Deasphalting of heavy crude oil by hexamethyldisiloxane: The effect of a solvent/oil ratio on the structure, composition, and properties of precipitated asphaltenes

Ilyin, Sergey O.; Ignatenko, V. Ya.; Kostyuk, Anna V.; Левин, И. С.; Бондаренко, Г. Н.

doi:10.1016/j.petrol.2021.109329

Cited by 20 publications

(14 citation statements)

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“…The weight average molecular weight, dispersity, and softening point of ARB were 828 g/mol, 1.14, and 71 °C, respectively. ARB consisted of 19.3% heptane-insoluble asphaltenes and 49.7% resins, while the rest were admixtures of heavy aromatic compounds and crystallizing saturates [ 95 ].…”

Section: Methodsmentioning

confidence: 99%

“…At the same time, due to the similarity of the properties of hydrocarbon resins and asphaltenes, the latter can act as a tackifier for polymer adhesive production. Moreover, asphaltenes do not need to be hydrogenated, since some methods of heavy crude oil deasphalting allow extracting resins (crude oil consists of saturates, aromatics, resins, and asphaltenes [ 92 ]) along with asphaltenes [ 93 , 94 , 95 ].…”

Section: Introductionmentioning

confidence: 99%

“…Resins are natural crude oil surfactants [ 96 , 97 , 98 , 99 ] that stabilize asphaltenes [ 100 ] and improve their interaction with various media, including polymer matrices [ 81 ]. However, the viscosity of resins and asphaltenes is quite high even in the molten state [ 95 ], so a plasticizer may still be required to create a polymer adhesive. Naphthenic oil is a rational choice, taking into account the miscibility of asphaltenes with cycloaliphatic compounds and their insolubility in linear alkanes [ 83 , 101 ].…”

Section: Introductionmentioning

confidence: 99%

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Hot-Melt and Pressure-Sensitive Adhesives Based on Styrene-Isoprene-Styrene Triblock Copolymer, Asphaltene/Resin Blend and Naphthenic Oil

et al. 2022

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Asphaltene/resin blend (ARB) extracted from heavy crude oil was used to modify poly(styrene-block-isoprene-block-styrene) (SIS) to make it an adhesive. There were prepared double and triple mixtures containing 10–60% SIS, 10–40% ARB, and 10–50% naphthenic oil used as an additional plasticizer. The viscoelasticity of the mixtures at 25 °C and 120 °C was studied, their flow curves were obtained, and the temperature dependences of the loss tangent and the components of the complex modulus were measured. In addition, the mixtures were used as hot-melt adhesives (HMAs) and pressure-sensitive adhesives (PSAs) in the shear, peel, and pull-off tests of the adhesive bonds that they formed with steel. Both naphthenic oil and ARB act as plasticizers for SIS and make it sticky. However, only the combined use of ARB and the oil allows for achieving the best set of adhesive properties of the SIS-based mixture. High-quality HMA requires low oil content (optimal SIS/ARB/oil ratio is 50/40/10, pull-off adhesion strength (τt) of 1990 kPa), whereas a lot of the oil is needed to give SIS characteristics of a PSA (SIS/ARB/oil is 20/40/40, τt of 100 kPa). At the same time, the resulting PSA can be used as a hot-melt pressure-sensitive adhesive (HMPSA) that has many times lower viscosity than HMA (13.9 Pa·s versus 2640 Pa·s at 120 °C and 1 s−1) but provides a less strong adhesive bond (τt of 960 kPa).

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hot-Melt and Pressure-Sensitive Adhesives Based on Styrene-Isoprene-Styrene Triblock Copolymer, Asphaltene/Resin Blend and Naphthenic Oil

et al. 2022

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“…Resins and asphaltenes have the best tendency to associate among all the fractions of crude oil. However, high-molecular-weight alkanes, polycyclic aromatic hydrocarbons, and their mixtures also exhibit associative characteristics. − Paraffin hydrocarbons tend to form a network of flexible crystals and deposit on surfaces. High-molecular-weight alkanes, characterized by a particular propensity to associate, are primarily responsible for the gel-like state of paraffinic oils, usually observed at temperatures below 30–45 °C.…”

