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.     

Developing a Scaling Equation as a Function of Pressure and Temperature to Determine the Amount of Asphaltene Precipitation

A simple and applicable scaling equation as a function of pressure, temperature, molecular weight, dilution ratio (solvent), and weight percent of precipitated asphaltene has been developed. This equation can be used to determine the weight percent of precipitated asphaltene in the presence of difference precipitants (solvents) and the amount of solvent at onset point. Since increasing the pressure of crude oil decreases the amount of asphaltene precipitation, the effect of reservoir pressure has been taken into account in developing this equation. The results obtained by using this equation are substantially different and more accurate from other developed scaling equations for asphaltene precipitation. By considering the effect of reservoir pressure in developing the scaling equation and application of a genetic algorithm, the unknown parameters of the scaling equation are simultaneously and without any reservation obtained. The most important application of this unique equation is in the determination of critical point of asphaltene precipitation, known as onset point, and asphaltene precipitation in gas injection operations for enhanced oil recovery. The results predicted using the scaling equations are compared with the authors' experimental and literature precipitation data and it is shown that they are in good agreement with our experimental data. The scaling equation can be used in the design of gas-injected reservoir to prevent precipitation of the asphaltene aggregates in the reservoir.     

Modeling Asphaltene Precipitation Under Gas Injection and Pressure Depletion Conditions

Asphaltene precipitation is a major problem during primary oil production and enhanced oil recovery in the petroleum industry. In this work, a series of experiments was carried to determine the asphaltene precipitation of bottom hole live oil during gas injection and pressure depletion condition with Iranian bottom hole live oil sample, which is close to reservoir conditions using high pressure-high temperature equilibrium cell. In the majority of previous works, the mixture of recombined oil (mixture dead oil and associated gas) was used which is far from reservoir conditions. The used pressure ranges in this work covers wide ranges from 3 to 35 MPa for natural depletion processes and 24–45 MPa for gas injection processes. Also, a new approach based on the artificial neural network (ANN) method has been developed to account the asphaltene precipitation under pressure depletion/gas injection conditions and the proposed model was verified using experimental data reported in the literature and in this work. A three-layer feed-forward ANN by using the Levenberg-Marquardt back-propagation optimization algorithm for network training has been used in proposed artificial neural network model. The maximum mean square error of 0.001191 has been found. In order to compare the performance of the proposed model based on artificial neural network method, the asphaltene precipitation experimental data under pressure depletion/gas injection conditions were correlated using Solid and Flory-Huggins models. The results show that the proposed model based on artificial neural network method predicts more accurately the asphaltene precipitation experimental data in comparison to other models with deviation of less than 5%. Also, the number of parameters required for the ANN model is less than the studied thermodynamic models. It should be noted that the Flory and solid models can correlate accurately the asphaltene precipitation during methane injection in comparison with CO₂ injection.     

注气对固溶物沉淀影响的研究与应用

注气采油是提高原油采收率的主要方式之一,在此过程中准确描述含有沥青质等高分子有机固相物质的油气体系相平衡十分必要。为此,将沉淀的沥青质视为固相,假设标准状态下必须有沥青质沉淀,将标准状态压力和温度引入沥青质固相逸度计算,并同时考虑了标准状态压力和温度对沥青质固相逸度的影响,建立了能模拟沥青质沉淀的气、液、固三相相平衡热力学模型。据该模型计算的结果表明:①能通过比较液相沥青质逸度和固相沥青质逸度大小来判断固相沥青质沉淀的出现。②当注入某油的气体为烃类混合气体时,烃类混合气体的添加使得含沥青质原油的组分发生变化;温度相同时,注气浓度越高,沉淀的压力越大;浓度相同时,温度越低,沉淀的压力越大;当沉淀量一定时,随着注气浓度增加,油品的饱和压力随之增大;相同注气浓度下,当压力高于饱和压力时,随着压力增大,沉淀量减少。③在温度不变的情况下,注入某油的气体为CO2时,其沥青质沉淀量是注CO2浓度的函数且随着CO2浓度的增加,固相(沥青质)的沉淀量不断增大。④在注气驱油过程中,气体的注入极易引发含沥青质原油中沥青质等重质有机物的沉积。     

