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AZERBAIJAN CHEMICAL JOURNAL No 2 2020 ISSN 2522-1841 (Online)
ISSN 0005-2531 (Print)
UDC 622.276
ANALYSIS OF THE MODERN STATE OF RESEARCHES ON DEPOSITION OF ASPHALT-RESIN SUBSTANCES, PARAFFIN AND MODELING METHODS
REVIEW
PART I: PRECIPITATION OF ASPHALTENES M.R.Manafov, G.I.Kelbaliev
M.Nagiyev Institute of Catalysis and Inorganic Chemistry, NAS of Azerbaijan
mmanafov@gmail.com
Received 24.04.2019 Accepted 13.09.2019
Asphaltenes are the heaviest crude oil fraction and tend to self-associate and precipitate. The precipitation and deposition of asphaltenes during the production, refining, transportation of oil is the main for the oil industry, the precipitation of asphaltenes and their subsequent deposition can cause problems at all stages of production. Asphaltenes have different structures and molecular composition, they are a mixture of poorly defined components, they are self-associated even at very low concentrations, what makes them one of the most difficult components of crude oil. Since the deposition mechanism of paraffin wax differs from the deposition mechanism of asphaltenes, mathematical modeling of crystallization of paraffin will be considered separately in another work. Creating accurate asphaltene models that can predict the behavior of asphaltenes in various scenarios should help reduce asphaltene problems. This review is specifically devoted to advances in mathematical modeling of asphaltenes. Several different models have been proposed in the literature for predicting the initial conditions and precipitation of asphaltenes. Existing modeling approaches can be broadly classified into colloidal and thermodynamic models. It should be noted intelligent models, such as a vector machine, an artificial neural network, in recent years are increasingly used for modeling various parameters and properties in the oil and chemical industries. However, these models are a black box and cannot provide a clear link between the output and input parameters of the model. In the past few years, models based on the Cubic Plus EoS Association (CPA EoS) and Statistical associating fluid theory (SAFT) have been recognized as promising one for studying asphaltene sediments. However, in the literature, there exist different opinions. Therefore, a systematic study is important for modeling the deposition of asphaltenes. Over the past decades, several different models have been proposed to predict the onset of asphaltenes and the amount of asphaltenes deposited. This paper examines various models that have been proposed to predict asphaltenes deposition under changing thermobaric conditions. A brief summary of various research approaches is presented.The main focus is on the description of the basic assumptions underlying various models, as well as on the ability of the model to correspond to experimental data. The presented models are compared and current modeling trends for forecasting precipitation are shown. This work will help improve understanding of asphaltenes and provide recommendations for the proper study and modeling of asphaltenes in future research.
Keywords: crude oil, asphaltenes, association, precipitation, equations of state, modeling.
doi.org/10.32737/0005-2531-2020-2-6-19 Introduction
The ability of asphaltenes to plug wells, pipelines, ground equipment and pores in geological formations is well known. The data obtained from numerous laboratory studies and field work to solve this problem help oil companies cope with the formation of asphaltene deposits or restore them when they cannot be prevented.
One of the best methods to solve this problem is to modify production processes to prevent precipitation and deposits from an economic,
technical and environmental point of view. Other methods, such as chemical and mechanical ones, are used when modification of production processes is not possible. So, there are other problems. The fact is that different chemicals under different thermobaric conditions have different effects for different types of crude oil, which complicate their processing [1].
Therefore, there are many studies on the type and selection of chemicals that are compatible with various types of crude oil to reduce the deposition of asphaltenes.
Asphaltene formation and deposition
Changes in pressure, temperature, composition and sliding velocity can lead to the deposition of asphaltenes and the accumulation of deposits [2, 3]. These changes can occur due to various processes, such as primary depletion, injection of natural or carbon dioxide (Gas injection is one of the main types of enhanced oil recovery (EOR) methods), acid treatment or coproduction of incompatible fluids. Asphaltenes can accumulate in different parts of the system production, starting from the pores of the reservoir and ending with flow lines and ground equipment. Normally, the processes of oil recovery cause changes in the properties of the fluid (for example, changes in pressure, temperature and composition) which, in turn, can lead to the precipitation of asphaltenes [4, 5]. Asphaltenes are the most high molecular weight components of oil and differ significantly from the basic properties of other petroleum products, primarily their adhesive properties, ie high ability to adhere to contacting surfaces. The accumulation of a small amount of asphaltene on the rock grains of the oil reservoir and the internal surfaces of ground equipment, pipes and flow lines may not cause flow disturbance, however, over time the formation of their deposits of large thickness can lead to production shutdown [6].
