首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到10条相似文献,搜索用时 118 毫秒
1.
Abstract

Viscosity is one of the most important governing parameters of the fluid flow, either in the porous media or in pipelines. So it is important to use an accurate method to calculate the oil viscosity at various operating conditions. In the literature, several empirical correlations have been proposed for predicting undersaturated crude oil viscosity. However these correlations are not able to predict the oil viscosity adequately for a wide range of conditions. An extensive experimental data of undersaturated oil viscosities from different samples of Iranian oil reservoirs was applied to develop an Artificial Neural Network (ANN) model and fuzzy model to predict and calculate the undersaturated oil viscosity. Validity and accuracy of these models has been confirmed by comparing the obtained results of these correlations and with experimental data for Iranian oil samples. It was observed that there is acceptable agreement between the ANN model and fuzzy model results with experimental data.  相似文献   

2.
Reservoir oil properties are usually measured at reservoir temperature and are estimated at other temperature using empirical correlations. Fluid properties correlations cannot be used globally because of different characteristics of fluids in each area. Here, based on Iranian oil PVT data, new correlations have been developed to predict saturation pressure and oil formation volume factor at bubble point pressure. Validity and accuracy of these correlations were confirmed by comparing results of these correlations with experimental data. Checking the results shows that results for Iranian oil properties in this work are in good agreement with experimental data respect to other correlations.  相似文献   

3.
Viscosity is a parameter that plays a pivotal role in reservoir fluid estimations. Several approaches have been presented in the literature (Beal, 1946; Khan et al, 1987; Beggs and Robinson, 1975; Kartoatmodjo and Schmidt, 1994; Vasquez and Beggs, 1980; Chew and Connally, 1959; Elsharkawy and Alikhan, 1999; Labedi, 1992) for predicting the viscosity of crude oil. However, the results obtained by these methods have significant errors when compared with the experimental data. In this study a robust artificial neural network (ANN) code was developed in the MATLAB software environment to predict the viscosity of Iranian crude oils. The results obtained by the ANN and the three well-established semi-empirical equations (Khan et al, 1987; Elsharkawy and Alikhan, 1999; Labedi, 1992) were compared with the experimental data. The prediction procedure was carried out at three different regimes: at, above and below the bubble-point pressure using the PVT data of 57 samples collected from central, southern and offshore oil fields of Iran. It is confirmed that in comparison with the models previously published in literature, the ANN model has a better accuracy and performance in predicting the viscosity of Iranian crudes.  相似文献   

4.
选取渤海油田地面50℃脱气原油黏度366.4~72 477.0mPa·s的黏温曲线进行拟合,结果表明ASTM标准二次对数坐标下,各样本的直线拟合关系良好,各直线的斜率近似相同,并进一步得出了渤海稠油黏度预测公式,根据50℃地面原油黏度可以预测其他温度时的脱气原油黏度。将计算得出的地层温度下的脱气原油黏度与已有的PVT实验数据进行对比,通过数据回归,得出了地层含溶解气的原油黏度预测公式,可为渤海稠油油藏开发方案设计提供参考。  相似文献   

5.
Abstract

Pressure–volume–temperature (PVT) properties of crude oil are essential parameters used for prediction of fluid flow both in porous media and through transmission pipelines. Whenever laboratory works are absent, the engineer should use regionally developed correlations. A large portion of all crude oil resources is located in the Persian Gulf countries, and they have more or less similar API ranges and acidities, so that any empirical PVT correlation based on data from one region can adequately predict the behavior of others in this large geological basin. In this study, a new set of black oil–type correlations for bubble point pressure (Pb), solution gas–oil ratio (GOR; Rs), and formation volume factor (Bo) is proposed based on more than 400 Iranian crude oil PVT lab data. Moreover, previous works were reviewed, most of which were not suitable to model Iranian crude PVT behavior. Although the new correlations are developed over Iranian crudes, they can be used for prediction over any crude oil with similar compositional properties (API and acidity). Then the accuracy of these correlations is compared with the newly presented set and the superiority of this work for predicting those parameters is demonstrated.  相似文献   

