共查询到20条相似文献,搜索用时 0 毫秒
1.
Recently due to increasing demand for energy and declination of oil reservoir the researchers have been encouraged to investigate the enhancement of oil recovery (EOR) approaches. One of popular and wide applicable processes in EOR is carbon dioxide injection which is attractive for researchers and industries due to environmentally aspects, good efficiency in displacement and low cost. The carbon dioxide injection causes the hydrocarbons extracted from crude oil so the solubility of hydrocarbon in carbon dioxide which is one of the critical parameters affects this phenomenon becomes interesting topic for researchers. In the present work Grid partitioning based Fuzzy inference system approach as a new method for prediction of solubility of hydrocarbons in carbon dioxide as function of temperature, pressure and carbon number of alkane was applied. To show the accuracy of the model the coefficients of determination were determined as 0.9902 and 0.9584 for training and testing phases respectively. 相似文献
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Karim Rouhibakhsh Houman Darvish Hamed Sabzgholami Mohammad Sadegh Goodarzi 《Petroleum Science and Technology》2018,36(15):1143-1149
In the recent years, the enhancement oil recovery processes become the one of the interesting topics in petroleum engineering because of declination of oil reservoirs. One of the most popular processes is the carbon dioxide injection that has special importance because of its environmentally friendly and high efficiency of displacement. The interfacial tension (IFT) between carbon dioxide and hydrocarbon is known as a key parameter in this process so in the present investigation the Adaptive neuro-fuzzy inference system (ANFIS) was coupled with Genetic Algorithm (GA) to create a novel tool for prediction IFT between carbon dioxide and hydrocarbon in terms of temperature, pressure, molecular weight of alkane, gas and liquid densities. The outputs of predicting model were compared with experimental IFT statistically and graphically. The comparisons showed that predicting model has acceptable accuracy in prediction of IFT of hydrocarbon and carbon dioxide. 相似文献
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Mohammad Hosein Emami Baghdadi Houman Darvish Hesam Rezaei Mohammad Savadinezhad 《Petroleum Science and Technology》2018,36(15):1170-1174
One of the critical parameters in petroleum and chemical engineering is the interfacial tension between brine and hydrocarbon which has major effects on trapping and residual oil in reservoir pore throat so it becomes one of the interesting topics in enhancement of oil recovery in this work Least squares support vector machine (LSSVM) algorithm was applied as a novel predicting machine for prediction of interfacial tension of brine and hydrocarbons in terms of hydrocarbon carbon number, temperature, pressure and ionic strength of brine. A total number of 175 interfacial tensions were collected from literature in the purpose of training and testing of the model. The root mean squared error (RMSE), average absolute relative deviation (AARD) and the coefficient of determination (R2) were calculated overall datasets as 0.23964, 0.27444 and 0.98509 respectively. The results of study showed that predicting LSSVM machine can be applicable for estimation of interfacial tension and EOR processes. 相似文献
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Fardin Shakeri Houman Darvish Hamid Garmsiri 《Petroleum Science and Technology》2018,36(9-10):648-653
The worldwide demand for energy increases and also the price of crude oil increases so these reasons have been caused the searchers have motivated to investigate enhanced of oil recovery (EOR) processes. The carbon dioxide injection is recognized as one of the favorable approaches of EOR because of high displacement efficiency, environmentally aspects and lower cost. The Interfacial tension between crude oil and carbon dioxide is known as one of the critical factors which affect the performance of injection. The main objective of the present investigation is development of Fuzzy c-means (FCM) approach as novel method to estimate interfacial tension between carbon dioxide and hydrocarbons as function of pressure, temperature, liquid and gas densities and molecular weight of alkane. The performance of predicting model was evaluated statistically and graphically and the results confirmed the ability of the model to predict interfacial tension between carbon dioxide and hydrocarbons. 相似文献
5.