Fig. 1. Solid deposits in the wellbore.
In such cases, to optimize production and take the necessary measures to modify the production cycle, information is required on the oil composition and the conditions under which the asphaltenes contained in it will precipitate from the solution. Heavy oils, characterized by the highest concentrations of asphaltenes, usually remain stable during production and therefore may not cause blockage in the wellbore. Diffi-
culties associated with the deposition of asphal-tenes are more characteristic of less viscous oils containing fewer asphaltenes and under a pressure significantly exceeding the saturation pressure. Oil-deposited asphaltenes have relatively high reactivity. Although asphaltenes are used in practice, for example, as vulcanizing agents, corrosion inhibitors, and as ion-exchange agents with high radiation resistance, anionic resins are co-monomers for epoxy resins, various adsorbents etc. their presence in the produced oil is usually considered a negative factor and it is accepted that they are a class of hydrocarbon components [7].
The plugging ability of asphaltenes also manifests itself at the stages following oil production, creating difficulties in oil refining, since asphaltenes constitute a significant part of heavy oils, which are increasingly being processed. As-phaltenes also affect the stability of oil-water emulsions and the wettability of the oil reservoir. The SARA method is usually used to study the content of crude oil in the laboratory [8].
Separation of crude oil into saturated hydrocarbons, aromatics, resins and asphal-tenes by SARA fractionation
Asphaltenes by this method (Figure 2) are separated from other hydrocarbon components by adding «-alkane, for example, n-heptane or propane. Then the remaining components, called maltens, are separated by passing their mixture through a chromatographic column with an adsorbent. Each of the components is released by washing it out (eluting) with various solvents. Resins form a class of substances distinguished by solubility characteristics, and in this are similar to asphaltenes: resins are a non-volatile polar component of crude oil, soluble in n-alkanes, but insoluble in liquid propane.
Natural hydrocarbon fluids form a continuous series of compositions from dry natural gas to bitumen. In this series, there is a significant increase in density and viscosity, and as the content of asphaltenes increases from 0 to about 20%, the color also changes - from transparent to dark brown. Some properties of asphaltenes have been known since the beginning of industrial oil production from the first drilled wells.
Fig. 2. Flowchart of the SARA method [9, 10].
The term "asphaltenes" was introduced by J.-B. Bussengo in 1837. So he called the residue from the distillation of bitumen, insoluble in alcohol, but soluble in turpentine. Today, a similar definition of asphaltenes is used: a residue insoluble in n-alkanes, such as n-pentane or n-heptane, but soluble in toluene. Such asphal-tenes are dark-colored brittle solids with a density of about 1.2 g/cm . Asphaltenes do not melt when heated, but pass into a plastic state at a temperature of about 3000C, decompose at a higher temperature with the formation of gaseous and liquid substances and a solid residue -
coke. Thus, at high temperatures, the following transformations occur:
Resin ^ Asphaltenes ^ Coke.
The asphaltene content is an important factor in determining how crude oil is refined. For this reason, a convenient laboratory method for finding it has been developed. The SARA method is based [11] on the separation of degassed oil (oil from which all gaseous components have escaped) into saturated hydrocarbons, aromatic compounds, resins and asphaltenes (saturates, aromatics, resins, asphaltenes - SARA) according to their solubility and polarity. The advantage of the SARA method is its simplicity and its applicability in many laboratories. However, it has some disadvantages. There are gaseous components in the reservoir oil, therefore, the results of the SARA analysis do not provide a correct idea of the behavior of the oil in real reservoir conditions. In addition, laboratory methods vary significantly, and the solubility data of asphaltenes depend on the type of n-alkane used to precipitate them. This means that for the same oil, you can get different SARA results depending on the precipitant (or solvent). The chemical structure of asphaltenes is slowly clarifying, but their average composition as a class is well known. Elemental analysis showed that they consist of carbon and hydrogen in a ratio of about 1:1.2. Unlike most hydrocarbon components, asphaltenes usually contain a small fraction of other atoms, such as sulfur, nitrogen, oxygen, vanadium and nickel. As for the structure of asphaltenes, experts agree that some carbon and hydrogen atoms form ring-shaped aromatic groups in which heteroatoms are also present. All other carbon and hydrogen atoms are located in alkane chains and cycloalkanes and are linked to ring groups.
