[1]章雨,李少华,李俊仪,等.环江油田长6储层基于多元回归分析的产能评价[J].油气井测试,2019,28(02):68-72.[doi:10.19680/j.cnki.1004-4388.2019.02.012]
　ZHANG Yu,LI Shaohua,LI Junyi,et al.Productivity evaluation of Chang 6 formation in Huanjiang Oilfield based on multivariate regression analysis[J].Well Testing,2019,28(02):68-72.[doi:10.19680/j.cnki.1004-4388.2019.02.012]
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环江油田长6储层基于多元回归分析的产能评价()
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《油气井测试》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2019年02期
页码:
68-72
栏目:
出版日期:
2019-04-25

文章信息/Info

Title:

Productivity evaluation of Chang 6 formation in Huanjiang Oilfield based on multivariate 

regression analysis

文章编号:
1004-4388(2019)02-0068-05
作者:
章雨1; 2; 李少华2; 李俊仪2; 陈彤伟2; 杨定贵2; 陈威2
1.北京大学地球与空间科学学院 北京 100871
2.长江大学地球科学学院 湖北武汉 430100
Author(s):
ZHANG Yu 1; 2;  LI Shaohua 2;  LI Junyi 2;  CHEN Tongwei 2;  YANG Dinggui 2;  CHEN Wei 2
1. School of Earth and Space Sciences, Peking University, Beijing 100871, China
2. School of Geosciences, Yangtze University, Wuhan Hubei 430100, China
关键词:
环江油田;  产能预测;  多元回归分析;  低孔低渗油藏;  储层非均质性;  相关系数;  定量评价
Keywords:

Huanjiang Oilfield;  productivity prediction;  multiple regression analysis;  low porosity and

permeability reservoir;  heterogeneity of reservoir;  correlation coefficient;  quantitative evaluation

分类号:
TE353
DOI:
10.19680/j.cnki.1004-4388.2019.02.012
文献标志码:
B
摘要:

环江油田长6储层具有低孔隙度、特低-超低渗透率的特征，非均质性强，产能预测难度大。利用研究区内11口井

的测井资料，对有效层段的测井解释孔隙度、渗透率及含油饱和度进行多种方法的平均化处理，筛选出最大值，分析单井日产量与各测井参数的相关关系，引入表征储

层非均质性的定量评价参数进行回归分析，建立了多元线性回归的产能预测模型。结果表明，利用孔隙度、渗透率、含油饱和度的最大值，以及有效厚度、突进系数、

变异系数、级差，多参数组合与单井日产量进行回归分析得到的相关性最好，复相关系数0970。建立的回归公式对新井的产能具有很好的预测效果，为油田产能评价

提供依据。

Abstract:

The reservoirs in Chang 6 Formation of Huanjiang Oilfield have the characteristics

of low porosity, extra and ultralow permeability, and strong heterogeneity, which lead to the difficult prediction of production capacity. The

well logging data of 11 wells in the study area were used to average the porosity, permeability and oil saturation of the effective interval, and

the maximum value of them were selected. In addition, the correlation between daily production of single well and various logging parameters was

analyzed, and quantitative evaluation parameters for reservoir heterogeneity were introduced for regression analysis. Based on these works, a

productivity prediction model for multiple linear regression was established. The results showed that the combination of porosity, permeability,

maximum oil saturation, effective thickness, penetration coefficient, coefficient of variation, and gradation has the best correlation with the

daily production of single well, and the multiple correlation coefficient factor reached to 0970. The established regression formula has a good

prediction effect on the productivity of new wells and provides a basis for the productivity evaluation of oilfields.

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备注/Memo

备注/Memo:

 2018-10-21 收稿, 2019-01-31 修回, 2019-02-15 接受, 2019-04-20 网络版发表
湖北省自然科学基金创新群体项目“储层精细表征与建模”（2016CFA024）、大学生创新项目

“产能评价方法研究——以环江油田为例”（2015011）

章雨，男，1995年出生，北京大学地质系在读硕士研究生，研究方向为含油气盆地分析。电

话:18062441948；Email：2892122872@qq.com。通信地址：北京市海淀区颐和园路5号北京大学，邮政编码：100871。


 

更新日期/Last Update: 2019-04-30