Modeling of precipitated asphaltene using the ANFIS approach

Asphaltene precipitation is introduced as a seriously problematic issue in the petroleum reservoirs that causes filling porosity of rocks and reduction of oil production. Hence, estimating the amount of precipitated asphaltene has huge importance in preventing the deposition of asphaltene. The present study was done to estimate the precipitated asphaltene as a function of temperature, dilution ratio, and molecular weight of different n-alkanes using adaptive neuro-fuzzy inference system (ANFIS). Moreover, another new scaling model was also developed to compare with the ANFIS model. In addition, these two developed models have been compared with previously developed correlations. The obtained values of R² for the ANFIS and scaling models were 0.9912 and 0.9862, respectively. These tools are simple to use and can be used as an accurate approximation of the precipitated asphaltene as a function of temperature, dilution ratio, and molecular weight of different n-alkanes.     

An Investigation of Asphaltene Precipitation During Natural Production and the CO2 Injection Process

Some of Iranian oil reservoirs suffer from operational problems due to asphaltene precipitation during natural depletion, so widely investigation on asphaltene precipitation is necessary for these reservoirs. In this study, a reservoir that is candidate for CO₂ gas injection process is selected to investigate asphaltene precipitation with and without CO₂ injection. In this case, asphaltene precipitation is monitored at various pressures and reservoir temperature. Then, a series of experiments are carried out to evaluate the amount of precipitated asphaltene by injection different molar concentrations (25%, 50%, and 75%) of CO₂. The results show that during primary depletion the amount of precipitated asphaltene increases with pressure reduction until bubble point pressure. Below the bubble point the process is reversed (i.e., the amount of precipitated asphaltene at bubble point pressure is maximum). The behavior of asphaltene precipitation versus pressure for different concentrations of CO₂ is similar to primary depletion. Asphaltene precipitation increases with CO₂ concentration at each pressure step. In the modeling part, solid model and Peng-Robinson equation of state are employed which show a good match with experimental results.     

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.     

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.     

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.     

Predicting asphaltene precipitation during titration of diluted crude oil with paraffin using artificial neural network (ANN)

Abstract

Asphaltene precipitation from crude oil in underground reservoirs and on ground facilities is one of the major problems in a large portion of oil production units around the world. Many scaling equations and intelligent predictive models using the artificial neural network (ANN) are proposed in the literature but none of them can be applied when crude oil is diluted with any types of paraffin. In this study, feed forward artificial neural network is used for prediction of the amount of asphaltene precipitated weight percent of diluted crude oil with paraffin based on titration tests data from published literature. Trial and error method is utilized to optimize the artificial neural network topology in order to enhance its strength of generalization. The results showed that there is good agreement between experimental and predicted values. This predictive model can be applied to estimate the amount of asphaltene precipitated weight percent when the crude oil is diluted with paraffin and to avoid experimental measurement that is time-consuming and requires expensive experimental apparatus as well as complicated interpretation procedure.     

A comprehensive experimental evaluation of asphaltene dispersants for injection under reservoir conditions

As the efficiency of dispersants with different origins is questionable for each typical oil sample, the present study provides a reproducible and reliable method for screening asphaltene dispersants for a typical asphaltenic crude oil. Four different asphaltene dispersants (polyisobutylene succinimide, polyisobutylene succinic ester, nonylphenol-formaldehyde resin modified by polyamines, and rapeseed oil amide) were prepared and their performance on two oils from an Iranian field under laboratory and reservoir conditions was studied. A thorough analysis including ash content and SARA tests was performed on the solid asphaltene particles to characterize the nature of deposits. Then a highly efficient carrier fluid, which is crucial when injecting dispersant into the wells, was selected from a variety of chemicals by comparing their solubility. In the next step, using an optical microscope, a viscometer, and a Turbiscan, the screening of dispersants under laboratory conditions was done on a mixture of dead oil and dispersant to evaluate the onset of asphaltene precipitation and its stability when titrating by a precipitant. Finally, two different mixtures of the efficient dispersants, live oil, and carrier fluid were used with the solid detection system (SDS) and the filtration method to examine their effects on the onset pressure of asphaltene precipitation and the asphaltene content of the crude oil under reservoir conditions. The results show that the combination of experimental methods used in this work could be consistently applied to screening asphaltene dispersants. Among the four different dispersants applied here, the dispersant based on nonylphenol-formaldehyde resin modified by polyamines showed the best performance on the available live oils. This chemical modified the onset pressure of asphaltene precipitation of light oil from 4300 psi to about 3600 psi and decreased the precipitated asphaltene of heavy oil by about 30 %.     