Determination of asphaltenes, by solubility, and not based on chemical properties, makes their study more complicated than lighter hydrocarbons. The lighter hydrocarbon components -saturated hydrocarbons and aromatics - have a precise chemical structure. However, heavier as-phaltenes and related compounds, together with resins, are a unified residue, and their subsequent study is difficult or considered unpromising.
Resin-asphaltene substances (RAS)
Resin-asphaltene substances are one of the large groups of high molecular weight oil compounds. Characteristic features of RAS are a large molecular weight, the presence of various heteroatoms, polarity, paramagnetism, a tendency to form associations, polydisperse and colloidal dispersion properties. RAS asphaltenes are highly soluble in many organic solvents, including alkanes. Dark solids are soluble in arenes, carbon sulfides, but insoluble in n-alkanes. As-phaltenes differ from resins due to the high content of carbon and metals and a smaller amount of hydrogen, large sizes of polyaromatic nuclei, the average length of large aliphatic substitutes and the presence of atomic fragments. In contrast to the lighter components of a certain group of oil by the similarity of their chemical structure, the class criteria for RAS are their affinity for solubility in a particular solvent. With the exception of RAS, the residues of heat treatment of oil contain a small percentage of carbene and carbides. Chemical transformations as a result of high temperatures occur according to the following scheme: resins ^ asphaltenes ^ carbene ^ carbides.
Hotier and numerous scientists [7, 12, 13] proposed precipitants and solvents for as-phaltenes. According to this scale, solvents for
increasing the solubility of asphaltenes have the following series: < xylene < toluene < benzene < chloroform < pyridine. The order of precipitants to increase the ability to precipitate asphalts: n-decane < «-heptane < n-dodecane < «-hexadecane < squalane [1].
Asphaltene structure
Asphaltene is extremely complex. Several models were developed in an attempt to provide a standard method that could cover all different asphaltene chemical structures and simulate these structures [10, 14]:
1. Model of the archipelago
2. Continental model
3. Anionic Continental Model
4. Yen-Mullins Model
The pack model proposed by Jen to describe the structure of asphaltenes takes into account the presence of various chemical components in asphaltenes, such as polycyclic aromatic hydrocarbons, their compounds, saturated hydrocarbons (alkanes), and oil porphyrins [14]. Recent studies have identified many of the chemical compounds contained in oil and as-phaltenes and have led to the appearance of a modified Ian model or Yen-Mullins model [1517] (Figures 3-6).
Fig. 3. Archipelago asphaltene structure [15]. Fig.4. Continental asphaltene structure [16].
Fig. 5. Anionic continental asphaltene structure [16]
Black Oil: Asphaltene concentration is moderate. Nanoaggregates
Fig. 6. Yen-Mullins asphaltene model [17].
In the framework of Yen-Mullins model, the dependence of the molecular weight of as-phaltenes on the conditions of isolation and the nature of the solvent is easily explained by an association involving several levels of structural organization of asphaltenes.
Modeling the behavior of asphaltenes and their precipitation
According to literature, models for predicting asphaltene precipitation can be divided into three main categories: thermodynamic models, models based on fractal aggregation, and conjunctivistic models.
Scale models form the basis for aggregation methods. They are based on the properties of a mixture of asphaltene crude oil, such as dilution coefficient, resin to asphaltene ratio, percentage of heavy components, specific gra-
vity, temperature, pressure and so on.
Recently, artificial intelligence-based models have been proposed to overcome difficulties in studying asphaltene deposition processes. Such models using artificial neurons, Bayesian networks, and other advanced machine algorithms predict the amount of deposited asphaltenes under given conditions [18,19] and save time and resources, unlike other modeling categories. In [20], the simultaneous influence of operational parameters on the deposition of asphal-tenes was studied using a combination of the artificial neural network methodology and the response surface. The results showed that, despite the difficulty of deposition of asphalttenes, the combination of an artificial neural network with the methodology of the response surface can be successfully used to study the mutual influence
of various variables that affect the deposition of asphaltenes.