Houman Darvish Hamid Garmsiri Mohsen Zare Nassim Hemmati 《Petroleum Science and Technology》2018,36(4):308-312
In the recent years, declination of oil reservoir causes the importance of researches on enhancement of oil recovery processes become more important. One of wide applicable approaches in enhancement of oil recovery is carbon dioxide injection which becomes interested because of relative low cost, good displacement and environmentally aspects. The injection of carbon dioxide to oil reservoir causes the lighter hydrocarbons of crude oil are extracted by CO2. This phenomena can be affected by various factors such the solubility of hydrocarbons in carbon dioxide so in the present investigation Fuzzy c-means (FCM) as a novel approach for estimation of solubility of alkanes in carbon dioxide in terms of temperature, pressure and carbon number of alkane were utilized. The predicting algorithm FCM has reliable ability to estimate solubility based on graphical and statistical results. The coefficient of determination (R2) for training and testing data are calculated as 0.9856 and 0.9529 respectively. 相似文献
6.
Houman Darvish Hamed Raji Asadabadi Ashkan Maleki Sadeghi karim Rouhibakhsh 《Petroleum Science and Technology》2018,36(9-10):660-665
Nowadays the importance of enhanced oil recovery (EOR) processes increases because of increasing demand of energy and declination of oil reservoirs. Due to this fact the researchers attracted to study performance of EOR methods. one of the high efficient methods is carbon dioxide injection which is favorable because of low cost and environmental friendly viewpoints. One of important parameters which have straight effect on recovery of injection is interfacial tension between carbon dioxide and hydrocarbons. In the present investigation the main objective is proposing the Grid partitioning based Fuzzy inference system method as novel approach to predict interfacial tension of carbon dioxide and hydrocarbon in terms of temperature, pressure, liquid and gas densities and molecular weight of alkane. The coefficients of determination for different datasets of training and testing of estimating algorithm are determined as 0.9919 and 0.9899. This results express the algorithm has potential of estimating interfacial tension of hydrocarbons and carbon dioxide. 相似文献
7.
基于平衡常数k和超临界CO2密度ρ1的曲线关系,提出了一个改进的溶解度模型用于计算溶质在超临界CO2中的溶解度,该模型强化了温度对k的影响。改进的溶解度模型计算了18种溶质在超临界CO2中的溶解度,并与常用的Chrastil,Adachi-Lu,del Valle-Aguilera,Sparks模型进行了对比。计算结果表明,改进模型精度最高,其绝对平均偏差(AAD)的平均值为5.81%,而Chrastil,Adachi-Lu,del Valle-Aguilera,Sparks模型的AAD平均值分别为10.66%,7.38%,9.91%,7.00%。该模型为溶质在超临界CO2中的溶解度计算提供了一种新的方法。 相似文献
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研究了啤酒花在超临界CO2中的平衡溶解度随介质温度和压力的变化规律,以及溶解特性。选择适宜的模型,用实验数据对模型进行验算,结果令人满意 相似文献
10.
Razieh Razavi Mohammad Navid Kardani Alireza Ghanbari 《Petroleum Science and Technology》2018,36(11):807-812
In the gas engineering the accurate calculation for pipeline and gas reservoirs requires great accuracy in estimation of gas properties. The gas density is one of major properties which are dependent to pressure, temperature and composition of gas. In this work, the Least squares support vector machine (LSSVM) algorithm was utilized as novel predictive tool to predict natural gas density as function of temperature, pressure and molecular weight of gas. A total number of 1240 experimental densities were gathered from the literature for training and validation of LSSVM algorithm. The statistical indexes, Root mean square error (RMSE), coefficient of determination (R2) and average absolute relative deviation (AARD) were determined for total dataset as 0.033466, 1 and 0.0025686 respectively. The graphical comparisons and calculated indexes showed that LSSVM can be considered as a powerful and accurate tool for prediction of gas density. 相似文献
11.
The interfacial tension that exists between brine and hydrocarbon is known as one of major properties in petroleum industries because it extremely affects oil trapping in reservoirs and consequently oil recovery. Due to aforementioned reasons the importance of investigation of this parameter has been highlighted. In the present study, Fuzzy C-means (FCM) algorithm was developed to predict interfacial tension between hydrocarbon and brine as function of different parameters such as pressure, temperature, carbon number of hydrocarbon and ionic strength of brine. The obtained results of predicting algorithm expressed its low relative error and deviation from the experimental data which gathered from the literature. Also the coefficients of determination (R2) for training and testing data were calculated 0.9508 and 0.9309 respectively. This predictive tool is simple and user friend to utilize and can be helpful for petroleum engineers to estimate interfacial tension between hydrocarbons and brine. 相似文献
12.
