A CORRELATION FOR VISCOSITY AND SOLVENT MASS FRACTION OF BITUMEN-DILUENT MIXTURES

A simple equation is presented for predicting the kinematic viscosity of bitumens and heavy oils mixed with diluents. The correlation has been shown to provide accurate viscosity estimates of these mixtures for a wide range of data and requires only the knowledge of the pure bitumen and pure solvent viscosities at any given temperature.

The correlation makes use of a viscosity reduction parameter which reduces error significantly when compared to similar equations presented by Chirinos et al. (1983), and Cragoe (1933). For a total of 89 data points, excluding the pure bitumens and diluents values, the correlation yielded an overall average absolute deviation of about 14 percent. The same equation was applied to predict the mass fraction of diluent required to reduce bitumen viscosity to pumping viscosity. Predicted values matched experimental values very well, with an overall average absolute deviation of about 6 percent.     

Application of fuzzy c-means algorithm as a novel method to predict density of mixtures of Athabasca bitumen and heavy n-alkane

The significant number of oil reservoir are bitumen and heavy oil. One of the approaches to enhance oil recovery of these types of reservoir is dilution of reservoir oil by injection of a solvent such as tetradecane into the reservoirs to modify viscosity and density of reservoir fluids. In this investigation, an effective and robust estimating algorithm based on fuzzy c-means (FCM) algorithm was developed to predict density of mixtures of Athabasca bitumen and heavy n-alkane as function of temperature, pressure and weight percent of the solvent. The model outputs were compared to experimental data from literature in different conditions. The coefficients of determination for training and testing datasets are 0.9989 and 0.9988. The comparisons showed that the proposed model can be an applicable tool for predicting density of mixtures of bitumen and heavy n-alkane.     

Modeling of viscosity for mixtures of Athabasca bitumen and heavy n-alkane with LSSVM algorithm

The resources of heavy oil and bitumen are more than those of conventional light crude oil in the world. Diluting the bitumen with liquid solvent can decrease viscosity and increase the empty space between molecules. Tetradecane is a candidate as liquid solvent to dilute the bitumen. Owning to the sensitivity of enhanced oil recovery process, the accurate approximation for the viscosity of aforementioned mixture is important to decrease uncertainty. The aim of this study was to develop an effective relation between the viscosity of Athabasca bitumen and heavy n-alkane mixtures based on temperature, pressure, and weight percentage of n-tetradecane using the least square support vector machine. This computational model was compared with the previous developed correlation and its accuracy was confirmed. The value of R² and MSE obtained 1.00 and 1.02 for this model, respectively. This developed predictive tool can be applied as an accurate estimation for any mixture of heavy oil with liquid solvent.     

Liquid-phase Mutual Diffusion Coefficients for Heavy Oil + Light Hydrocarbon Mixtures

Liquid-phase mutual diffusion coefficients are a key parameter in reservoir simulation models related to both primary production and envisioned secondary recovery processes for heavy oil and bitumen. The measurement of liquid-phase mutual diffusion coefficients in bitumen and heavy oil + light hydrocarbon or gas mixtures present numerous experimental and data analysis challenges due to the viscosity and opacity of the mixtures, the variability of density, viscosity and mutual diffusion coefficient with composition, and the multi-phase nature of these mixtures. Data analysis challenges are particularly acute. For example, recently reported mutual diffusion coefficient values for liquid mixtures of bitumen + carbon dioxide vary over three orders of magnitude when different analysis methods are applied to the same experimental data. In this contribution, we illustrate the importance of measuring composition profiles within liquids as a function of time, as a basis for mutual diffusion coefficient computation, and for allowing explicitly for the variation of diffusion coefficient and liquid density with composition in the analysis of composition profile data. Such inclusions eliminate apparent temporal variations of mutual diffusion coefficients and yield values consistent with relevant theories and exogenous data sets. Liquid-phase mutual diffusion coefficients computed for the mixtures Athabasca Bitumen + pentane and Cold Lake Bitumen + heptane exemplify the experimental and data analysis approaches.     