Despite the widespread use of thermo-dynamic and scale models for predicting asphal-tenes, they have some drawbacks. These models require a large number of experimental indicators and insufficiently accurate results with a wide and high pressure range. It is noted that in the model using artificial intelligence, they show greater consistency in predicting the results of asphaltenes compared to the scale model [21]. Despite all this, conjunctivistic models are more modern and younger than others, it is still difficult to interpret their results. In addition, many of them require a relatively large number of indicators [22, 23], which leads to an increase in the number of experiments.
In thermodynamic models, the behavior of asphaltenes is determined by the general rules of thermodynamics, and asphaltenes are a component of an imperfect mixture. In these models, various phase transitions are considered: liquid-liquid or liquid-solid particles and a forecast is made in accordance with these assumptions. Although the reversibility of precipitation of asphaltenes is widely discussed in the literature, a clear answer is still not possible. Thermodynamic models suggest that this process is reversible.
To describe the interaction of asphaltene molecules with other components, two different thermodynamic theories have been proposed: solubility models and colloidal models. Models based on the Flory-Huggins equation and equations of state related to the first theory. As colloidal models, one can cite solid-phase colloidal models of asphaltenes [24-26], thermodynamic model [27] of micelle formation [28]. Recent studies disproving the colloidal model are discussed by Punnapala and Vargas [29].
Asphaltene precipitation Modeling Approaches
Before discussing the mathematical models developed by various scientists to predict the deposition of asphaltenes, it is necessary to take into account that some researchers believe that the deposition and deposition of asphaltenes is not a reversible process [30].
The cause of the irreversibility of the process is the colloidal nature of suspensions of asphaltenes, which was confirmed by experimental observers [31].
Prediction and modeling of asphaltene precipitation are based on the theory of solubility and callloids. The solubility method assumes that solutions dissolve in crude oil and what happens when solubility falls below a certain threshold level [32].
The theory of regular solutions and the equation of state (EoS) are the two main approaches to the theory of solubility. The theory of colloidal solutions suggests that asphaltenes are in the form of colloidal particles, and adsorbed surfaces stabilize them [24].
The distribution of resins between the colloidal surface and the environment controls the solubility of asphaltene. If a sufficient amount of resin is desorbed, the stability of the asphaltenes will be compromised and they will collapse.
Solubility approach
Based on this approach, models are increasingly used to predict the deposition of as-phaltenes. These models use the concept of solubility parameters and suggest that crude oil consists of two phases: asphaltenes and deasphalted oil. The solubility parameters of asphaltenes are calculated using the equations of Scatchard [33] or Hildebrand [34] or by calculating the interaction of asphaltenes with other oil components. The properties of deasphalted oil are usually calculated using cubic equations of state. Solubility models believe that any change in the solubility parameter for any of the two phases leads to a change in their phase equilibria. A change in phase equilibrium can occur when liquid alkanes are added or gas is absorbed in deasphalted oil. The difference between the amount of asphal-tenes in oil and solubility under these conditions allows us to calculate the amount of precipitated asphaltene [35].
Tin, Hirasaki, and Chapman [36] showed that asphaltenes are unstable below a certain value of the oil solubility parameter, while Vargas et al. found that the solubility parameter is not always constant along the stability boundary of asphaltenes.
Models based on the theory of regular solutions, models based on the theory of Flory-Huggins and Scott Magat fall into this category. Although regular solutions and the Flory-Huggins theory suggests that asphaltenes have the same structure and properties, Scott Magat's theory suggests that asphaltenes have a heterogeneous structure. The theory of regular solutions is the simplest theory based on the concept of regular solutions.
Regular solutions have an ideal entropy of formation, despite an imperfect enthalpy of formation. Therefore, a random distribution of molecules in a solution takes place even in the presence of specific solvent-dissolved substance interactions. The theory of regular solution is based on the assumption that the enthalpy and entropy parts of the Gibbs free energy of formation can be considered separately and are additive. The theory of regular solutions is best explained using a lattice model. The key parameters for this approach are the molar volume and solubility parameters of each component. However, these parameters are mostly unknown for crude oil. Some authors have used cubic equations of state (CEoS) to estimate the solubility parameter and molar volumes of solvents [37]. The modified regular solution model [37] includes the Flory - Huggins entropy contribution from the difference in molecular sizes, as well as the enthalpy contribution from the regular solution or Scatchard-Hildebrand solubility theory [38].
