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A Practical Method for MinimunnMiscibility-Pressure Estimation of Contaminated CO_2 Mixtures

机译:最小化被污染的CO_2混合物的混溶性-压力估算的实用方法

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Minimum miscibility pressure (MMP) is a key parameter in the design of gasfloods. Injection-gas compositions often vary during the life of a gasflood owing to reinjection and mixing of fluids in situ. Understanding the impact of the gas compositional changes on the MMP is essential to optimal design of fieldwide pressure management and carbon dioxide (CO_2) use. Determining the MMP by slimtube or other methods for each possible variation in the gas-mixture composition is impractical. This paper gives an easy and accurate way to determine impure CO_2 MMPs for variable field solvent compositions on the basis of just a few MMPs. Alternatively, the approach could be used to estimate the enrichment level required to lower the MMP to a desired pressure.rnThe MMP-estimation method relies on determining the MMP for pure CO_2 injection, and also for a few impure binary MMPs at small CO_2-contaminant levels. The number of MMPs needed for the method is equal to the number of components in the injection gas. We use the method of characteristics (MOC) and our newly developed mixing-cell method to estimate the required MMPs, although any reliable MMP analytical or experimental method can be used. We demonstrate how to calculate MMPs for several multicompo-nent oils displaced by CO_2 contaminated by mixtures of N_2, CH_4, C_2, C-3 and H_2S. The results show that the predicted MMPs for a west Texas crude displaced by contaminated-CO_2 injection streams are nearly linear over the range from pure-CO_2 injection to any mole fraction combination of the five contaminants. The accuracy of the predicted MMPs is within ±15 psia of that from calculations using mixing-cell simulations, slimtube simulations, and slimtube experiments where available. For another example oil displacement by impure CO_2, however, the linear trend in MMPs with contamination mole fractions is accurate only for total contamination levels less than approximately 20% mole fraction, but this is still within a useful range for CO_2-gasflood design and optimization. We also examine the sensitivity of local displacement efficiency to dispersion for binary gas mixtures using 1D simulation.
机译:最小混溶压力(MMP)是气驱设计中的关键参数。由于在原地重新注入和混合流体,因此在气驱寿命期间注入气体的成分通常会发生变化。理解气体成分变化对MMP的影响对于优化现场压力管理和二氧化碳(CO_2)的使用至关重要。对于气体混合物组成的每种可能的变化,通过细管或其他方法确定MMP是不切实际的。本文提供了一种简单而准确的方法,可以仅基于几个MMP来确定可变场溶剂成分的不纯CO_2 MMP。或者,该方法可用于估算将MMP降低至所需压力所需的富集水平。rnMMP估算方法依赖于确定纯CO_2注入的MMP,也取决于少量CO_2污染的不纯二元MMP。水平。该方法所需的MMP数量等于注入气体中的组分数量。尽管可以使用任何可靠的MMP分析或实验方法,但我们使用特征方法(MOC)和我们新开发的混合池方法来估计所需的MMP。我们演示了如何计算几种被N_2,CH_4,C_2,C-3和H_2S的混合物污染的CO_2取代的多成分油的MMP。结果表明,从纯CO_2注入到五种污染物的任何摩尔分数组合,被污染的CO_2注入流驱替的德克萨斯州西部原油的预测MMP几乎是线性的。预测的MMP的准确度在使用混合池模拟,slimtube模拟和slimtube实验(通过可用的计算)的计算结果的±15 psia以内。但是,对于不纯CO_2驱油的另一个示例,具有污染摩尔分数的MMP中的线性趋势仅对于总污染水平小于约20%摩尔分数才是准确的,但是对于CO_2气驱设计和优化仍处于有用范围内。我们还使用一维模拟研究了二元混合气体局部位移效率对弥散度的敏感性。

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