The Impact of CO2 Injection and Pressure Changes on Asphaltene Molecular Weight Distribution in a Heavy Crude Oil: An Experimental Study

Abstract

This work concerns observing the pressure as well as CO₂ mole percentage effects on asphaltene molecular weight distributions at reservoir conditions. A high-pressure, high-temperature asphaltene measurement setup was applied, and the amount of precipitated asphaltene at different pressures as well as CO₂ mole percentage in an Iranian heavy crude oil was measured. Moreover, the asphaltene molecular weight distributions during titration of crude oil with different n-alkanes were investigated. The gel permeation chromatography (GPC) apparatus was used for characterization of asphaltene molecular weight under different conditions. It has been observed that some thermodynamic changes such as pressure depletion above the bubble point increase the average molecular weight of asphaltene and cause the asphaltene molecular weight distributions changes from a bimodal curve with two maxima to a single maxima curve. One the other hand, below the bubble point, pressure reduction causes a decrease in the average molecular weight of asphaltene and also causes the shape of asphaltene molecular weight distributions to restore, which might be due to dissolution of asphaltene aggregates. An interesting result is that asphaltene molecular weight distribution at the final step of pressure reduction tests, ambient condition, shows approximately the same trend as the distribution of asphaltene molecular weight obtained at reservoir condition. This behavior explains the reversibility of the asphaltene precipitation process under pressure depletion conditions. In the case of CO₂ injection, the graphs of asphaltene molecular weight distributions always show a single modal trend and shift toward larger molecular weight values when CO₂ mole percentage increases. The results of this work can be imported to thermodynamic models that use polydisperse data of heavy organic fractions to enhance their performance at reservoir conditions. The distributions obtained by this method are good indicators of asphaltene structures at reservoir conditions.     

A Thermodynamic Model for the Prediction of Asphaltene Precipitation

Abstract

Asphaltene precipitation in reservoirs, wells, and facilities can have a severe and detrimental impact on the oil production. Due to the extreme chemical complexity of the asphaltene and crude oil and the lack of comprehensive experimental data, the modeling of asphaltene precipitation in crude oil remains as a challenging task. In this article, a compositional thermodynamic model was developed to predict asphaltene precipitation conditions. The proposed model is based on a cubic equation of state with an additional term to describe the association of asphaltene molecules. Extensive testing against the literature data, including asphaltene precipitation from crude oil and solvent injection systems, concludes that the proposed model provides reasonable predictive results.     

Prediction of Asphaltene Precipitation during Pressure Depletion and CO2 Injection for Heavy Crude

Abstract

In this work, a thermodynamic approach is used for modeling the phase behavior of asphaltene precipitation. The precipitated asphaltene phase is represented by an improved solid model, and the oil and gas phases are modeled with an equation of state. The Peng-Robinson equation of state (PR-EOS) was used to perform flash calculations. Then, the onset point and the amount of precipitated asphaltene were predicted. A computer code based on the solid model was developed and used for predicting asphaltene precipitation data reported in the literature as well as the experimental data obtained from high-pressure, high-temperature asphaltene precipitation experiments performed on Sarvak reservoir crude, one of Iranian heavy oil reserves, under pressure depletion and CO₂ injection conditions. The model parameters, obtained from sensitivity analysis, were applied in the thermodynamic model. It has been found that the solid model results describe the experimental data reasonably well under pressure depletion conditions. Also, a significant improvement has been observed in predicting the asphaltene precipitation data under gas injection conditions. In particular, for the maximum value of asphaltene precipitation and for the trend of the curve after the peak point, good agreement was observed, which could not be found in the available literature.     

Modeling of Coprecipitation of Resin and Asphaltene in Crude Oil by Association Equation of State

Abstract

Resin content is an effective parameter that has adverse effect on precipitation of asphaltene in crude oil. Fluctuations in temperature, pressure, or oil composition disturb the chemical equilibrium in a reservoir, which results in coprecipitation of resin and asphaltene. In this work, coprecipitation of resin and asphaltene has been modeled using an association equation of state (AEOS) in which asphaltene and resin are considered associate components of oil. According to association fluid theory, the total compressibility factor is assumed to be the sum of physical and chemical compressibility factors. Liquid–liquid and liquid–vapor equilibrium calculations are accomplished with the assumption that asphaltene and resin do not contribute in the vapor phase. Comparison of experimental asphaltene precipitation with that obtained from the model developed proves the acceptability of the proposed model.     