Flory-Huggins theory
Each of the two scientists independently developed the theory of regular solutions by introducing a new Gibbs free energy equation of the polymer mixture. The Flory - Huggins approach can successfully predict both the beginning and the amount of asphaltene deposits, but it does not take into account the association of asphaltenes and the effect of compressibility on the phase behavior, which is estimated by the EoS approach [39].
Scott Makat Theory
They expanded the Flory-Huggins theory by applying a mixture of polymers of different lengths [40]. Later, based on this theory, other
authors proposed their own thermodynamic models [41, 42].
Models of the equation of state
These equations are widely used in the oil industry to calculate the phase equilibrium parameters with good accuracy and relative mathematical simplicity [43].
Cubic equation of state
Using the equations of state of the cubic type, one can simulate the behavior of both polar and nonpolar substances. An important advantage of cubic equations of state is that they can be used to describe the properties of the gas and liquid phases in the two-phase region. Moreover, the number of coefficients of the equation of state is relatively small. Such equations of state are successfully used for the analysis of phase equilibria in multicomponent systems. The most common of these equations were proposed by Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK) [43].
Cubic-plus-association equation of state
Attempts to use a wide range of equations have led to the creation of an equation of state of association: a cube-plus-association, which also considers asphaltene associations (CPA EoS). This equation of state initially associated the Soave-Redlich-Kwong equation of state with Wertheim's thermodynamic perturbation theory [43].
The equation for the case of cubic association was developed to describe the thermodynamic properties of associative fluids [44]. This equation has two parts. One part describes the influence of molecular interaction without association based on the cubic equation, and the other on the theory of thermodynamic excitation of polar interaction.
Statistical associating fluid theory (SAFT)
This theory was developed by Chapman and others using Wertheim's thermodynamic perturbation theory to a mixture [45, 46]. This theory was later expanded by other scientists (Gross, Sa-dovsky, etc.) [47]. The use of the SAFT case equations in studying the thermodynamic properties and behavior of a fluid was found in the scientific works of many scientists [48, 49].
SAFT was based on extensions and simplifications of Wertheim's first-order perturbation theory for associated fluids. SAFT is widely used for both polar and non-polar substances, including polymers. In SAFT, molecules are modeled as chains of connected spherical segments. Numerous forms of the SAFT equation of state have also been proposed. These forms differ only in the segment term used to explain the van der Waals attraction between the molecules. All forms use the same chain and association terms introduced in [50].
The perturbed-chain version of SAFT (or PC-SAFT) is usually adapted to simulate the deposition of asphaltenes from crude oil [47]. In short, asphaltene precipitation is modeled based on the size of the molecule and the van der Waals interactions. For each unassociated species in SAFT, the equation of state requires three physical parameters: a, the diameter of each molecular segment, m, the number of segments in the molecule and s/k, the interaction energy (van der Waals attraction) between each molecular segment. Two additional parameters are included for associating molecules: association energy and association volume.
The equation is usually written in terms of Helmholtz free energy as the sum of the contributions
Ahelm = aseg + achain + aassoc, where Ahelm is Helmholtz's free energy, assg is the free energy of individual monomeric spherical "segments" or in other words is a contribution to free energy due to interactions between monomers or individual segments, achain is a
change in free energy due to chain formation, and aasso° is a contribution of positions associations (aasso° is the contribution from the association sites).
The term chain formation refers to segments connected in linear chains (the same as polymer molecules), and the term association refers to the real shape of the associated molecules. Because of this separation of Helmholtz energy into three factors, many SAFT options could be achieved: each term can be considered separately and modified or new contributions can be added, for example polar and electrostatic
terms. The equation is very versatile, and evidence of this is the number of different versions of the theory developed over the years. Although the differences may be small, the main symptom leading to different versions is the choice of a reference fluid [36].
Colloid approach
The theory of colloids suggests that the deposition of asphaltenes is irreversible and that they are colloidal. According to this theory, in order to fully peptize asphaltenes in crude oil, a certain amount of resin is needed. In colloidal models, it is assumed that asphaltenes were dispersed in crude oil in the state of solid colloidal colloidal particles. They are stabilized by resins and adsorbed on the surface. Unlike solubility models, it is believed that in colloidal models, crude oil contains asphaltenes in the form of colloidal dispersions of resins. It is also believed that the latter acts as a peptizer. In these models, the deposition of asphaltenes is likely to largely depend on the chemical potential of the resins. Therefore, asphaltene deposition is measured under certain conditions necessary to interpret the chemical potential of the resins. These measurements and interpretations are then used as key input indicators for predicting the deposition of asphaltenes in other conditions [51].
