Mangala聚合物驱性能:通过原位聚合物取样连接点

Vivek Shankar, Shekhar Sunit, A. Brown, Abhishek Kumar Gupta
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引用次数: 4

摘要

本文介绍了Mangala油田的聚合物原位取样,这有助于解释印度Mangala油田大规模聚合物驱的性能。Mangala油田含有中等稠度原油。值得注意的是,它是印度最大的聚合物驱,在11年的生产中,已经开采了34%的STOIIP。Mangala油田在2009年开始注水生产6年后,于2015年进行了全油田聚合物驱。聚合物驱在6年内比预期的注水采收率增加了9300万桶。油藏模拟模型可以复制Mangala聚合物驱的初始性能。然而,Mangala低层(FM-3和FM-4)的性能继续逐渐偏离模型估计。同样重要的是,聚合物突破的预测与模型估计有很大偏差。经过6年和0.7孔体积的聚合物注入,很明显,现场性能仅相当于地面注入聚合物粘度的50-60%。为了更好地了解和量化聚合物降解的性质和程度,有必要收集在储层条件下停留相当长时间的具有代表性的聚合物的井下样品。实验室加速老化研究表明,在长时间暴露于Mangala油藏条件下,HPAM会失去粘度和沉淀,而水解程度的增加是降解的主要原因。利用基于一级动力学的传递函数概念,将实验结果外推到Mangala储层温度。为了验证这一假设,一个多学科团队实施了一项计划,从储层中收集具有代表性的聚合物样本。聚合物样品在储层中放置了近120天,并在低剪切和厌氧条件下捕获,以尽量减少剪切和氧化降解。用核磁共振法测定了样品的水解度。结果证实,注入的HPAM的水解水平确实在储层中增加,导致粘度降低,酰胺浓度降低。利用粘度半衰期的概念进行了初步的模拟研究,模拟了聚合物在储层中随时间的降解。该方法是一种非常简单的热降解表示,但它显著提高了模型对下层含水率的预测和对全油田聚合物突破的预测。储层中聚合物沉淀对渗透率的影响正在研究中,这将推动下一阶段更详细的建模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mangala Polymer Flood Performance: Connecting the Dots Through in Situ Polymer Sampling
The paper describes the in-situ polymer sampling in Mangala which helped explain the performance of a large polymer flood in Mangala field in India. The Mangala field contains medium-gravity viscous crude oil. Notably, it is the largest polymer flood in India and 34% of the STOIIP has been produced in 11 years of production. Mangala was put on full field polymer flood in 2015, six years after the start of field production on water flood in 2009. Polymer flood added 93 million barrels above the anticipated water flood recovery in 6 years. Reservoir simulation models could replicate the initial Mangala polymer flood performance. However, the performance of the lower layers of Mangala (FM-3 and FM-4) continued to progressively deviate from modeling estimates. Equally importantly, the prediction of polymer breakthrough deviated significantly from modeling estimates. After 6 years and 0.7 pore volumes of polymer injection, it is apparent that field performance is equivalent to only 50-60% of the viscosity of the polymer injected at the surface. To better understand and quantify the nature and extent of polymer degradation it is necessary to gather representative down hole samples of polymer which has stayed in the reservoir conditions for a considerable length of time. Accelerated ageing studies in the lab showed HPAM can lose viscosity and precipitate after prolonged exposure to Mangala reservoir conditions with an increase in the degree of hydrolysis as the primary reason for the degradation. The concept of transfer function based on first order kinetics was used to extrapolate the laboratory results to Mangala reservoir temperatures. To test the hypothesis, a multi-disciplinary team implemented a plan to gather a representative polymer sample from the reservoir. The polymer sample had been in the reservoir for nearly 120 days and was captured in low shear and anaerobic conditions to minimize shear and oxidative degradation. The sample was tested for degree of hydrolysis by NMR method. The results confirmed that the level of hydrolysis of the injected HPAM did increase in the reservoir leading to lower viscosity and reduced lower amide concentration. Preliminary simulation studies using the concept of viscosity half-life were used to mimic the polymer degradation with time in the reservoir. The method is quite a simplistic representation of the thermal degradation, but it significantly improved the model's water cut predictions for lower layers and the full field polymer breakthrough predictions. The impact of polymer precipitation in the reservoir on the permeability is under study and it will drive the next phase of more detailed modeling.
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