An Experimental Investigation of Asphaltene Precipitation During Natural Production of Heavy and Light Oil Reservoirs: The Role of Pressure and Temperature

Abstract

Many oil reservoirs encounter asphaltene precipitation as a major problem during natural production. In spite of numerous experimental studies, the effect of temperature on asphaltene precipitation during pressure depletion at reservoir conditions is still obscure in the literature. To study their asphaltene precipitation behavior at different temperatures, two Iranian light and heavy live oil samples were selected. First, different screening criteria were applied to evaluate asphaltene instability of the selected reservoirs using pressure, volume, and temperature data. Then, a high pressure, high temperature filtration (HPHT) setup was designed to investigate the asphaltene precipitation behavior of the crude samples throughout the pressure depletion process. The performed HPHT tests at different temperature levels provided valuable data and illuminated the role of temperature on precipitation. In the final stage, the obtained data were fed into a commercial simulator for modeling and predicting purposes of asphaltene precipitation at different conditions. The results of the instability analysis illustrated precipitation possibilities for both reservoirs which are in agreement with the oil field observations. It is observed from experimental results that by increasing the temperature, the amount of precipitated asphaltene in light oil will increase, although it decreases precipitation for the heavy crude. The role of temperature is shown to be more significant for the light crude and more illuminated at lower pressures for both crude oils. The results of thermodynamic modeling proved reliable applicability of the software for predicting asphaltene precipitation under pressure depletion conditions. This study attempts to reveal the complicated role of temperature changes on asphaltene precipitation behavior for different reservoir crudes during natural production.     

Development of an Artificial Neural Network Algorithm for the Prediction of Asphaltene Precipitation

Abstract

The precipitation and deposition of crude oil polar fractions such as asphaltenes in petroleum reservoirs considerably reduce rock permeability and oil recovery. Therefore, it is of great importance to determine how and how much the asphaltenes precipitate as a function of pressure, temperature, and liquid phase composition. The authors designed and applied an Artificial Neural Network (ANN) model to predict the amount of asphaltene precipitation at a given operating condition. Among this training, the back-propagation learning algorithm with different training methods was used. The most suitable algorithm with an appropriate number of neurons in the hidden layer, which provides the minimum error, was found to be the Levenberg-Marquardt (LM) algorithm. An extensive experimental data for the amount of asphaltene precipitation at various temperatures (293–343 K) was used to create the input and target data for generating the ANN model. The predicted results of asphaltene precipitation from the ANN model was also compared with the results of proposed scaling equations in the literature. The results revealed that scaling equations cannot predict the amount of asphaltene precipitation adequately. With an acceptable quantitative and qualitative agreement between experimental data and predicted amount of asphaltene precipitation for all ranges of dilution ratio, solvent molecular weight and temperature was obtained through using ANN model.     

Hydrotreating of Furrial Crude Oil Using NiMoS Supported on Alumina: Study of the Asphaltene and Their Fractions in Cyclohexane

Abstract

The Furrial crude oil originated in northern Monagas State. This shows problems such as the colloidal instability of the asphaltenes fraction present in them, causing its precipitation. This work is oriented to achieve an interpretation of the colloidal behavior of the asphaltenes through the study of the effect of the hydrotreating reactions (HDT) on the asphaltenes of the Furrial crude oil, using NiMoS/γ-Al₂O₃ as a catalyst. The results obtained after HDT reactions were analyzed to know the percentage of asphaltene and their fractions in cyclohexane, the measurement of flocculation thresholds and molecular weights by the VPO technique, and ¹³C NMR as well as the determination of the total sulfur content. Appreciable changes on the asphaltene of the Furrial crude oil and its fractions in cyclohexane after HDT, under conditions used, were observed. In general terms, the amount of asphaltene diminished and the percentage of distribution for insoluble fraction in cyclohexane (IFC) and for soluble fraction in cyclohexane (SFC) was affected causing an increase in the stability of the asphaltene. The asphaltene and IFC were observed to be a pronounced variation of the molecular weight average in number, in comparison with SFC. ¹³C NMR spectra indicate that the hydrotreated asphaltene shows structural change, and IFC presents a variation of the percentage of sulfur minor in comparison to SFC.     

