Intelligent model for prediction of CO2 - Reservoir oil minimum miscibility pressure
Intelligent model for prediction of CO2 - Reservoir oil minimum miscibility pressure
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DOI：
10.1016/j.fuel.2013.04.036
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发表时间：
2013-10-01
期刊：
影响因子：
7.4
通讯作者：
Mohammadi, Amir H.
中科院分区：
文献类型：
--
作者：
Shokrollahi, Amin;Arabloo, Milad;Mohammadi, Amir H.
多重接触混相驱，例如将相对便宜的气体注入油藏，被认为是针对常规油藏的成熟的提高采收率（EOR）技术。注气项目设计的一个基本因素是最小混相压力（MMP），而注气的局部波及效率很大程度上取决于 MMP。细管位移和上升气泡装置 (RBA) 是用于实验测定 MMP 的两种主要测试，但这些测试既昂贵又耗时。因此，寻找快速、准确的瓦斯油MMP数学测定方法势在必行。本研究的目的是提出一种可靠的预测模型，即最小二乘支持向量机 (LSSVM)，以预测纯和不纯 CO2 MMP。为此，利用文献中约147个属于实验CO2 MMP值的数据集和相应的气/油成分信息来构建和评估模型的可靠性。结果表明，所提出的模型显着优于所有现有方法，并提供与实验数据一致的预测。此外，结果表明，所提出的模型能够模拟 CO2 MMP 相对于五个最重要的输入参数的实际物理趋势：储层温度、戊烷分子量、硫化氢和氮浓度。最后，为了检测可能可疑的CO2 MMP数据，对数据集进行异常诊断。 (C) 2013 Elsevier Ltd. 保留所有权利。
Multiple contact miscible floods such as injection of relatively inexpensive gases into oil reservoirs are considered as well-established enhanced oil recovery (EOR) techniques for conventional reservoirs. A fundamental factor in the design of gas injection project is the minimum miscibility pressure (MMP), whereas local sweep efficiency from gas injection is very much dependent on the MMP. Slim tube displacements, and rising bubble apparatus (RBA) are two main tests that are used for experimentally determination of MMP but these tests are both costly and time consuming. Hence, searching for quick and accurate mathematical determination of gas-oil MMP is inevitable. The objective of this study is to present a reliable, and predictive model namely, Least-Squares Support Vector Machine (LSSVM) to predict pure and impure CO2 MMP. To this end, about 147 data sets belonging to experimental CO2 MMP values from the literature and corresponding gas/oil compositional information was used to construct and evaluate the reliability of the model. The results show that the proposed model significantly outperforms all the existing methods and provide predictions in acceptable agreement with experimental data. Moreover, it is shown that the proposed model is capable of simulating the actual physical trend of CO2 MMP versus five most important input parameters: reservoir temperature, molecular weight of pentane plus, hydrogen sulfide and nitrogen concentration. Finally, for detection of the probable doubtful CO2 MMP data, outlier diagnosis was performed on the data sets. (C) 2013 Elsevier Ltd. All rights reserved.