Experimental and Modelling Investigations of Asphaltene Precipitation During Pressure Depletion and Gas Injection Operations

Asphaltene precipitation problems manifest themselves in different stages of oil reservoirs production. Experimental and modeling investigations are, therefore, employed as promising tools to assist in predictions of asphaltene precipitation problems and selection of proper production facilities. This study concerns experimental and modeling investigations of asphaltene precipitation during natural production and gas injection operations for a heavy Iranian crude oil at reservoir conditions. First, with design and performance of high pressure–high temperature experiments, asphaltene precipitation behavior is comprehensively investigated; the effects of pressure and temperature are fully studied during pressure depletion tests and the role of injection gas composition on precipitation is described in gas injection experiments. In the next stage, the obtained experimental results are fed into a commercial simulator to develop the asphaltene precipitation model. The results for the pressure depletion experiments indicate that the maximum amount of asphaltene precipitation takes place at fluid bubble point pressure. Increase in the temperature, as seen, causes to reduce the amount of precipitation for the entire range of pressures. For gas injection experiments, the onset of precipitation for CO₂, associated, and N₂ gases takes place at around 0.20, 0.28, and 0.50 gas to mixture mole ratios, respectively. Carbon dioxide shows the highest asphaltene precipitation values and nitrogen has the lowest amounts for the whole range of gas mole fractions. Finally, the results for modeling indicate successful asphaltene precipitation predictions for both pressure depletion and gas injection processes.     

Prediction of asphaltene precipitation using non-isothermal compositional network model

In this paper a comprehensive flow model which incorporates compositional and non-isothermal effects is proposed to investigate asphaltene precipitation onset conditions in advanced well completions. The focus is on precipitation induced by pressure and temperature conditions, particularly in flow restrictions used in wells to delay unwanted break through of water/gas. A network model is used with a non-isothermal black oil fluid model to predict the distribution of pressure, temperature, flow rate and phase fractions in all components of the well completion. The network geometry consists of a production tubing (or liner) and an annulus between the reservoir and the tubing. This geometry will allow for flow between the annulus and the tubing through inflow control devices which are commonly used for zonal control. An asphaltene precipitation envelope is used to identify locations in the well completion at risk. Subsequently, a fully compositional and non-isothermal model is invoked at these locations. This detailed model uses a Finite Difference representation of conservation of mass, energy and momentum. Furthermore, it uses an isenthalpic pseudo-three-phase equilibrium model to predict if asphaltene precipitation actually will occur inside the restriction. A case study is presented in which the proposed model was successfully used to predict physical flow parameters and asphaltene onset conditions. It was found that asphaltene precipitation may occur in flow restriction due to large pressure drop. Furthermore, it was found that the use of isothermal modeling to predict asphaltene precipitation may lead to underestimation of the precipitation. It is concluded that the details of the well completion must be represented in the flow model since pressure and temperature may vary non-monotonically from toe to heel in advanced well completions.     

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.     

