclimatic zones in Chad

Physico-chemical properties of crude oil of Khaya senegalensis (Desr.) A. Juss according to bioclimatic zones in Chad

Cluster analysis of crude oils with k-means based on their physicochemical properties

The values of the physicochemical properties of crude oils vary significantly, depending on their geographical origins. A standard categorization of crude oils is grossly based on the density and sulfur content, not considering other properties that can have meaningful impacts on blending and in some refining processes. Cluster analysis is an unsupervised machine learning technique that categorizes observations based on their similarity. In this work, k-means clustering algorithm was applied to a wide range of physicochemical properties to identify groups of crudes oils with high affinity that possibly have similar behavior later on, in downstream operations.A data set from Galp SA refineries (located in Portugal) containing 454 observations, corresponding to values of 9 properties, from 45 different crude oil sources was used in the present analysis. After suitable preprocessing, k-means was applied using different cluster numbers, and their performance was evaluated through the internal validation metrics silhouette index and Local Cores-based Cluster Validity (LCCV) index. The recommend number of clusters was 3, which presented the best performance with a LCCV index of 0.39. Crude oils from the same source should be incorporated in the same cluster, and this was corroborated by external validation, with 1.8% of the observations were placed in a different cluster than the majority of same source crude oils. The proposed method was also able to identify observations with unusually high iron contents concerning the same source of crude oils when more clusters were considered.This work provides a methodology to obtain a better categorization of crude oils by using cluster analysis, allowing the refineries to know how similar crude oils and their sources are. This categorization is very useful for improving the formulation of crude blends and the crude oils quality control, with the goal to optimize further the refining operations.

Can fluid-substitution models continue to ignore the complex physicochemical properties of crude oil?

The mechanical nature of fluid-substitution models has always been recognized as a major cause of their limited predictive power. For instance, saturants are typically treated as simple fluids characterized only by their densities, viscosities, and moduli of elasticity; their chemistry is just ignored, even when that fluid is crude oil. However, crude oil is a complex mixture of several thousand organic compounds characterized by a variety of molecular weights, polarities, and polarizabilities, and the response of its rheological behavior to acoustic wave propagation is difficult to predict, especially when it resides in the pore space of rocks. We have performed ultrasonic-velocity measurements on carbonate core plugs saturated with a brine and with a light crude oil that are mechanically similar (i.e., having comparable densities, viscosities, and moduli of elasticity) and that show a significant and consistent excess of hardening when the saturant is oil. Dispersion and wettability are excluded as explanations for the data. We hypothesize that asphaltene aggregation and adsorption as well as paraffin-wax crystallization (and possibly volumetric expansion) combine to cause crude oil to exhibit a dilatant-like behavior within the pore space of carbonates at ultrasonic frequencies. In general, the observed effect would be similar to the hardening of ooblek at high deformation rates. This hypothesis could be tested in the future by an adequate combination of high-resolution imaging and microfluidic setups. This and similar studies would be beneficial in developing physical fluid-substitution models with a more consistent predictive power.

Prediction Model between Emulsified Water Fractions and Physicochemical Properties of Crude Oil Based on the Exergy Loss Rate.

The quantitative calculation of emulsified water fractions of crude oil–water systems is of great significance for the study of flow characteristics of multiphase flow pipelines. For a crude oil–water system with a high water fraction, the emulsified water fraction under different influencing factors was determined by emulsification experiments. It was found that the emulsified water fraction under different shearing conditions correlated well with the exergy loss rate and could be described by a power-law equation, in which two undetermined parameters relate to the crude oil physicochemical properties. Six representative parameters were selected to describe the crude oil physicochemical properties, i.e., the sum of asphaltene and resin contents, wax content, mechanical impurity content, crude oil acid number, crude oil average carbon number, and crude oil viscosity. Further, the correlations between the two undetermined parameters and the crude oil physicochemical properties were derived by regression analysis. Thus, the prediction model of emulsified water fraction was determined, which could be conveniently adopted to predict the emulsified water fraction with different crude oils and shearing conditions. The validation results showed that the mean relative deviation of the model prediction is 4.5%.

Nutritional Quality of Moringa oleifera Seeds and Physicochemical Properties of Its Crude Oil

This study aimed to evaluate the centesimal composition of Moringa oleifera Lam seeds and identify the physicochemical properties of crude oil extracted from Moringa oleifera Lam seeds. The values ​​found for the centesimal composition showed that the seeds are constituted by 41% of crude oil, 32.40% of proteins, 4.20% of ash, 19.54% of carbohydrate, and 2.86% of moisture. These results indicate that Moringa oleifera Lam seeds are a potential source for health and diet food products. Compared with oils from Moringa oleifera Lam seeds grown in other countries, the physicochemical characteristics found in the oil are in agreement with data from the literature. Therefore, Moringa oleifera Lam oil can be used as a potential source for the manufacture of several industrial products, such as food and cosmetics.