The nature of the interaction between as-phaltenes and other oil components has not yet been fully studied, and practical and theoretical studies in this area are of great importance. Although the results according to the theory of colloids are not entirely accurate, it is assumed that asphaltenes are colloids in different degrees of association. This is illustrated by the Yen-Mullins model in [17].
Solubility Models
The most predictable model is used to predict the deposition of asphaltenes. The first such model, created in 1984, used a thermodynamic approach based on the reversible equilibrium of the solution to describe the stability of asphaltenes.
Hirschberg et al.
This is a simple thermodynamic model of the effect of asphaltene flocculation on light
fractions. The Flori-Huggins theory was used to calculate the amount of asphaltenes from the liquid phase [52]. In these models, a liquid containing asphaltene is presented as a combination of asphaltene and a solvent in the liquid phase. Its thermodynamic properties can be found using the Flory-Huggins solubility theory. Although this approach was easily implemented, it did not reflect the behavior of asphaltenes in experiments. Since then, the model has been updated several times. This improvement was mainly due to the calculation of solubility parameters and a description of the heavy fractions in crude oil. In the initial version of the model, the equilibrium between vapor and liquid was calculated to determine the properties of the liquid phase. Then, the equilibrium in the liquid-liquid phase was calculated. At that time, asphaltene was considered a pseudo-fluid, and it was assumed that the precipitated asphaltene phase does not affect the previously calculated parameters of vapor-liquid equilibrium. Then, the researchers began to take into account the effect of asphaltene deposition on the gas phase and began to calculate the three-phase equilibrium [53]. Thanks to studies conducted in 1995, the model expanded to include the thermodynamics of polymer solutions. Although using this model you can get good results about the behavior of asphaltenes, by calibrating the experimental results, in the case of oils with a composition different from the calibration, noticeable deviations occur [54].
Thomas et al.
To predict asphaltene deposition based on the Vaughn solubility theory [55] a multi-component model was proposed [56].
Chung et al.
They proposed a generalized forecasting model based on the thermodynamic principle of equilibrium of solids and liquids for organic solids, and tested it with experimental parameters for the deposition of paraffin and asphal-tene [27].
Cimino et al.
Cimino et al. [54] developed a model based on the hypothesis that phase separation results in a heavy liquid phase containing both
asphaltenes and a solvent fraction. (Hirschberg et al. suggested that the resulting asphaltene phase is pure asphaltene). It was also assumed that the light liquid phase does not contain as-phaltenes. The model proposed by Cimino et al. is based on measuring the cloud point for studying phase behavior. Model equation obtained by Cimino et al. showed a better match than the Hirschberg model for fitting reservoir oil data from several fields.
In addition, various studies have been conducted to improve solution models [52, 57].
Solid phase models
Solid models fall under the category of models using the cubic EoS approach. In solid models, precipitated asphaltenes are represented as a pure dense phase (solid phase), while the oil and gas phases are modeled using cubic EoS. A limitation of cubic EoS is its inability to take into account the effect of polar or associative effects, such as hydrogen bonds.
In the model proposed by Nghiem L. et al. [58] it was assumed that the heavy fraction of crude oil could be divided into two parts. One of these parts is precipitated and the other non-precipitated components. As precipitated components accepted asphaltenes. Although the application of this model is simple, it is necessary to find some experimental data to determine a number of parameters. In another three-phase model, asphaltenes are assumed to be one pseudo-component, while other components are considered solvents. This model is simple and allows you to calculate the asphaltene solution directly. However, this model does not take into account the influence of pressure, which is an important factor in the stability of asphaltenes [57, 59].
Another improved model was proposed by the authors for asphaltenes and paraffins of a related bond model [60]. For modeling in different pressure ranges, thermodynamic parameters were found by fitting experimental results with 4 oil samples with different asphalt-tenes contents.