Prediction of Asphaltene Precipitation in Live and Tank Crude Oil Using Gaussian Process Regression

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. Since the nature of asphaltene solubility is yet unknown and several unmodeled dynamics are hidden in the original systems, the existing models may fail in prediction the asphaltene precipitation in crude oil systems. The authors developed some Gaussian process regression models to predict asphaltene precipitation in crude oil systems based on different subsets of properties and components of crude oil. Using feature selection techniques they found some subsets of properties of crude oil that are more predictive of asphaltene precipitation. Then they developed prediction models based on selected feature sets. Results of this research indicate that the proposed predictive models can successfully predict and model asphaltene precipitation in tank and live crude oils with good accuracy.     

The Thermodynamic Modeling of Asphaltene Precipitation Equilibrium during the Natural Production of Crude Oil: The Role of Pressure and Temperature

Asphaltene precipitation is a sophisticated issue in the upstream oil industry, worldwide, and has detrimental effect on a verity of production processes; it damages the properties of the reservoir and causes an unfavorable and significant decrease in oil production. In spite of numerous studies to predict asphaltene behavior, the effect of temperature on asphaltene precipitation during pressure depletion at reservoir conditions is still obscure in the literature. In this study the PVT data as well as experimental data of asphaltene precipitation at reservoir conditions of an Iranian light oil samples is used, and the asphaltene precipitation and deposition envelops (APE and ADE) of the oil are developed using solid thermodynamic modeling.     

高压注烃类气体过程中沥青质初始沉淀压力试验研究

为预防注烃类气体提高采收率过程中产生沥青质沉淀,对沥青质初始沉淀压力进行了试验研究.在分析注烃类气体过程中沥青质沉淀机理的基础上,通过自主研发的固相沉积激光探测装置,采用透光强度法测定了原油样品在不同温度下高压注气过程中沥青质的初始沉淀压力,并确定了沥青质沉淀的深度.试验得出,原油沥青质初始沉淀压力随温度升高而下降,测得44,80和123 ℃温度下原油的沥青质初始沉淀压力分别为44.1,39.7和35.2 MPa;每注入物质的量分数为1%的烃类气体,试验油样的沥青质初始沉淀压力升高0.5~0.6 MPa;井筒温度压力曲线与沥青质沉淀相包络线相结合预测井筒中出现沥青质沉淀的深度在1 800 m左右,与现场情况吻合较好.研究表明,原油中沥青质初始沉淀压力与注气量之间呈线性关系,可为现场注气驱油预防和清除沥青质沉积物提供理论依据.      

Dynamic Pore Scale Modeling of Asphaltene Deposition in Porous Media

Asphaltene deposition in porous medium is one of important factors in reducing the productivity of oil reservoirs. Reduction of permeability is the main factor, which is also due to reduced pores size or complete closure of them. The authors simulate phase one flow of oil in porous medium using a dynamic pore scale network model. Also asphaltene deposition process is considered based on a scaling equation. Because the greatest amount of precipitation occurs at bubble point pressure condition, we considered boundary conditions of the model in this pressure. The hypothetical model is only a very small element of a real reservoir rock therefore we assumed constant temperature in this process, consequently the main reason of asphaltene precipitation is pressure changes in the pores. Permeability reduction simulated was based on these steps: pore and throat pressure changes were due to fluid flow through the network and asphaltene deposited according to scaling equation. Applying a material balance for each pore/throat gives the volume reduction of pores/throats according to the deposited asphaltene. Due to this change in pores size permeability and porosity of the model is calculated. Repeating these steps over the time gives effect of asphaltene deposition on the primary properties of porous medium.     

气液固三相相平衡热力学模型与计算方法

原油中含有大量的高分子有机固相物质，因此，要准确地描述油气体系相平衡，必须对气液固三相相平衡进行研究，在对高分子有机烃类沥青沉降机理有了一定的认识的基础上，提出了大的交互作用系数，可以描述沥青与原油中轻质不相容性的程度。根据对油气烃类混合物体系的一般性认识与提出的沥青组分特征化方法，导出了与之相应的有其自身特殊性的气液沥青三相相平衡物料平衡方程组，用考虑沥青沉降三相闪蒸数值算法，对沥青沉降进行有效的理化模拟计算，此外，结合实例分析，给出了沥青质参考逸度的计算，饱和压力和沉降量的拟合方法。     

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.