Reservoir alteration of crude oils in the Junggar Basin, northwest China: Insights from diamondoid indices

Reservoir alteration of crude oils is ubiquitous in petroleum reservoirs. Alteration can change the composition and physicochemical properties of crude oils, and complicate oil–source correlations and origin studies of crude oils. Thus, the identification and assessment of reservoir alteration could provide a better understanding of the formation and evolution of crude oils. In this study, the effects of reservoir alteration (e.g., biodegradation, gas washing, water washing, and mixing) on oils in the Junggar Basin, northwest China, were identified and assessed by combining diamondoid indices with other commonly studied crude oil properties. The results indicate that: (1) diamondoid indices can be used to evaluate the intensity of reservoir alteration on oils (e.g., slight biodegradation and water washing has no effect on diamondoids; moderate biodegradation and water washing can result in a marked increase in diamondoid concentrations; severe biodegradation and water washing significantly changes diamondoid concentration and isomerization ratios); (2) diamondoid indices can assist in determining the type of reservoir alteration of oils (e.g., condensate formed by gas washing has a lower diamondoid concentration than that generated by thermal cracking; differing from biodegradation and water washing, gas washing can affect diamondoid ratios; mixing can be identified by a combination of diamondoid concentrations and other parameters, such as API gravity and biomarker indices in oils). Therefore, diamondoids provide specific information as to the reservoir alteration of oils, which is useful in further understanding of the origin and evolution of crude oils in the Junggar Basin.

Evaluating physicochemical properties of crude oil as indicators of low-salinity\u2013induced wettability alteration in carbonate minerals

The injection of low-salinity brine enhances oil recovery by altering the mineral wettability in carbonate reservoirs. However, the reported effectiveness of low-salinity water varies significantly in the literature, and the underlying mechanism of wettability alteration is controversial. In this work, we investigate the relationships between characteristics of crude oils and the oils’ response to low-salinity water in a spontaneous imbibition test, aiming (1) to identify suitable indicators of the effectiveness of low-salinity water and (2) to evaluate possible mechanisms of low-salinity–induced wettability alteration, including rock/oil charge repulsion and microdispersion formation. Seven oils are tested by spontaneous imbibition and fully characterized in terms of their acidity, zeta potential, interfacial tension, microdispersion propensity, water-soluble organics content and saturate-aromatic-resin-asphaltene fractionation. For the first time, the effectiveness of low-salinity water is found to positively correlate with the oil interfacial tension in low-salinity water. Oils with higher interfacial activity are found to respond more positively to low-salinity water. Moreover, cryogenic transmission electron microscopy images suggest that microdispersion is essentially macroemulsion, and its formation is an effective indicator – but not the root cause – of wettability alteration. The repulsive zeta potential for the rock and the oil in low-salinity water is found to be an insufficient condition for wettability alteration in carbonate minerals.

Correlation of Physicochemical Properties of Bach Ho Oils with Proton NMR Relaxation Parameters and Their Temperature Dependence

The physicochemical properties of crude oils (density, viscosity, asphaltene concentrations) from the Bach Ho oilfield (Vietnam) have been correlated with 1H NMR relaxation parameters (spin–lattice and spin–spin relaxation times T1i and T2i, respectively), and their temperature dependence has been studied. The results are discussed in terms of the concept of the formation of structural units (SU) in oils. The standard “alkane line”—the conventional correlation ηТ1,2 = const/Т for viscous oils—has been refined. The temperature dependences of T1,2i have been obtained, which manifest ordering processes in the test oils.

Effect of Oxidative Treatment on the Physicochemical Properties of Crude Oils

An effect of oxidative processes on the physicochemical parameters of crude oils is studied. The following physicochemical parameters of oil are found: the acidity of its individual fractions, the elemental composition, the density, and the viscosity. The IR data of crude oil and its individual fractions are given.

Quantitative Structure-Activity Relationship (QSAR) analysis of functionalized triblock copolymers with applications as dehydrating agents of crude oil

QSAR analysis was applied to obtain the water removal efficiency (WRE) values of triblock copolymers functionalized with tertiary amines, employed as demulsifier agents of crude oil. Taking into account the evaluation of F- and G-series reported by Zamora et al., the H-series was synthesized based on a triblock copolymer of 1920 g mol−1, and evaluated in CM1 and CM2 crude oils (7.5 and 18.7 °API). In addition, quantum and QSAR parameters, physicochemical properties of crude oil were included in the QSAR analysis. 66 WRE values were considered in the training set. Q2 value was established to weigh up an equation as acceptable, achieving eight equations, T1 – T8, for the training set. About external validation, F-, G- and H-series were assessed in CM3 heavy crude oil (16.9 °API), considering an overall of 33 WRE values for the validation. For the external validation, the coefficient of the prediction set (R2EXT), the predictive squared correlation coefficient (Q2Fn), the metric value (r2m), the concordance correlation coefficient (CCC), and the regression line slopes (k and k’) criteria were obtained. Only two equations, T1 and T8, complied with threshold established in the validation criteria. About r2m criterion, T8 equation gave a better correlation, 0.62, than that of T1 equation, 0.58. However, both equations could be optimal to calculate the water removal efficiency. Regarding physicochemical parameters of crude oil, number average molecular mass and run-off temperature were the unique parameters showing a clear effect over the calculated water removal efficiency.