Liquid-phase Mutual Diffusion Coefficients for Heavy Oil + Light Hydrocarbon Mixtures

Abstract:

Liquid-phase mutual diffusion coefficients are a key parameter in reservoir simulation models related to both primary production and envisioned secondary recovery processes for heavy oil and bitumen. The measurement of liquid-phase mutual diffusion coefficients in bitumen and heavy oil + light hydrocarbon or gas mixtures present numerous experimental and data analysis challenges due to the viscosity and opacity of the mixtures, the variability of density, viscosity and mutual diffusion coefficient with composition, and the multi-phase nature of these mixtures. Data analysis challenges are particularly acute. For example, recently reported mutual diffusion coefficient values for liquid mixtures of bitumen + carbon dioxide vary over three orders of magnitude when different analysis methods are applied to the same experimental data. In this contribution, we illustrate the importance of measuring composition profiles within liquids as a function of time, as a basis for mutual diffusion coefficient computation, and for allowing explicitly for the variation of diffusion coefficient and liquid density with composition in the analysis of composition profile data. Such inclusions eliminate apparent temporal variations of mutual diffusion coefficients and yield values consistent with relevant theories and exogenous data sets. Liquid-phase mutual diffusion coefficients computed for the mixtures Athabasca Bitumen + pentane and Cold Lake Bitumen + heptane exemplify the experimental and data analysis approaches.     

Applying FCM-ANFIS algorithm as a novel computational method for prediction of viscosity of bitumen and heavy alkane mixture

Recently the studies expressed that the noticeable number of oil reservoirs in all over the world are heavy oil and bitumen reservoirs. So the importance of enhancement of oil recovery (EOR) processes for heavy oil and bitumen reservoirs is highlighted. The Dilution of the reservoir fluid by solvents such as tetradecane is one of well-known methods for these types of reservoirs which effects oil recovery by decreasing viscosity. In the present study, Fuzzy c-means (FCM) algorithm was coupled with Adaptive neuro-fuzzy inference system (ANFIS) to predict viscosity of bitumen and tetradecane in terms of temperature, pressure and weight percent of tetradecane. The coefficients of determination for training and testing steps were calculated such as 0.9914 and 0.9613. The comparison of results and experimental data expressed that FCM-ANFIS algorithm has great potential for estimation of viscosity of bitumen and tetradecane.     

VISCOSITY OF BITUMEN-CRUMB RUBBER BLEND (NEW PAVING MATERIAL)

The feasibility of blending scrap tire rubber with Asphalt Ridge and Circle Cliffs (Utah, USA) tar sand bitumens was studied. Viscosity of the blended mixtures was analyzed as a function of composition, and coprocessing variables including processing temperature and time. Coprocessing of tar sand bitumens with crumb rubber at elevated temperatures has been shown to increase the viscosity of the bitumens with the exception of the bitumen-rubber sample prepared at 380°C. Optimum viscosity behavior was exhibited for an oil-extended bitumen blended with crumb rubber at 200°C for 0.5 hours. The viscosity of the bitumen-rubber blend prepared under these conditions met ASTM specifications of a viscosity-graded AC-30 asphalt binder. Viscosity increase was most noticeable at low temperature, providing the benefit of high viscosity at pavement temperatures experienced during summer months without concession of processability at pavement construction temperatures. A difference in viscosity was observed between bitumen modified with whole-tire crumb and tread-rubber crumb, due to the compositional differences that exist between the two materials.     

VISCOSITY OF BITUMEN-CRUMB RUBBER BLEND (NEW PAVING MATERIAL)

ABSTRACT

The feasibility of blending scrap tire rubber with Asphalt Ridge and Circle Cliffs (Utah, USA) tar sand bitumens was studied. Viscosity of the blended mixtures was analyzed as a function of composition, and coprocessing variables including processing temperature and time. Coprocessing of tar sand bitumens with crumb rubber at elevated temperatures has been shown to increase the viscosity of the bitumens with the exception of the bitumen-rubber sample prepared at 380°C. Optimum viscosity behavior was exhibited for an oil-extended bitumen blended with crumb rubber at 200°C for 0.5 hours. The viscosity of the bitumen-rubber blend prepared under these conditions met ASTM specifications of a viscosity-graded AC-30 asphalt binder. Viscosity increase was most noticeable at low temperature, providing the benefit of high viscosity at pavement temperatures experienced during summer months without concession of processability at pavement construction temperatures. A difference in viscosity was observed between bitumen modified with whole-tire crumb and tread-rubber crumb, due to the compositional differences that exist between the two materials.     

