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Microbial Enhanced Oil Recovery - Modeling and Numerical Simulations

机译:微生物强化采油-建模和数值模拟

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摘要

This thesis examines the process by which microbes are used to enhance oil recovery from subsurface reservoirs. A brief introduction to reservoirs is given and the possible effects of microbes are explained. A model is developed combining porous media flow and microbial kinetics. The model is then used to run simulations in conjunction with the MATLAB Reservoir Simulation Toolbox from SINTEF (Stiftelsen for Industriell og Teknisk Forskning). Microbial enhanced oil recovery (MEOR) is simulated by injecting a microbe and nutrient mix into the reservoir. The microbes consume the nutrients and then reproduce and create metabolites according to the Monod model of bacteria. The metabolites are simulated to be either surfactant or polymer which are both beneficial to oil recovery. Surfactant reduces the residual oil level while polymer increases the volumetric sweep of the reservoir. Langmuir equilibrium adsorption is used to model the formation of biofilm. This results in more metabolites being produced nearer the injection sites. An attempt to recreate the results of Nielsen et al. (2010) and Lacerda et al. (2012) is made. Differences in the results are highlighted and explained. Further testing is done to examine the impact of a high permeability thief zone to the model. The thesis concludes that the model and its implementation have been successful so far though more testing should be done.
机译:本文探讨了使用微生物增强地下储层采油的过程。简要介绍了水库,并解释了微生物的可能作用。建立了结合多孔介质流动和微生物动力学的模型。然后,该模型与SINTEF(用于Industriell og Teknisk Forskning的Stiftelsen)的MATLAB Reservoir Simulation Toolbox一起用于运行仿真。通过向储层中注入微生物和营养混合物来模拟微生物提高的采油量(MEOR)。根据细菌的莫诺德模型,微生物消耗了营养,然后繁殖并产生代谢产物。代谢物被模拟为表面活性剂或聚合物,都有利于采油。表面活性剂减少了残余油位,而聚合物增加了储层的体积扫描。 Langmuir平衡吸附用于模拟生物膜的形成。这导致在注射部位附近产生更多的代谢产物。试图重现Nielsen等人的结果。 (2010)和Lacerda等。 (2012年)。结果的差异将突出显示并说明。进行了进一步的测试,以检查高渗透率窃贼带对模型的影响。论文的结论是,尽管需要做更多的测试,但是该模型及其实现已经成功。

著录项

  • 作者

    Amundsen Aleksander;

  • 作者单位
  • 年度 2015
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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