Section: Introductionmentioning

confidence: 99%

Influence of High-Molecular n-Alkane Associates on Rheological Behavior of the Crude Oil Residue

et al. 2022

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In this paper, we present the results of chemical and physical investigations of the crude oil residue of low-sulfur but high-paraffin-base crude oil produced from the Mangyshlak (Kazakhstan) reservoir. The object contains 14.6 wt % of resins and significant amounts of high-molecular alkanes. A non-Newtonian behavior of the system is preserved even at 70–90 °C. 1H NMR data revealed divergence in temperature-dependent ratios corresponding to the low-viscous liquid petroleum products. The experimental results indicate the existence of associations of n-alkanes among themselves, as well as with resins and asphaltenes in the composition of the crude oil residue sample. In paraffin-base crude oil, the size of such associates (coacervates) is in the range of 100–300 nm. The associative behavior of medium- and long-chain n-alkanes is explained by their existence in transitional plastic (rotator) phases. As building blocks, associates of n-alkanes can be combined into worm-like structures due to adsorption of resins and asphaltenes on their surface and adhesion, thereby determining the non-Newtonian behavior and thixotropy of the system. Worm-like structures may be partially destructed under shear thinning (torn into shorter pieces) but can regenerate their structure over time. The optical and electron microscopy results justify the asphaltene aggregation model proposed by Balestrin and Loh. The formation of coacervates from asphaltene and concomitant molecules, which are surrounded by solvation shells of high-molecular alkanes, is evidenced. It is proposed that high-molecular n-alkane associates, as well as coacervates containing asphaltene and concomitant molecules, are compositional parts of many oil dispersed systems.

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“…Asphaltene is the most polar and the heaviest component of crude oils, having a sophisticated molecular architecture that is defined in terms of solubility in different substances. − Asphaltenes can be dissolved in aromatic hydrocarbons (e.g., toluene and benzene), and it is not soluble in paraffinic solvent with low molecular weight, including n -hexane, n -heptane, and n -pentane. ,, Asphaltene aggregation increases the crude oil viscosity and promotes the stability of water-in-oil emulsions, implying the need for removing them from crude oil. Asphaltene precipitation can result in undesired wettability alteration, plugging wellbores, and permeability reduction leading to flow assurance issues, equipment damage, increased capital/operation costs, and decreased production. , …”

Section: Introductionmentioning

confidence: 99%

Asphaltene Precipitation Prediction during Bitumen Recovery: Experimental Approach versus Population Balance and Connectionist Models

et al. 2022

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Deasphalting bitumen using paraffinic solvent injection is a commonly used technique to reduce both its viscosity and density and ease its flow through pipelines. Common modeling approaches for asphaltene precipitation prediction such as population balance model (PBM) contains complex mathematical relation and require conducting precise experiments to define initial and boundary conditions. Machine learning (ML) approach is considered as a robust, fast, and reliable alternative modeling approach. The main objective of this research work was to model the effect of paraffinic solvent injection on the amount of asphaltene precipitation using ML and PBM approaches. Five hundred and ninety (590) experimental data were collected from the literature for model development. The gathered data was processed using box plot, data scaling, and data splitting. Data pre-processing led to the use of 517 data points for modeling. Then, multilayer perceptron, random forest, decision tree, support vector machine, committee machine intelligent system optimized by annealing, and random search techniques were used for modeling. Precipitant molecular weight, injection rate, API gravity, pressure, C 5 asphaltene content, and temperature were determined as the most relevant features for the process. Although the results of the PBM model are precise, the AI/ML model (CMIS) is the preferred model due to its robustness, reliability, and relative accuracy. The committee machine intelligent system is the superior model among the developed smart models with an RMSE of 1.7% for the testing dataset and prediction of asphaltene precipitation during bitumen recovery.

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Deasphalting of heavy crude oil by hexamethyldisiloxane: The effect of a solvent/oil ratio on the structure, composition, and properties of precipitated asphaltenes

Cited by 20 publications

References 97 publications

Hot-Melt and Pressure-Sensitive Adhesives Based on Styrene-Isoprene-Styrene Triblock Copolymer, Asphaltene/Resin Blend and Naphthenic Oil

Hot-Melt and Pressure-Sensitive Adhesives Based on Styrene-Isoprene-Styrene Triblock Copolymer, Asphaltene/Resin Blend and Naphthenic Oil

Influence of High-Molecular n-Alkane Associates on Rheological Behavior of the Crude Oil Residue

Asphaltene Precipitation Prediction during Bitumen Recovery: Experimental Approach versus Population Balance and Connectionist Models

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