西南石油大学学报(自然科学版) ›› 1988, Vol. 10 ›› Issue (4): 74-85.DOI: 10.3863/j.issn.1000-2634.1988.04.008

• 论文 • 上一篇    下一篇

毛管压力曲线分布特征的确定

罗明高   

  1. 新疆石油管理局勘探开发研究院
  • 收稿日期:1988-06-05 修回日期:1900-01-01 出版日期:1988-11-20 发布日期:1988-11-20

DETERMINATION OF THE DISTRIBUTION TYPES OF CAPILLARY PRESSURE CURVES

Luo Ming-gao
  

  1. Research Institute of Petroleum Exploration and Development; Xinjiang Petroleum Administration
  • Received:1988-06-05 Revised:1900-01-01 Online:1988-11-20 Published:1988-11-20

摘要:

本文严格建立了常见的几种不同毛管压力曲线分布在统一座标系下的分布特征,从而使目前在毛管压力中存在的各种不同分布能在同一座标系下进行判断。分布类型的确定,重点在于对结果的检验,这有利于避免结果的多解性和人为性的影响。文章通过对正态分布几个公式的意义进行数学描述,用x~2分布的数值代入进行计算的结果,进一步阐明正态分布的标准曲线与实际曲线的差异对结果参数的影响,因此,仅用概率论方法进行假设检验还不够,必须用统计学参数进行检验;仅用曲线的特征参数不能正确判断曲线的分布特征,必须用实际曲线与标准曲线的拟合法才能确定。在此还解释了经常遇到的统计学参数(用矩法求得的结果)与正态分布法结果不同的现象。

关键词: 毛细管压力, 曲线, 分布特征, 正态分布, 分布

Abstract:

Several usual distribution types of capillary pressure curves have been strictly established in the same coordinate system Thereby, different distributions of usual types of capillary pressure curves can be distinguished in the same coordinate system. The key point in determining the distribution of capillary pressure curves is to test the results, in this way, the results cannot be influenced by the personal factor, and multiple answers can be avoided The calculation formulae from normal distribution have been described mathematically.The calculation results have been obtained by using (chi)distribution data.The influence of the difference between typical curves and actual curves upon the results obtained by the normal distribution method is expounded in this paper.The results must be tested by statistical parameters besides hypothesis testing by probability.The bistribution of the curve can be determined correctly not simply by using statistical character parametrs,but by using typical curves fitting actual curves (or data points). The usual difference between the results of the statistical method (momentmethod) and those of normal distribution is also explained here.

Key words: Capillary pressure, Curve, Distribution characteristics, Normal distribution, X~2 distribution