尼日利亚原油泡点压力下原油粘度与死油粘度的数学模型

Y. Adeeyo
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引用次数: 0

摘要

传统上,油藏工程流体流动计算使用粘度数据。然而,在缺乏实验室/实验数据的情况下,使用其他可用的推导相关性来预测PVT特性。由于可用数据数量的限制,流体的区域特性,文献中几种粘度相关性的准确性和适用性有限。这项研究利用来自尼日利亚不同地点的2020多个未发表的PVT数据集,在严格的非线性回归建模中开发了预测模型。不同的非线性算法,改进的Newton-Raphson非线性最小二乘数据拟合方法;利用Levenberg-Marquardt算法建立了气泡点压力下粘度和死油粘度的新模型。气泡点黏度模型的性能结果表明,该模型具有较好的预测效果,平均绝对相对误差为21.06,相关系数为0.98;dead oil黏度模型的平均绝对相对误差为30.06,相关系数为0.90。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematical Modelling of Oil Viscosity at Bubble point Pressure and Dead Oil Viscosity of Nigerian Crude
Traditionally, reservoir engineering fluid flow calculations use viscosity data. However, in the absence of lab/experimental data other available derived correlations are used to predict the PVT property. Limit on the number of available data, regional peculiarity of the fluid, several viscosity correlations in the literature have limited accuracy and applicability. This study has developed predictive models using more than 2020 unpublished PVT data sets from different locations in Nigeria in rigorous nonlinear regression modelling. Different nonlinear algorithms, modified Newton-Raphson nonlinear least-square data fitting approach; Levenberg-Marquardt algorithm were used to develop new models for the estimation of the viscosity at the bubblepoint pressure and dead oil viscosity. The results of the performance of the model for viscosity at the bubblepoint show that the model provides better prediction with average absolute relative error of 21.06 and coefficient of correlation of 0.98 and the dead oil viscosity model shows a substantial improvement with average absolute relative error of 30.06 and coefficient of correlation of 0.90 over published correlations.
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