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.     

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.     

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.     

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.     

The Effective Diffusion/Dispersion Coefficient in Vapor Extraction of Heavy Oil

Abstract

In this study, a new correlation for determination of effective diffusion/dispersion coefficients in the vapor extraction of heavy oil/bitumen (VAPEX) is introduced. This model takes into account the solvent concentration as well as the drainage height and permeability dependency of these coefficients. The concentration dependency in this model stems from the mixture viscosity changes, while the height dependency appears directly in the correlation. The correlation was obtained using the experimental results of the VAPEX experiments that were conducted with physical models of varying sizes and different permeability sand-packs. Estimation of a proper mass transfer coefficient has been a challenging issue for the analytical and numerical simulation of the VAPEX and other similar processes. Incorporating the effect of drainage height on dispersion with a concentration-dependent diffusivity model enables one to estimate the dispersion coefficient values involved in this process.     

测量天然气在稠油中扩散系数的新方法

可靠的扩散系数测量方法对于稠油开发中气体注入方案设计、页岩气开发中流动机理研究和天然气成藏保存过程中气体运移方式的确定等都具有重要的意义。为此,提出了一种基于压力脉冲技术在稠油中测量扩散系数的新方法。首先通过压力脉冲实验来记录PVT容器空腔内的甲烷气体向稠油扩散过程中的压力变化,然后根据Fick第二定律和油气界面的动态边界条件建立数学模型,利用模型所得到的解析解对实验数据进行拟合得到相应的扩散系数。通过对数学模型的分析可以发现:在任一时刻空腔内还未流入油相中的气体物质的量与扩散达到平衡时流入油相中总的物质的量的比值,在时间较长时与无因次时间呈线性关系;与其他文献进行比较的结果表明,所建立方法的测量结果合理,并可推测出扩散系数随油相黏度的增加而逐渐减小;动态边界数学扩散模型符合实际气体扩散的物理过程,能准确地测量气体在稠油等有机质中扩散系数的大小。同时,所得到的新扩散系数测量方法还具有实验简便、操作简单、不用分析油相组分的优点。     

The Solubility of Asphaltenes in Different Hydrocarbon Liquids

Abstract

Bitumen miscibility in low-molecular-weight hydrocarbon liquids was evaluated. The presence of toluene in bitumen–solvent blends improved bitumen miscibility and led to the delay in onset of asphaltenes precipitation due to the dipole–dipole and heteromolecular interactions. For heavy naphtha, the results showed reduced asphaltenes precipitation and enthalpy of mixing due to strong hydrogen bonding and moderate homomolecular interactions. Hexane and light naphtha systems showed higher heats of mixing and higher asphaltenes precipitation due to homomolecular interactions. The best miscibility characteristics of heavy petroleum were obtained with aromatic solvents and solvent mixtures that contained increasing composition of toluene.     

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.     

充分利用SZ36-1原油资源生产优质沥青

SZ36-1原油由中国海洋石油总公司生产，该原油密度大、粘度高，含蜡量低、胶质高，渣油收率高，为我国少有的低硫环烷基重质原油，是生产优质沥青的好原油，目前主要生产70号及90号重交沥青，中海沥青企业集团与抚顺石油化工研究院合作，根据SZ36-1原油的特点，先后开发了一系列新沥青产品，以适应市场需求。     

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.     

Measurement of gas diffusivity in heavy oils

Molecular diffusion of gases in oil plays a role in several heavy oil recovery processes. In solution gas drive, the gas diffusion coefficient has a direct impact on the amount of gas that is released and the level of supersaturation that exists during pressure depletion. In the Vapex process, molecular diffusion controls the rate at which the solvent vapour is absorbed by the oil. Molecular diffusion is also important in supercritical fluid extraction of heavy oils and in recovery of residual oil by miscible displacement. Unfortunately experimental data on gas diffusion coefficient in heavy oils are relatively scarce due to the tedious nature of diffusivity measurements. The main objective of this work was to develop a simple experimental technique for measuring gas diffusion coefficients in heavy oils. Diffusion coefficients of carbon dioxide and methane were measured by measuring the rate of gas absorption in a high-pressure windowed cell. The diffusion equation, coupled with the gas material balance equation, was used to history match the gas absorption data using the diffusion coefficient as an adjustable parameter. The diffusion coefficients calculated by this history match technique are compared with the reported values of diffusion coefficients in similar systems.     