Monitoring of asphaltene precipitation: Experimental and modeling study

Preparing relatively complete collections of experimental data on asphaltene precipitation in different reservoir conditions leads to considerable improvement in this area of science. In this work, asphaltene precipitation was studied upon two Iranian live oil samples, one a heavy oil and another light oil, under primary depletion as well as gas injections. Pressure depletion experiments were carried out at different temperatures to observe temperature effect besides pressure changes on asphaltene phase behavior. CO₂, dry and enriched gases were used as injecting agents to investigate the effect of different gases on asphaltene precipitation. Surprisingly, it was observed that raising temperature decreases the amount of precipitation in case of heavy oil while acting in favor of precipitation for light oil sample. In addition, Enriched gas resulted in more precipitation compared to dry one while CO₂ acted as hindering agent for light oil samples but increased the amount of precipitation in case of heavy oil. In the next part of this work, polydisperse thermodynamic model was developed by introducing an asphaltene molecular weight distribution function based on fractal aggregation. Modification that was introduced into polydisperse model not only solved the instability problem of Kawanaka model but also eliminates the need for resin concentration calculation. Flory–Huggins and Modified Flory–Huggins thermodynamic solubility models were applied to compare their predictions with proposed model.     

Intelligent Modeling of Asphaltene Precipitation in Live and Tank Crude Oil Systems

Abstract

The study of asphaltene precipitation properties has been motivated by their propensity to aggregate, flocculate, precipitate, and adsorb onto interfaces. The tendency of asphaltenes to precipitation has posed great challenges for the petroleum industry. The most important parameters in asphaltene precipitation modeling and prediction are the asphaltene and oil solvent solubility parameters, which are very sensitive to reservoir and operational conditions. The driving force of asphaltene flocculation is the difference between asphaltene and the oil solvent solubility parameter. Since the nature of asphaltene solubility is yet unknown and several unmodeled dynamics are hidden in the original systems, the existing prediction models may fail in prediction the asphaltene precipitation in crude oil systems. One of ways in modeling such systems is using intelligent techniques that need some information about the systems; so, based on some intelligent learning methods it can provide a suitable model. The authors introduce a new implementation of the artificial intelligent computing technology in petroleum engineering. They have proposed a new approach to prediction of the asphaltene precipitation in crude oil systems using fuzzy logic, neural networks, and genetic algorithms. Results of this research indicate that the proposed prediction model with recognizing the possible patterns between input and output variables can successfully predict and model asphaltene precipitation in tank and live crude oils with a good accuracy.     

Effect of pressure of the onset of asphaltene precipitation during gas flooding

In order to prevent and eliminate the asphaltene precipitation during gas flooding, the rules of the changes of the pressure under different conditions are systematically studied by the laser solid detection system, the light transmission method, and the P–T phase diagram when the asphaltene precipitation occurs. When the pressure is reducing to a certain value, the penetrating light intensity of the crude oil is markedly decreased, which shows that the pressure at this point is the pressure of the onset of asphaltene precipitation (AOPP). The AOPP value decreases with an increase in the temperature. During gas flooding, the AOPP value increases with an increase in the content of gas in the crude oil, and these two nearly do have a linear relationship. According to the P–T phase behaviors of the gas–crude oil system, with an increase in the content of gas in the crude oil, the asphaltene precipitation envelope curve (APE) is gradually moved up, which shows that the possibility of asphaltene precipitation is much higher. During oil production, for the oil reservoirs with rich asphaltene, the production pressure drop should be kept a small value to ensure that the flowing bottom-hole pressure is higher than AOPP and it is necessary to help complement producing energy timely by using water injection, gas injection, etc. Besides, according to the intersection of T–P curve and APE curve in the P–T phase diagram, the location where the asphaltene precipitation occurs in the wellbore can be roughly predicted. The experimental results can provide the theoretical foundation for taking measures to prevent and eliminate the asphaltene precipitation.     