Association model
The association model is based on several assumptions, the main ones of which are [9]:
1. asphaltene molecules exist mainly in the form of monomers in the mass of crude oil and aggregates (in the associated state) in the precipitated phase;
2. the association of molecules causes their precipitation;
3. the process of precipitation of asphaltenes is thermodynamically reversible;
4. the phase of precipitated asphaltenes is a pseudo-liquid.
This type of model combines conditions that describe the physical and chemical effects of the association of asphaltene molecules. It does not require indicators for each ingredient, molecular weight, molecule size and interaction energy of each component. Currently, SAFT uses the statistical associating fluid theory to search for thermodynamic properties.
To date, most of these models have been tested based on limited experiments. However, since not all of these models were developed before the molecular weight and structure of the asphaltenes were consistent, they cannot be considered reliable.
The recent increase in the number of scientific publications [61-69] devoted to a detailed analysis of various approaches to modeling RAC by world scientists proves the importance and prospects of developing improved mathematical models for predicting RAC.
Conclusions
RAC deposits are one of the main problems of industry. In recent years, numerous attempts have been made to model and predict the precipitation of asphaltenes and this process continues. This work will help us make maximum use of the key models used in this area, their advantages and disadvantages, as well as create new, more accurate ones. A comparison of the models shows that the use of PC SAFT equations of state in modeling and predicting deposits and taking into account the polydisper-sity of asphaltenes in the model are more promising directions.
Acknowledgment
This work was supported by the Science Foundation of "SOCAR" under the grant pro-
ject 04LR-AMEA (10/09/2019) at the acad. M.Nagiyev Institute of Catalysis and Inorganic Chemistry.
The authors are grateful to Professor G.A.Mansoori (University of Illinois at Chicago) for providing extensive information on asphaltenes and other heavy organics in petroleum fluids, as well as for censorious remarks.
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NEFTDON ASFALT-QATRAN, PARAFiNLORIiN CÖKMOSi PROSESiNiN MÜASiR VOZiYYOTiNiN VO PROSESiN MODELLO§DiRMOSi ÜSULLARININ ANALiZi
iCMAL
I HiSSO: ASFALTENLORiN CÖKMOSi
M.R.Manafov, Q.LKalbaliyev
Asfaltenlar xam neftin öz-özüna assosiasiyaya va gökmaya meylli an agir fraksiyasi dirlar. Neftin hasilatinda, emali va naql edilmasinda asfaltenlarin gökmasi va göküb yigilmasi neft sanayesinin asas problemidir, bela ki, bu göküntülarin yigilmasi istehsalin bütün marhalalarinda problemlar yarada bilar. Asfaltenlar müxtalif qurulu§a va molekulyar tarkiba malik olub, tam daqiq olmayan komponentlarin qari§igidirlar, onlar hatta az qatiliqda bela öz-özüna assosiasiya olunurlar va bu onlari xam neftin an mürakkab komponentlarindan biri edir. Parafinin gökma (kristalla§ma) mexanizmi asfaltenlarin gökmasindan farqli oldugu ügün, parafinlarin kristalla§masinin riyazi modella§dirilmasina ayrica olaraq növbati i§da baxilacaqdir. asvaltenlarin davrani§ini müxtalif ssenari larda proqnozla§dira bilan Daqiq asfalten modellarinin yaradilmasi, asfaltenlarin gökmasi ila bagli problemlarin azaldilmasina imkan veracakdir. Hazirda asfaltenlarin gökma prosesinin riyazi modella§dirilmasi ügün geni§ olaraq kolloid va hallolma modellari yayilmi§dir. Qeyd etmak lazimdir ki, son illar vektor ma§ini, süni neyron, Bayes §abakasi va digar mütaraqqi intellektual modellar neft va kimya sanayesinda müxtalif parametrlarin va xassalarin modella§dirilmasinda daha tez-tez istifada olunurlar. Lakin bu modellarin naticalarinin interpretasiyas, halalik arzu edilan saviyyada deyildir. Son illar Kubik-plyus-assosiasiya hal tanliyi (CPA EoS) va ststistik assosiasiya olmu§ mayelar nazariyyasi asasinda (SAFT) modellarin asfaltenlarin gökmasini proqnozla§dirmaq ügün daha perspektivli olduqlari qabul edilmi§dir. Lakin, adabiyyatda hala da, müxtalif raylara rast galmak olur. Son onilliklarda, asfaltenlarin gökmasinin ba§langici va gökan asfaltenlarin miqdarini proqnozla§diran bir sira müxtalif modellar taklif olunmu§dur. Taqdim olunan bu i§da termobar va digar §artlarin dayi§masi zamani asfaltenlarin gökmasini proqnozla§dirmaq ügün möxtalif modellara baxilir. Modella§dirmada müxtalif yana§malarin qisa xülasasi, müxtalif tadqiqatgilar tarafindan apanlmi§ i§larin tasviri verilir. Müxtalif modellarin asasinda dayanan asas ehtimallara va modelin tacrübi naticalarla uygunluq saviyyasina asas diqqat verilmi§dir. Taqdim olunmu§ modellar müqayisa edilmi§ va gökmanin proqnozla§dirilmasi ügün modella§dirilmanin müasir meyllar göstarilmi§dir. Taqdim olunan i§ galacak tadqiqat i§larinda asfaltenlarin gökmasinin düzgün modella§dirilma üsulunun segilmasinda kömak edacakdir.