The Use of Microscopic Bitumen Froth Morphology for the Identification of Problem Oil Sand Ores

Abstract

Oil sand, which is found in various deposits around the world, consists mostly of sand, surrounded by up to 18 wt% bitumen. The largest deposits known are situated in northern Alberta, Canada, where reserves of bitumen are estimated to be 1.7 trillion barrels. Bitumen is similar to heavy oil, but with much higher viscosity and density. The two main commercial oil sand operations in Alberta are surface mines and use aqueous flotation of the bitumen to separate it from the rest of the oil sand. Under optimal conditions up to 95% of the bitumen can be recovered, but occasionally ores are mined that create problems in extraction, and recovery can drop to 70% or less. This article discusses the microscopic morphologies of various bitumen and heavy oil streams and their relationship to processing problems. The results of extensive microscopic work have demonstrated that the bitumen in an oil sand ore is the phase most susceptible to oxidation and that the resulting changes manifest themselves in particular microscopic structures. The presence and type of these structures can be related to the processing behavior of oil sand ores. Morphological features found in froths from commercial operations are similar to those found in froths from laboratory-prepared samples. The morphological features found in froths of oxidized ores have been categorized and quantified for a variety of samples and are referred to as degraded bitumen structures. Experiments in which fresh oil sand ores were subjected to low-temperature oxidation showed that bitumen froth morphology changed dramatically compared to that of nonoxidized ores for identical bulk compositions and extraction water chemistries.     

The Use of Microscopic Bitumen Froth Morphology for the Identification of Problem Oil Sand Ores

Oil sand, which is found in various deposits around the world, consists mostly of sand, surrounded by up to 18 wt% bitumen. The largest deposits known are situated in northern Alberta, Canada, where reserves of bitumen are estimated to be 1.7 trillion barrels. Bitumen is similar to heavy oil, but with much higher viscosity and density. The two main commercial oil sand operations in Alberta are surface mines and use aqueous flotation of the bitumen to separate it from the rest of the oil sand. Under optimal conditions up to 95% of the bitumen can be recovered, but occasionally ores are mined that create problems in extraction, and recovery can drop to 70% or less. This article discusses the microscopic morphologies of various bitumen and heavy oil streams and their relationship to processing problems. The results of extensive microscopic work have demonstrated that the bitumen in an oil sand ore is the phase most susceptible to oxidation and that the resulting changes manifest themselves in particular microscopic structures. The presence and type of these structures can be related to the processing behavior of oil sand ores. Morphological features found in froths from commercial operations are similar to those found in froths from laboratory-prepared samples. The morphological features found in froths of oxidized ores have been categorized and quantified for a variety of samples and are referred to as degraded bitumen structures. Experiments in which fresh oil sand ores were subjected to low-temperature oxidation showed that bitumen froth morphology changed dramatically compared to that of nonoxidized ores for identical bulk compositions and extraction water chemistries.     

The Determination of Effective Diffusivity Coefficients in a Solvent Gas Heavy Oil System for Methane

Abstract

In this investigation, an accurate high pressure and temperature diffusion setup was applied to measure the diffusion coefficients of methane in Iranian heavy oils in presence and absence of porous media by using the pressure-decay method. The solvent diffusivity in heavy oil was determined by both graphical and numerical methods. In addition, the effects of the porous medium and the temperature on the molecular diffusion coefficient of the solvent gas in the liquid phase were discussed and finally, using experimental data, a functionality dependence of molecular diffusivity on temperature and porous medium characteristics was proposed.     

