首页> 外文学位 >New strategic method to tune equation-of-state to match experimental data for compositional simulation.
【24h】

New strategic method to tune equation-of-state to match experimental data for compositional simulation.

机译:调整状态方程以匹配实验数据以进行成分模拟的新策略方法。

获取原文
获取原文并翻译 | 示例

摘要

Since the plus fraction of reservoir fluids has some uncertainty in its molecular weight and critical properties, equation-of-state, EOS, are generally not predictive without tuning its parameters to match experimental data. Tuning of the EOS is found to be the best method for improving the predictions of compositional reservoir simulators.; The proposed strategy for tuning EOS consists of seven steps: (1) split the laboratory plus fraction to single carbon number groups, SCN, usually up to SCN 44; the last component will be C45+, (2) use set of correlations to calculate the critical properties and acentric factor for each SCN group, (3) match the saturation pressure at reservoir temperature by altering the measured value of the molecular weight of the plus fraction using the extended composition, (4) group SCN groups to multiple carbon number groups, MCN, (5) assign critical properties and acentric factor for each MCN group, (6) rematch the saturation pressure at reservoir temperature using the grouped composition, and (7) match the volumetric data by regressing on volume shift parameters of all components in grouped composition.; This research shows an accurate method to split the plus fraction to SCN groups. The most accurate set of correlations to calculate the critical properties and acentric factor for each SCN group that will result in a small adjustment for the molecular weight of the plus fraction when saturation pressure is matched using the extended composition. The proposed strategy groups the extended composition to eight pseudocomponents. The binary interaction coefficients between hydrocarbons and between hydrocarbons and non-hydrocarbons are set to zero which dramatically reduces the simulation time.; The strategy proposed in this research for tuning EOS to match experimental data has been tested for a wide range of C7+ mole% (4--25) which covers gas condensate and volatile oil samples. Also, using this strategy to tune EOS at reservoir temperature will accurately predict the fluid properties at separator conditions and saturation pressures at different temperatures.; The scope of this research is to come up with an accurate and systematic technique for tuning an EOS for use in compositional simulation.
机译:由于储层流体的正馏分在分子量和临界性质方面存在一定的不确定性,因此如果不调整参数以匹配实验数据,状态方程EOS通常是无法预测的。 EOS的调整被认为是改善成分储层模拟器预测的最佳方法。提议的EOS调整策略包括七个步骤:(1)将实验室加馏分分成单个碳数组SCN,通常不超过SCN 44;最后一个成分将是C45 +,(2)使用一组相关性来计算每个SCN组的临界特性和偏心因子,(3)通过更改正馏分分子量的测量值来匹配储层温度下的饱和压力。使用扩展的成分,(4)将SCN组分配到多个碳原子数组,MCN,(5)为每个MCN组分配关键性质和无心因子,(6)使用分组的成分重新匹配储层温度下的饱和压力,和( 7)通过对分组组成中所有组件的体积偏移参数进行回归来匹配体积数据。这项研究显示了将正分数拆分为SCN组的准确方法。计算每个SCN组的关键特性和无心因数的最准确的一组相关关系,当使用扩展的组成匹配饱和压力时,将导致正馏分的分子量小调整。所提出的策略将扩展组成分为八个伪组件。碳氢化合物之间以及碳氢化合物和非碳氢化合物之间的二元相互作用系数设置为零,这极大地减少了模拟时间。本研究中提出的调整EOS使其与实验数据匹配的策略已针对多种C7 +摩尔%(4--25)进行了测试,涵盖了气体凝析油和挥发油样品。同样,使用这种策略在储层温度下调整EOS可以准确预测分离器条件下的流体性质和不同温度下的饱和压力。本研究的范围是提出一种精确且系统的技术来调整EOS以用于成分模拟。

著录项

  • 作者

    Al-Meshari, Ali Abdallah.;

  • 作者单位

    Texas A&M University.;

  • 授予单位 Texas A&M University.;
  • 学科 Engineering Petroleum.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 248 p.
  • 总页数 248
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 石油、天然气工业;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号