6.
核磁共振测井在砂砾岩稠油油藏评价中的应用   总被引:2,自引:0,他引:2  
卜凌梅  赵文杰 《测井技术》2004,28(6):531-534
胜利油区的宁海-王庄油田储层岩性复杂,油质稠,常规测井资料在产液性质、产层性质评价及储层参数计算等方面存在困难.核磁共振测井在该油田的有效储层划分、流体识别、孔隙结构研究等方面发挥了重要作用.但由于稠油粘度大,含氢指数低,也造成核磁共振测井的孔隙度、渗透率偏低.因此,在6口砂砾岩稠油井的核磁共振测井资料分析的基础上,提出了稠油校正方法,经稠油校正后,计算的储层参数更加准确,满足了砂砾岩稠油油藏精细评价的要求.  相似文献   

7.
Abstract

A generalized equation based on modified Eyring's theory for predicting kinematic viscosity of petroleum fractions is proposed in this work. The equation uses two reference fluids including a pair of (C6 and C10), (C10 and C14), or (C14 and C20) for petroleum fractions of molecular weight higher than 70 and lower than 300.

Validity and accuracy of this equation have been confirmed by comparing the obtained results of this equation with experimental data. In contrast to other correlations that require so many specific parameters for oil viscosity prediction, this type of equation requires only molecular weight and true boiling point. The results obtained in this work are in agreement with experimental data with an average absolute deviation (AAD) of less than 5%.  相似文献   

8.
稠油油藏水平井产能预测新模型   总被引:2,自引:0,他引:2  
不同黏度下稠油室内实验研究结果,证明了稠油流动中存在启动压力梯度,启动压力梯度随原油黏度的增大而增大。考虑水平井三维空间渗流特征和启动压力梯度,应用速度势理论建立了稠油油藏水平井产能预测新的数学模型。应用新模型,对海上稠油油藏水平井产能进行了预测,分析了启动压力梯度对稠油油藏水平井产量和动用范围的影响:启动压力越大,水平井产能越低;启动压力梯度增大了渗流的阻力,减小了水平井的动用范围。  相似文献   

9.
Abstract

The oil recovery and rate of production are highly dependent on viscosity of reservoir fluid so this term becomes one of the attractive parameters in petroleum engineering. The viscosity of fluid is highly function of composition, temperature, and pressure so in this article, Grid partitioning based Fuzzy inference system approach is utilized as novel predictor to estimate dynamic viscosity of different normal alkanes in the wide range of operational conditions. In order to comparison of model output with actual data, an experimental dataset related to dynamic viscosity of n-alkanes is gathered. The graphical and statistical comparisons between model outputs and experimental data show the high quality performance of predicting algorithm. The coefficients of determination (R2) of training and testing phases are 0.9985 and 0.9980, respectively. The mentioned statistical indexes represent the great accuracy of model in prediction of dynamic viscosity.  相似文献   

10.
目前海上油田受多方面因素制约,地层流体取样少或无取样,而南海西部北部湾区域油藏流体性质变化较大,导致地层原油黏度难以准确预测。针对上述问题,通过收集北部湾区域已开发油藏地面及地层流体性质资料,分析影响原油黏度的主控因素,从主到次依次为含硫量、胶质含量、沥青质含量、含蜡量,其中胶质含量、沥青质含量和含硫量组合因素对原油性质影响显著,原油黏度对温度敏感,原油脱气前,压力对其影响小;运用数理统计学原理,建立了地面原油参数团、原油密度、地面脱气原油黏度与地层原油黏度间的3种评价方法,经乌石油田群15个样本点检验,平均绝对误差在0.5 mPa·s左右。该预测方法可为流体评价和油藏开发提供较为科学可靠的地层原油黏度资料。  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号