PSO-ANFIS modeling of viscosity for mixtures of Athabasca bitumen and a high-boiling n-alkane

The bitumen and heavy oil reservoirs are more in number than light crude oil reservoirs in the world. To increase the empty space between molecules and decrease viscosity, the bitumen was diluted with a liquid solvent such as tetradecane. Due to the sensitivity of enhanced oil recovery process, the accurate approximation for the viscosity of mentioned mixture is important. The purpose of this study was to develop an effective relation between the viscosity of Athabasca bitumen and heavy n-alkane mixtures based on pressure, temperature, and the weight percentage of n-tetradecane using the adaptive neuro-fuzzy inference system method. For this model, the value of MRE and R² was obtained as 0.34% and 1.00, respectively; so this model can be applied as an accurate approximation for any mixture of heavy oil with a liquid solvent.     

Prediction of density and viscosity of bitumen

Abstract

It is well known fact that temperature and pressure significantly affects density and viscosity of bitumen. The present work utilizes Gene Expression Programming (GEP) approach to develop models to predict density and viscosity of bitumen. To evaluate the accuracy of proposed GEP based models, results reported by various researchers were utilized. This includes test results regarding Athabasca, Cold Lake and Gas free bitumen. The developed GEP based models were compared with the conventional empirical regression equations. The statistical analysis indicates that GEP based models work better than other existing models for density and viscosity of bitumen.     

A PSO-ANFIS framework for prediction of density of bitumen diluted with solvents

One of the important properties in petroleum engineering calculations in heavy oil reservoirs is the density of bitumen diluted with solvents. It is required in newly developed solvent based enhanced oil recovery methods. Hence, developing accurate models for prediction of this parameter is essential. To tackle this issue, this study presents an accurate model based on adaptive neuro-fuzzy inference system trained by particle swarm optimization (PSO-ANFIS) for estimation of density of bitumen diluted with solvents and hydrocarbon mixtures using experimental data from literature. The accuracy and reliability of results were evaluated by utilizing various statistical and graphical approaches and comparing the predictions of the developed model with literature models. The analysis showed that the PSO-ANFIS model is capable to predict the experimental data with acceptable error and high accuracy. The predictions of the PSO-ANFIS model were also better than the literature models.     

不同粘度等级的再生剂对老化沥青再生性能的影响

研究了不同粘度等级的再生剂对老化沥青再生性能的影响。结果表明,不同粘度等级的再生剂对老化沥青的再生效果有明显差异。粘度低的再生剂对老化沥青软化点的降低、延度的提高、针入度的增大和粘度的减小更为明显。然而,对于轻度老化沥青,低粘度再生剂使其软化点和粘度降低幅度较大,对再生沥青的高温性能影响明显,因此轻度老化沥青宜选用粘度较高的再生剂,而重度老化沥青应选用低粘度的再生剂。     

Application of Grid partitioning based Fuzzy inference system and ANFIS as novel approach for modeling of Athabasca bitumen and tetradecane mixture viscosity

The heavy oil and bitumen reservoirs have effective role on supplying energy due to their availability in the world. The bitumen has extremely high viscosity so this type of reservoirs has numerous problems in production and trans- portation.one of the common approach for reduction of viscosity is injection of solvents such as tetradecane. In the present study the Grid partitioning based Fuzzy inference system was coupled with ANFIS to propose a novel algorithm for prediction of bitumen and tetradecane mixture viscosity in terms of pressure, temperature and weight fraction of the tetradecane. In the present study, the coefficients of determination for training and testing phases are determined as 0.9819 and 0.9525 respectively and the models are visualized and compared with experimental data in literature. According to the results the predicting method has acceptable accuracy for prediction of bitumen and tetradecane mixture viscosity.     

Viscosity estimation of mixed oil using RBF-ANN approach

Diluting the bitumen and heavy oil with a liquid solvent such as tetradecane is one way to decrease the viscosity. The accurate estimation for the viscosity of the aforesaid mixture is serious due to the sensitivity of enhanced oil recovery method. The main aim of this study was to propose an impressive relation between the viscosity of heavy n-alkane and Athabasca bitumen mixtures based on pressure, temperature, and the weight percentage of n-tetradecane using radial basis function artificial neural network (RBF-ANN). Also, this model has been compared with previous equations and its major accuracy was evidenced to estimate the viscosity. The amounts of mean relative error (MRE %) and R-squared received 0.32 and 1.00, respectively. The endeavors confirmed amazing forecasting skill of RBF-ANN for the approximation of the viscosity as a function of temperature, pressure, and the weight percentage of n-tetradecane.     