Soroush Khosravani Haghighi 《Petroleum Science and Technology》2018,36(15):1137-1142
The most of oil reservoirs in the world are heavy oil and bitumen reservoirs. Due to high viscosity and density of these types of reservoirs the production has problems so importance of enhanced oil recovery (EOR) processes for them is clear. The injection of solvents such as tetradecane is known as one of methods which improve oil recovery from bitumen reservoirs. In the present investigation, the Least squares support vector machine (LSSVM) algorithm was used to estimate density of Athabasca bitumen and heavy n-alkane mixture in term of temperature, pressure and weight percent of the solvent. The Root mean square error (RMSE), average absolute relative deviation (AARD) and the coefficient of determination (R2) for total dataset are determined 0.033466, 0.0025686 and 1 respectively. The predicted results indicate that the LSSVM algorithm has potential to be a predicting machine for the bitumen-heavy alkane mixture density prediction. 相似文献
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Asphaltene precipitation is one of critical problems for petroleum industries. There are different methods for inhibition of asphaltene precipitation. One of the common and effective methods for inhibition of asphaltene precipitation is utilizing asphaltene inhibitors. In this work, Least squares support vector machine (LSSVM) algorithm was coupled with simplex optimizer to create a novel and accurate tool for estimation of effect of inhibitors on asphaltene precipitation as function of concentration and structure of inhibitors and crude oil properties. To this end a total number of 75 measured data was extracted from the literature for training and testing of predicting model. The average absolute relative deviation (AARD), the coefficient of determination (R2) and root mean square error (RMSE) of total data for prediction algorithm were determined as 1.1479, 0.99406 and 0.61039. According to these parameters and graphical comparisons the LSSVM algorithm has potential to predict asphaltene precipitation in high degree of accuracy. 相似文献
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Houman Darvish Pejman Ghani Mohsen Zare Hesam Rezaei 《Petroleum Science and Technology》2018,36(5):338-342
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. 相似文献
16.
Alireza Baghban Peyman Abbasi Peyman Rostami 《Petroleum Science and Technology》2016,34(20):1698-1704
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. 相似文献
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Box—Behnken法研究二氧化碳驱油效果影响因素 总被引:2,自引:1,他引:1
温室气体CO2使全球气候变暖,对人类的生存和社会经济的发展构成了严重威胁。CO2地质处置的最有效方式就是注入油气田。国外很多油田已成功地进行大规模CO2驱并取得较好的效果,证明CO2驱是三次采油中最具潜力的提高采收率方法之一。针对这一问题,文中综合考虑各种影响因素,基于详细理论研究与分析,建立典型CO2驱油模型,开展数值计算,在单因素分析的基础上,引入综合反映CO2驱油效果的无因次参数,运用Box—Behnken试验设计,通过曲面反应法建立计算CO2驱油采收率的二项式计算模型,并对反应曲面结果进行分析,得出无因次参数对CO2驱油效果的影响顺序和交互影响的显著性。其研究成果对CO2驱油具有理论及现场指导意义。 相似文献
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CO_2在碳酸氢钠水溶液中溶解度的研究 总被引:3,自引:0,他引:3
实验研究了CO2在不同温度、压力下在碳酸氢钠水溶液中的溶解度,并对所测定的溶解度数据用新建立的热力学模型进行了模型计算,并同改进的P-T方程进行了比较。结果表明新热力学模型的计算结果与实验数据吻合较好,尤其在压力较高时,该模型能给出优于改进的P-T方程的计算结果。 相似文献
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与稀油注CO2提高采收率机理不同,CO2与稠油无法达到混相,因此影响其开发效果的主要因素差别很大,特别是在热化学复合采油过程中,注入的CO2主要发挥隔热、降黏、增能的作用。为了进一步研究不同因素对稠油油藏注CO2驱替效果的影响,在稠油样品物性分析的基础上,利用正交实验方法研究了原油黏度、温度、压力和渗透率对稠油油藏注CO2提高采收率的影响。温度对采收率影响最大,其他因素由大到小依次为:渗透率、压力、油样类型。根据实验结论及认识,综合考虑地层温度、油藏渗透率等因素,在胜利油田开展了稠油油藏注CO2吞吐提高采收率矿场试验。从矿场实际生产结果来看,油藏温度增加以及油藏渗透率提高,都有利于注CO2吞吐开发,都能够有效提高油井产量。 相似文献