强化水交变气的实际放大过程:数值研究

S. Majidaie, L. Hendraningrat, M. Hanifah
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摘要

水气交替(WAG)是一种众所周知的改善注气过程中流动性问题的策略。然而,在储层非均质性高、储层高渗透带的油田,WAG在实施过程中仍存在一定的挑战,会造成不利的流度比。利用泡沫和表面活性剂对WAG (EWAG)岩心取样的性能进行了研究,并取得了成功。本文将介绍EWAG在马来西亚油田的试点工作过程,重点介绍升级过程中的数值研究。泡沫处理具有控制气相流动性、延缓气侵、将气驱至未波及层的作用。同时,利用表面活性剂降低气液间的IFT,使气体向液相分散。研制了一种内部发泡表面活性剂,并将其用于恶劣环境下的岩心驱油实验。它被用来在与气体接触时产生稳定的泡沫,并导致流动性降低,适合于动员被困油,从而提高石油采收率。在原生岩心上进行了驱芯实验,并对所有实验结果进行了整合和核对,为油藏模拟器的质量先验模型标定提供了依据。一旦构建了岩心驱油模型,使用默认泡沫参数运行基本情况。它最初的目的是测试模型是否平稳运行,并使用默认值观察匹配质量。一旦达到满意的匹配,该过程继续进行,泡沫参数升级。在放大过程中,流体的速度和压降作为实验室数据被保留。研究了重要的放大参数和相应的放大倍率。通过将每次泡沫循环的平均DP除以之前注气时的基压差(DP),计算迁移率降低系数(MRF)。低速率和高速率的MRF值都显示出增加的MRF值。无论如何,与高流量序列相比,这些值在低流量序列中较低。这与实验室分析中计算的MRF值相对应。因此,使用更高的注射速率可以产生更坚固、更稳定的泡沫。低流量和高流量的泡沫参数组各不相同。在差压、油、水、气条件下均达到了可接受的匹配。适用于低流量。基于此研究,模型能够捕捉实验室分析中描述的生产趋势。高流量下的泡沫参数集具有更大的潜力,可以进一步扩大规模并在全油田规模下进行建模。
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Practical Upscaling Process for Enhanced Water Alternating Gas : A Numerical Investigation
Water alternating gas (WAG) is a well-known strategy to improve the mobility issues during gas injection. However, WAG was identified still having some challenges during implementation at oilfield with high reservoir heterogeneity and high permeable zones in the reservoir and will cause unfavorable mobility ratio. Enproperties of the selected core samplehancement of WAG (EWAG) using foam and surfactant has been research to solve its issue and has success stories. This paper will describe the work process of EWAG to be Pilot at Malaysian oilfield, focusing on numerical investigation during upscaling process. Foam treatment has role for gas mobility control, delaying gas breakthrough and diverting gas to unswept zones. Meanwhile, the surfactant was utilized to reduce the IFT between gas and liquid to enable gas dispersion into liquid phase. An in-house foaming surfactant has been developed and used for coreflooding experiment at harsh environment. It was used to generate stable foam in contact with gas and it caused a mobility reduction which was suitable for mobilizing trapped oil and hence improving oil recovery. Coreflood experiment was performed on native core and all experimental results were consolidated and checked for the quality prior model calibration in the reservoir simulator. Once coreflood model was constructed, base case was run using default foam parameters. It aimed initially to test whether the model run smoothly and to observe the matching quality using the default values. Once satisfactory matchings were achieved, the process continued with foam parameters upscaling. During scale-up process the velocity of the fluids and pressure drop were conserved as laboratory data. The important scale-up parameters and the corresponding scale-up ratio were investigated. Mobility Reduction Factor (MRF) was calculated by dividing average DP for each foam cycle with base differential pressure (DP) in the prior gas injection. MRF values for both lower and higher rate show increasing MRF values. Regardless, these values are lower in lower flowrates sequences compared to ones for higher flowrates. This corresponds to MRF values calculated in the laboratory analysis. Therefore, stronger and more stabilized foam were generated using higher injection rates. Lower and higher flowrates had distinctive set of foam parameters. The acceptable matches for differential pressure, oil, water, and gas were achieved. for lower flowrate. Based on this study, model was able to capture production trends depicted in the laboratory analysis. The foam parameter set from higher flowrates have more potential for further upscaling and modeling in full-field scale.
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