西南石油大学学报(自然科学版) ›› 1999, Vol. 21 ›› Issue (4): 26-29.DOI: 10.3863/j.issn.1000-2634.1999.04.008

• 油气藏工程 • 上一篇    下一篇

获得精细数值模拟流动参数的新方法—微观网络模拟

胡雪涛1 李允2   

  1. 1.西南石油学院石油工程系,四川南充637001; 2.西南石油学院
  • 收稿日期:1999-05-09 修回日期:1900-01-01 出版日期:1999-11-20 发布日期:1999-11-20
  • 通讯作者: 胡雪涛

A NEW APPROACH TO GAIN FLOWING PARAMETERS OF FINE RESERVOIR NUMERICAL SIMULATION—MICRO NETWORK SIMULATION

HU Xue-tao LI Yun   

  1. Southwest Petroleum Inst
  • Received:1999-05-09 Revised:1900-01-01 Online:1999-11-20 Published:1999-11-20
  • Contact: HU Xue-tao

摘要: 为了解决油藏精细数值模拟的网格流动参数难题,依据地质事件的层次性和结构性特征,将宏观问题的求解转化成对微观对象的研究,应用微观随机网络模拟方法获得了精细数值模拟的网络流动参数;并应用定向渗流理论建立了随机网络模型,方便、灵活地构造出岩石各种类型的孔隙结构特征和润湿性特征,较好地表征多孔介质的微观静态特性;快速、有效地模拟不同静态特征岩石的微观流动参数。通过实例证实微观网络模拟是精细数值模拟获得小规模流动参数的有效方法。
   

关键词: 微观, 网络模型, 随机模拟, 流动系数

Abstract:

It is the key and also very difficult point to gain flowing parameters of fine reservoir simulation. Based on the hierarchy and textural feature of geological events, stochastic simulation in micro networks is used in this article to acquire the flowing parameters by transforming macro phenomena into a study in micro- mechanism. In the paper, stochastic network model built with oriented percolation is flexible and convenient. Different kinds of pore structures and wettability of sand rock can be easily structured using the stochastic network model. The model can truly present the micro-character of porous media, and it can also be used to simulation flowing parameters quickly and effectively. It has been proved with case study that stochastic simulation in networks is an effective new approach to gain flowing parameter of small dimensions in fine reservoir simulation.

Key words: microcosmic, network model, stochastic simulation, and flowing parameter

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