Evaluation of immiscible CO2 injection in high water production reservoir in the Pannonian basin

I. Al-Jeboore, Danica Milićević, Bojan Martinović, Milica Ješić
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Abstract

Carbon dioxide (CO2) flooding is one of the most important and most used enhanced oil recovery (EOR) method because it does not only increase oil recovery efficiency but also is used as an underground CO2 storage. It is considered a very complex method as it involves knowing the fluid phase behavior with different CO2 concentrations. It should be noted that oil swelling (volume increase) with the dissolution of carbon dioxide has a significant effect on increase of oil recovery. When this occurs, a significant decrease in the viscosity of the oil is observed. In this study, a reservoir 3D simulation modeling approach was applied to evaluate immiscible and miscible CO2 flooding in a high WC reservoir. To reduce simulation time, the PVT composition was grouped into 5 fluid components. The 3-parameter, Peng-Robinson Equation of State (EOS) was used to match PVT experimental data by using the Schlumberger's ECLIPSE PVTi software. One-dimensional slim-tube model was defined using ECLIPSE 300 software to determine the minimum miscibility pressure (MMP) for injection of CO2. Beside this approach, an analytical MMP estimation was carried out using several correlations. Schlumberger Petrel software was used to set up a 3D simulation model of a static and dynamic model. Various scenarios of immiscible and CO2 injection have been simulated using ECLIPSE 300 software and these results have been compared.
潘诺尼亚盆地高含水油藏非混相CO2注入评价
二氧化碳驱油是最重要和最常用的提高采收率(EOR)方法之一,因为它不仅可以提高石油采收率,而且可以作为地下二氧化碳的储存手段。它被认为是一种非常复杂的方法,因为它涉及到了解不同CO2浓度下的流体相行为。需要注意的是,随着二氧化碳的溶解,油溶胀(体积增大)对提高采收率有显著的作用。当这种情况发生时,观察到油的粘度显著降低。在本研究中,采用油藏三维模拟建模方法对高WC油藏的非混相和混相CO2驱油进行了评价。为了减少模拟时间,将PVT组成分为5个流体组分。使用斯伦贝谢的ECLIPSE PVTi软件,使用3参数Peng-Robinson状态方程(EOS)来匹配PVT实验数据。利用ECLIPSE 300软件定义一维细管模型,确定CO2注入的最小混相压力(MMP)。除了这种方法之外,还使用几个相关性进行了分析性MMP估计。采用斯伦贝谢Petrel软件建立了静态模型和动态模型的三维仿真模型。利用ECLIPSE 300软件对不同的非混相和CO2注入情况进行了模拟,并对结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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