A comparative study of Iraqi crude oil taken from the Nasiriyah refinery with various local and global crude oils.

In the present work, was evaluated and compared some physicochemical properties of crude oil which is obtained from Nasiriyah refinery in south of Iraq with some physicochemical properties of various local and global of crude oils. Many methods were used in this study to evaluate some chemical content as sodium ,potassium ,calcium, magnesium, vanadium,Iron, copper, lead and nickel in samples of Iraqi Oil in Nasiriya Refinery , as well as some physical properties included color , density, Ash content wt%, carbon residue wt% , water, salt , Sulfur content % wt, Heat of combustion Kcal/Kg , Thermal conductivity, Specific heat and Latent heat of vaporization were determinate . Also in this study viscosity were measured with different temperatures to observe the effect of temperature on oil viscosity. Range concentration of metals can be cleared by the series Ca > Na > Mg> V > Ni > K > Fe> Pb > Cu. The present study has shown that high levels of metals ions in oil refinery whereas the physical properties were closed to previous findings conducted on a crude oil in Iraq and other countries. The study recommended to possible using of high levels of heavy metals in oil in scientific and industrial purposes as well as removal these metals contribute in reducing of contaminations problems.

Investigation of crude oils compatibility and relationship with their properties

The compatibility/incompatibility of crude oils will affect the asphaltene precipitation and finally for sludge deposition if such oils are storaged or blending together. Normally, the refineries process a mixture of several crude oils owing to economic, technical and political aspects. In this study, four crude oils were characterized and investigated in order to determine physical-chemical properties and insolubility number (IN) and blending solubility number (SBN). The result revealed that two pair of crude oils are fully compatible and the remaining are partly compatible. The volume limitation of each crude oil in the mixture is proposed. In addition, the relationship between the compatibility and physico-chemical properties of crude oils is discussed. In fact, the crude oil which possessed high wax content and low resins to asphaltenes ratio possesses low stability. This finding might provide a new and valuable strategy for solving the foulings in crude oil tanks and processing units in refineries.

Construction of prediction intervals for carbon residual of crude oil based on deep stochastic configuration networks

Complex components lead to large fluctuations in the physicochemical properties of crude oil which make accurate prediction more difficult. To quantify the potential uncertainty associated with prediction, this paper proposes a novel approach to construct prediction intervals (PIs) for the carbon residual content of crude oil based on the lower-upper bound estimation (LUBE) method and deep stochastic configuration networks (DSCNs). According to the principle of stochastic configuration networks, the input weights and biases of DSCN are randomly assigned with a supervisory mechanism and only the output weights need to be evaluated which can greatly reduce the number of parameters to be optimized. Then, combining the coverage width-based criterion and mean accumulated width deviation, a new cost function of DSCN for constructing PIs based on the LUBE method is proposed to center the mean values of the PIs as near as possible to the targets, hence the average of lower and upper bounds of the PI is calculated as the deterministic output, which can solve the problem that the PIs based on the original LUBE method cannot provide the deterministic prediction. Moreover, a modified backtracking search optimization algorithm, improving the population diversity and increasing the search capability while maintaining the convergence speed, is presented to obtain the optimal PIs. Finally, experiments using real-world data are carried out and the results demonstrate that the proposed approach can construct PIs with high quality.

Hydroprocessing of heavy residual oil: Opportunities and challenges

Recently, significant changes in petroleum sources have been observed where light crude sources are becoming heavy or extra heavy, containing a large number of contaminants (S, N, metals, asphaltene, etc.), and producing a significant fraction of the bottom of the barrel (residue) after distillation. Thus, the future crude slate is a vital issue facing refiners to invest strategically in processing larger quantities of sourer crude. Due to the feedstock, refinery process operations must advance and include next-generation processes and catalysts to fulfill the demand and supply. The qualities of these products primarily meet or satisfy stringent environmental regulations. On the other hand, traditional light crude oil refineries have seen drastic changes into heavy crude oil, which present enormous challenges to the refining industry to process heavier crude oils. The global trend indicated that the world oil refining industry has to face several challenges in demand as well as supply. At the same time, refineries are expected to be under a great deal of pressure to accomplish the market demand for high-quality fuels (i.e., gasoline and diesel). The global demand for diesel fuels is increasing, while fuel oil demand is decreasing. The fuel composition and their efficiency (energy content) remain a decisive factor for the price and the communally acceptable parameter. This review will focus primarily on the relationship between the various parameters of composition, physicochemical properties of crude oil, and their impact on hydroprocessing.