Agar sözlar: xam neft, asfaltenlar, assosiasiya, gökms, hal tanliyi, modell3§dirilm3.
АНАЛИЗ СОВРЕМЕННОГО СОСТОЯНИЯ ИССЛЕДОВАНИЙ ПРОЦЕССА ОСАЖДЕНИЯ АСФАЛЬТО-СМОЛИСТЫХ ВЕЩЕСТВ, ПАРАФИНОВ И МЕТОДОВ МОДЕЛИРОВАНИЯ
ОБЗОР
I ЧАСТЬ: ОСАЖДЕНИЕ АСФАЛЬТЕНОВ
М.Р.Манафов, Г.И.Келбалиев
Асфальтены представляют собой самую тяжелую фракцию сырой нефти и склонны к самоассоциации и осаждению. Осаждение и отложение асфальтенов при добыче, переработке и транспортировке нефти является основной проблемой, стоящей перед нефтяной промышленностью, выпадение их и последующее осаждение могут вызвать проблемы на всех этапах производства. Асфальтены имеют различные структуры и молекулярный состав, представляют собой смесь плохо определяемых компонентов, они самоассоциируются даже при очень низких концентрациях, что делает их одними из самых сложных компонентов сырой нефти. Поскольку механизм осаждения парафинового воска отличается от механизма осаждения асфальтенов, математическое моделирование кристаллизации парафинов будет рассматриваться отдельно в другой работе. Создание точных ас-фальтеновых моделей, которые способны прогнозировать поведение асфальтенов в различных сценариях, должны помочь в уменьшении связанных с ними проблем. Настоящий обзор посвящен достижениям в математическом моделировании асфальтенов. В литературе предложен ряд различных моделей для прогнозирования начальных условий и количества осадков асфальтенов. Существующие подходы к моделированию можно широко классифицировать на коллоидные и термодинамические модели. Следует отметить интеллектуальные модели, такие как векторная машина, искусственная нейронная сеть, которые в последние годы всё чаще используются для моделирования различных параметров и свойств в нефтяной и химической промышленности. Тем не менее эти модели являются черными ящиками и не могут обеспечить четкую связь между их выходными и входными параметрами. В последние несколько лет модели, основанные на Cubic Plus EoS ассоциации (CPA EoS) и теории статистической ассоциированной жидкости (SAFT), признаны перспективными для изучения асфальтеновых осадков. Однако в литературе существуют разные мнения. Следовательно, систематическое изучение важно для моделирования осаждения асфальтенов. За последние десятилетия лет предложен ряд различных моделей для прогнозирования начала выпадения асфальтенов, а также количества осажденных асфаль-тенов. В данной работе рассматриваются различные модели, которые были предложены для прогнозирования осаждения асфальтенов при изменении термобарных условий. Представлено краткое резюме различных подходов к моделированию с последующим описанием работы, проделанной различными исследователями. Основное внимание сосредоточено на описании основных допущений, лежащих в основе различных моделей, а также на способности модели соответствовать экспериментальным данным. Представленные модели сравнены и показаны современные тенденции моделирования для прогнозирования выпадения осадков. Эта работа поможет улучшить понимание асфальтенов и дать рекомендации по правильному их изучению и моделированию в будущих исследованиях.
Ключевые слова: сырая нефть, асфальтены, ассоциация, осаждение, уравнения состояния, моделирование.