Data-driven modeling of heavy oil viscosity in the reservoir from geophysical well logs

Viscosity is the most crucial fluid property on recovery and productivity of hydrocarbon reservoirs, more particularly heavy oil reservoirs. In heavy and extra heavy oil reservoirs e.g. bitumen and tar sands more energy is required to be injected into the system in order to decrease the viscosity to make the flow easier. Therefore, attempt to develop a reliable and rapid method for accurate estimation of heavy oil viscosity is inevitable. In this study, a predictive model for estimating of heavy oil viscosity is proposed, utilizing geophysical well logs data including gamma ray, neutron porosity, density porosity, resistivity logs, spontaneous potential as well as P-wave velocity and S-wave velocity and their ratio (Vp/Vs). To this end, a supervised machine learning algorithm, namely least square support vector machine (LSSVM), has been employed for modeling, and a dataset was provided from well logs data in a Canadian heavy oil reservoir, the Athabasca North area. The results indicate that the predicted viscosity values are in agreement with the actual data with correlation coefficient (R²) of 0.84. Furthermore, the outlier detection analysis conducted shows that only one data point is out of the applicability of domain of the develop model.     

EMULSIFICATION OF OIL SAND BITUMEN IN CAUSTIC SOLUTION

Bitumen in the form of concentrated bitumen-in-water emulsion can be transported using a pipeline. Froth, which is a product of water based extraction of bitumen from oil sands, can be emulsified using NaOH. The emulsion can then be inverted by lowering pH to recover the bitumen. NaOH concentration, salt concentration, temperature, and mechanical energy input affect the formation of the emulsion and its viscosity. Optimum conditions for emulsion formation and inversion were specified.     

两种油砂加工方法的对比研究

分别采用溶剂萃取法和流化热转化法对内蒙古图牧吉油砂的加工方法进行了研究。溶剂萃取法可以得到油砂中几乎所有油品,但其液体产品具有高密度、高黏度及高残炭等特点,后续加工难度大;流化热转化法可以得到油砂中82.3%的油品,与溶剂萃取法相比,其液体产品的性质得到了较大程度的改善。对流化热转化得到的液体产品进行分馏和分析,其中汽油、柴油收率之和达到了37.32%,但是需要进一步精制才能达到国家油品标准的质量要求;重油收率达到了62.68%,可以通过进一步掺炼实现其轻质化。     

内蒙古图牧吉油砂流化热转化反应规律

 在小型流化热转化实验装置上,考察了内蒙古图牧吉油砂的流化热转化反应规律。得到最佳的反应条件为反应温度490℃、反应时间5 min、水/油质量比0.4、热载体/油砂质量比2。在此最优操作条件下,液体产品收率达到79.87%, 轻油收率达到26.59%。随着图牧吉油砂流化热转化反应温度的升高,干气、液化气及汽油产率增加,这主要来自于重油的二次裂化。热转化后的液体产品相对于油砂沥青,残炭、微量金属含量及黏度都有大幅度的降低,同时馏程得到很大改善,有助于后续的加工利用。     

Evolving ANFIS model to estimate density of bitumen-tetradecane mixtures

Recent investigations have proved more worldwide availability of heavy crude oil resources such as bitumen than those with conventional crude oil. Diluting the bitumen through injection of solvents including tetradecane into such reservoirs to decrease the density and viscosity of bitumen has been found to be an efficient enhanced oil recovery approach. This study focuses on introducing an effective and robust density predictive method for Athabasca bitumen-tetradecane mixtures against pressure, temperature and solvent weight percent through implementation of adaptive neuro-fuzzy interference system technique. The emerged results of proposed model were compared to experimentally reported and correlation-based density values in different conditions. Values of 0.003805 and 1.00 were achieved for mean square error and R², respectively. The developed model is therefore regarded as a highly appropriate tool for the purpose of bitumen-tetradecane mixture density estimation.