VISCOSITY AND SOLUBILITY OF MIXTURES OF BITUMEN AND SOLVENT

The solubilities of three bitumen samples (Suncor, Syncrude and Lloydminster) in five solvents were examined and prediction on the various bitumen-solvent mixture viscosities were made with Cragoe equation. By calculating the Cragoe constant 'a' for each mixture and using the average value in the Cragoe equation the prediction accuracy of the equation was improved by over 60%. Bitumen-naphtha mixtures showed the best viscosity prediction characteristics.

The solubility of the asphaltenes in the bitumen was highest in toluene among the five solvents However, naphtha, showed a moderate solvating power, which negligibly varied over the range of composition studied. Therefore naphtha, a solvent derived from bitumen was recommended as the most appropriate solvent for reducing the viscosity bitumen.     

Estimation of bitumen emulsion dispersion using a light scattering method

Petroleum bitumen in the emulsified state is widely used as a binder in road and civil construction. Along with traditional quality parameters of bitumen emulsions the particle size is considered to be very important characteristic. The particle size of the dispersed phase affects the setting rate and viscosity of bitumen emulsions. The complete data on the particles size distribution can be obtained using such technical methods as light scattering and microscopy. In the study bitumen emulsions with three types of surfactants (cationic, nonionic, zwitterionic) have been prepared and their viscosity and decay index have been determined. The emulsions also have been studied with a microscope, as well as by the method of dynamic light scattering. The dynamics of particle size changes of the bitumen emulsions has been compared with the dynamics of the change in the basic parameters of the emulsions, such as viscosity and decay index, and the correlation between them has been found. Thus, using a modern laser and optical equipment, it is possible to estimate the quality of emulsions and, if necessary, to correct their composition.     

VISCOSITY AND SOLUBILITY OF MIXTURES OF BITUMEN AND SOLVENT

Abstract

The solubilities of three bitumen samples (Suncor, Syncrude and Lloydminster) in five solvents were examined and prediction on the various bitumen-solvent mixture viscosities were made with Cragoe equation. By calculating the Cragoe constant ‘a’ for each mixture and using the average value in the Cragoe equation the prediction accuracy of the equation was improved by over 60%. Bitumen-naphtha mixtures showed the best viscosity prediction characteristics.

The solubility of the asphaltenes in the bitumen was highest in toluene among the five solvents However, naphtha, showed a moderate solvating power, which negligibly varied over the range of composition studied. Therefore naphtha, a solvent derived from bitumen was recommended as the most appropriate solvent for reducing the viscosity bitumen.     

The rheological behavior of bitumen and moisture susceptibility modified with SBS and nanoclay

The effect of styrene–butadiene–styrene (SBS) and nanoclay additive on performance of pure bitumen and stone matrix asphalt (SMA) mixture was investigated. Different samples with various percentages of nanoclay (2%, 3%, 4%, and 5%) and SBS (0% and 5%) by weight of bitumen were prepared, and the rheological and chemical behavior of bitumen (rotational viscosity, dynamic shear rheometer, SEM, and FTIR), the indirect tensile strength and moisture susceptibility of different mixtures were evaluated. Based on the results, using nanoclay and SBS polymer can improve the rheological behavior of base binder and the resistance of SMA mixtures against moisture damage.     

The Comparison of Bitumens from Oil Sands with Different Recovery Profiles

Abstract

It has been proposed that, regardless of origin, the recovery of bitumen from oil sands is related to its viscosity. Asphaltene and resin contents are known to affect the viscosity of bitumen. In this article we compare the composition of solvent-extracted bitumens from several Athabasca oil sands with very different recovery profiles. After careful removal of any associated mineral matter by ultra-centrifugation, each bitumen sample was separated into saturate, aromatic, resin, and asphaltene (SARA) fractions by an enhanced SARA technique. The individual components were then characterized by several complementary analytical techniques, including carbon, nitrogen, nitrogen, sulfur, size exclusion chromatography molecular weight (MW_n) plus proton and ¹³C nuclear magnetic resonance spectroscopy. Based on this comparison, we see no correlation between the recovery of bitumen and its composition.     

欧盟标准硬质沥青的研制与生产

以环烷基稠油为原料,采用常减压蒸馏深拔工艺开发符合欧盟标准的硬质沥青产品,研制的硬质沥青软化点高、黏度高、针入度比大、闪点高,使用性能优良,试生产的硬质沥青产品满足欧盟EN13924道路沥青质量要求。