Features of the composition and properties of crude oil from the Bavly oil field of the Volga-Ural oil and gas province

The article presents the results of a comparative analysis of the composition and physicochemical properties of crude oils produced from different horizons of the Carboniferous and Devonian deposits of the Bavly oil field (Tatarstan, Russia), including the Zavolzhsky and the Dankovo-Lebedyan horizons attributed to the domanic deposit. It is shown that oils from the domanic deposit are similar to Carboniferous oils by composition and properties but have unique features. A cluster analysis of the obtained results was carried out.

Determination of flash point and Reid vapor pressure in petroleum from HTGC and DHA associated with chemometrics

Flash point (FP) and Reid vapor pressure (RVP) are physicochemical properties of crude oil that are used as safety and environmental parameters. In this paper, we propose a methodology for estimating the FP and RVP for crude oil by means of detailed hydrocarbon analysis (DHA) and high temperature gas chromatography (HTGC) associated with partial least squares (PLS) regression. These techniques were used due to their direct relationship to FP and RVP. We studied 107 crude oil samples (with an API gravity range of 11.4–54.0) collected from a Brazilian sedimentary basin. The curve data derived from these two techniques were merged to better describe the true boiling point curve. Using fusion information drawn from the two chromatographic techniques (DHA and HTGC), we estimated the flash point with an average error of 5.3 °C and a coefficient of determination of approximately 0.9. While the data fusion represents an information gain in the estimation of the flash point, for to estimate the Reid vapor pressure, the HTGC data are sufficient. The PLS regression generated the best Reid vapor pressure results, with an average error of 0.4 kPa and with a coefficient of determination of above 0.99.

Laboratory characterization of crude oil and sandstone reservoir for chemical enhanced oil recovery

PurposeBecause of the increasing global oil demand, efforts have been made to further extract oil using chemical enhanced oil recovery (CEOR) methods. However, unlike water flooding, understanding the physicochemical properties of crude oil and its sandstone reservoir makeup is the first step before embarking to CEOR projects. These properties play major roles in the area of EOR technologies and are important for the development of reliable chemical flooding agents; also, they are key parameters used to evaluate the economic and technical feasibilities of production and refining processes in the oil industries. Consequently, this paper aims to investigate various important physicochemical properties of crude oil (specific gravity; American Petroleum Institute [API]; viscosity; pour point; basic sediment and water; wax; and saturate, aromatic, resins and asphaltenes components) and sandstone reservoir makeup (porosity, permeability, bulk volume and density, grain volume and density, morphology and mineral composition and distributions) obtained from Malaysian oil field (MOF) for oil recovery prediction and design of promising chemical flooding agents.Design/methodology/approachThree reservoir sandstones from different depths (CORE 1; 5601, CORE 2; 6173 and CORE 3; 6182 ft) as well as its crude oil were obtained from the MOF, and various characterization instruments, such as high temperature gas chromatography and column chromatography for crude’s fractions identification; GC-simulated distillation for boiling point distribution; POROPERM for porosity and permeability; CT-Scan and scanning electron microscopy-energy dispersive X-ray for morphology and mineral distribution; wax instrument (wax content); pour point analyser (pour point); and visco-rheometre (viscosity), were used for the characterizations.FindingsExperimental data gathered from this study show that the field contains low viscous (0.0018-0.014 Pa.s) sweet and light-typed crude because of low sulfur content (0.03 per cent), API gravity (43.1o), high proportion of volatile components (51.78 per cent) and insignificant traces of heavy components (0.02 per cent). Similarly, the rock permeability trend with depth was found in the order of CORE 1 < CORE 2 < CORE 3, and other parameters such as pore volume (Vp), bulk volume (Vb) and grain volume (Vg) also decrease in general. For grain density, the variation is small and insignificant, but for bulk density, CORE 2 records lower than CORE 3 by more than 1 per cent. In the mineral composition analysis, the CORE 2 contains the highest identified mineral content, with the exception of quarts where it was higher in the CORE 3. Thus, a good flow crude characteristic, permeability trend and the net mineral concentrations identified in this reservoir would not affect the economic viability of the CEOR method and predicts the validation of the MOF as a potential field that could respond to CEOR method successfully.Originality/valueThis paper is the first of its kind to combine the two important oil field properties to scientifically predict the evaluation of an oil field (MOF) as a step forward toward development of novel chemical flooding agents for application in EOR. Hence, information obtained from this paper would help in the development of reliable chemical flooding agents and designing of EOR methods.