A new model for predicting asphaltene precipitation of diluted crude oil by implementing LSSVM-CSA algorithm

Abstract

One of the severe problems in all the oil production stages from the pore walls of the reservoir rocks to the wellhead, transfer pipelines, and production units of a large portion of the world’s hydrocarbon reservoirs, is asphaltene precipitation and deposition from crude oil on solid surfaces. In this article, least squares support vector machine optimized by coupled simulated annealing is employed for estimation of the amount of asphaltene precipitated weight percent of diluted crude oil with paraffin based on titration tests data from a recently published article. The results indicated that there is an excellent correlation between predicted and experimental values with an average absolute relative deviation percent, mean square error, and a determination coefficient of 0.0727%, 0.0242, and 0.9972, respectively. The developed predicting model can be applied to estimate the amount of asphaltene precipitated when the crude oil is diluted with paraffin and to eschew experimental titration test that is tedious and time-consuming.     

Modeling of Asphaltene Phase Behavior with the SAFT Equation of State

Abstract

The SAFT equation of state was used to model asphaltene phase behavior in a model live oil and a recombined oil under reservoir conditions. The equation of state parameters for the asphaltenes were fit to precipitation data from oil titrations with n-alkanes at ambient conditions. The SAFT model was then used to predict the asphaltene stability boundaries in the live oils. A lumping scheme that divides the recombined oil into six pseudo-components based on composition, saturates–aromatics–resins–asphaltenes fractionation, and gas–oil-ratio data was introduced. Using this lumping scheme, SAFT predicted stock-tank oil and recombined oil densities that are in excellent agreement with experiment data. For both the model and the recombined oil systems, SAFT predicted asphaltene instability and bubble points agree well with experimental measurements.     

Dispersion of Asphaltene Precipitation in Egyptian Crude Oil Using Corrosion Inhibitors

Three corrosion inhibitors are examined in this work to control asphaltene precipitation in Egyptian heavy crude oil. Dodecylbenzenesulfonic acid (DBSA), 4-nonylphenyl-polyethylene glycol, and synthetic cationic gemini surfactant: N₂,N₃-didodacyl-N₂,N₂,N₃,N₃-tetramethylbutane diaminium bromide displayed highest capacity to inhibit asphaltene deposition. The H¹-NMR spectroscopy was used to confirm the chemical structure of the synthetic inhibitor. The efficiency of the studied additives as corrosion inhibitors are evaluated by weight loss method using the same crude oil. The effect of the mentioned corrosion inhibitors as asphaltene inhibitors is studied. The studied inhibitors are with dual nature for inhibition of both corrosion and asphaltene precipitation.     

Prediction of asphaltene precipitation from n-alkane diluted crude oil by using PC-SAFT equation of state

The precipitation tendency of heavy organics such as asphaltene has posed great challenges for petroleum industry, and thus study of asphaltene precipitation amount and formation conditions seems to be necessary. One of the most common approaches for prediction of asphaltene precipitation is using thermodynamic models. In this study a PC-SAFT equation of state (EOS) is used to predict asphaltene precipitation in two Iranian dead oil samples. Asphaltene content is obtained by filtration method of the oil samples diluted with specific concentrations of different normal alkanes. Also liquid-liquid equilibrium is used for characterization of oil sample into one heavy phase (asphaltene) and another light phase (saturates, aromatics, and resin). Calculations show that the developed model is highly sensitive to interaction parameter between oil fractions. Prediction results were improved due to using Chueh-Prausnitz equation. The results indicate good potential of PC-SAFT EOS in the prediction of asphaltene precipitation in crude oil samples diluted with different normal alkanes. The model error is <5% and the model precision is increased by reducing the number of normal alkane carbons.     

The Effect of Temperature and Pressure on the Reversibility of Asphaltene Precipitation

A lot of hindrances are seen in petroleum operation, production, and transportation as a results of factors that related to asphaltene precipitation. It has great importance to investigate the reversibility of asphaltene precipitation under changes of effective factors on thermodynamic conditions such as pressure, temperature, and composition. In the present work the reversibility of asphaltene precipitation under changes of pressure and temperature was investigated for two kind of Iranian heavy oil. The stability test shows these samples are located at unstable region in aspect of asphaltene precipitation. The experimental procedure includes two parts, (a) decreasing pressure from initial reservoir pressure to near saturation pressure and surveying asphaltene content hysteresis with redissolution process at reservoir temperature, and (b) investigation of precipitated asphaltene in both precipitation and redissolution processes at different temperature and reservoir pressure. At each step IP143 standard test was used to measure precipitated asphaltene. It was concluded that above bubble point pressure, asphaltene precipitation is nearly reversible with respect to pressure for both samples and it was partially reversible with respect to the temperature for sample A, and accordingly pressurizing is acceptable method for solving the problem in both heavy asphaltenic crude oil samples and increasing temperature is acceptable method for solving asphaltene problem in crude oil sample A. Also density measurement of flashed oil confirmed that there is a little hysteresis in asphaltene content during redissolution and precipitation processes.     

Investigation of Asphaltene Precipitation Process for Kuwaiti Reservoir

Abstract

As part of an Enhanced Oil Recovery (EOR) research program, Asphalting precipitation processes were investigated for a Kuwaiti dead oil sample using different hydrocarbons and carbon dioxide as precipitants at the ambient and high pressure of 3000 psig conditions. The hydrocarbons used as precipitants were ethane (C2), propane (C3), butane (C4), normal pentane (n-C5), normal hexane (n-C6), and normal heptane (n-C7). The equipment used for this investigation was a mercury-free, variable volume, fully visual JEFRI-DBR PVT system with laser light scattering. The minimum critical value of precipitants concentration for the oil sample has been identified at the ambient and high-pressure conditions for each precipitant. Our investigation has revealed that for this oil sample the most powerful asphaltene precipitant were CO₂ followed by C2, C3, C4, n-C5, n-C6, and n-C7. Moreover, the effect of pressure and temperature on the asphaltene precipitation has been investigated experimentally for CO₂, n-C5, n-C6, and n-C7. The precipitation and redissolution of asphaltene upon the addition and removal of CO₂ and light alkanes (C2–C4), at 3000 psig and ambient temperatures, have shown evidence of reversibility of asphaltene precipitation. A comprehensive fluid characterization analysis for the oil sample has been performed including, physical properties of crude oil, compositional, molecular weight (Mw), and SARA analyses. Advanced analytical techniques such as 1H and 13C NMR and IR spectrometers have been utilized to investigate the molecular structure of the asphaltene for this sample. It was concluded that the asphaltene molecules for this oil contain 120 total aromatic carbons with 42 aromatic rings, 114 naphthenic rings, and 5–7 sets of condensed aromatic rings.     

The Vapor Extraction Process: Review

Abstract

The high viscosity of Canadian crude oil is a serious challenge for the recovery efficiency of this resource by conventional methods. Since 1991, the vapor extraction process (VAPEX) has emerged as a promising technology that has gained considerable attention within the oil industry. This article presents a current review of this process and its variations, as well as describing important factors affecting the process such as solvent requirements, mass transfer, asphaltene precipitation, oil rate, and wettability. Recent research has shown that VAPEX is an efficient alternative for the recovery of heavy oil.     

准噶尔盆地南缘井筒堵塞物中沥青质分子组成研究

采用傅里叶变换离子回旋共振质谱分析技术,分析了准噶尔盆地南缘高探1井原油及井筒堵塞物抽提物中沥青质化学组成及差异,探讨了沥青质的组成及结构与沥青质沉积关系,对于沥青质聚集理论研究具有重要意义.研究结果显示,高探1井原油及井筒堵塞物抽提物中沥青质分子主要为N1、N1 O1、O1、O2、O3和O4类化合物,但堵塞物抽提物中...     

Influence of pressure and CO2 content on the asphaltene precipitation and oil recovery during CO2 flooding

During CO₂ flooding, the crude oil is treated with CO₂, and meanwhile it is displaced by CO₂. Based on the two processes, the influence of pressure and CO₂ content on the asphaltene precipitation and oil recovery efficiency are systematically investigated by indoor simulation experiment. With the increase of the pressure or CO₂ content during CO₂ treatment, the amount of asphaltene precipitation can be increased to a certain value. Correspondingly, the degrees of the changes of oil-water interface, the compositions of crude oil, and reservoir permeability are positively correlated with the amount of asphaltene precipitation. However, during the process, the oil recovery has an optimal value due to the combined action of asphaltene precipitation and the improvement of flow performance of the crude oil. These conclusions can provide a basis for high efficiency development of low permeability oil reservoirs by CO₂ flooding.