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Engineering data indicate that reserves of tight sandstone reservoir account for a large proportion of the total reserves in low permeability reservoirs, therefore it is meaningful to work on the tight sandstone reservoir classification. Considering the specialty and various kinds of parameters of the tight sandstone gas field of Xinchang Xu-2 formation in the west part of Sichuan Province, the four parameters, that is, porosity, permeability, flow unit, and shale content are selected as reservoir parameters, and the K-means clustering method is used to divide the formations into five categories. On basis of this, by comparing the accuracy of the discriminant analysis with that of decision tree, the decision tree classification method is used to build the quantitative evaluation of the reservoir model. 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科技导报
|研究论文
2011
, 29
(24) :
47
-50
致密砂岩气藏储层分类新方法
全屏
王礼常, 王志章, 陶果
作者信息
中国石油大学(北京);油气资源与探测国家重点实验室,北京 102249
通讯作者:
王志章,教授,研究方向为油气田开发地质,电子信箱:whx3998@vip.sina.com
A Novel Classification Method for the Tight Sandstone Reservoir
WANG Lichang, WANG Zhizhang, TAO Guo
Affiliations
State Key Laboratory of Petroleum Resources and Processing; China University of Petroleum, Beijing 102249, China
出版时间: 2011-08-28
doi: 10.3981/j.issn.1000-7857.2011.24.006
文章导航
储层分类是油气勘探开发研究的重要内容之一,目前致密砂岩储层在低孔低渗储层占有很大比例,因此研究致密砂岩储层分类具有重要意义.本文结合四川川西新场地区须家河组致密砂岩储层的特点,综合考虑多种参数,选用孔隙度、渗透率、流动带指数a FZI 、泥质含量作为储层特征参数,采用K-means聚类方法将储层分为5大类,并在此基础上,通过对比判别分析和决策树判别准确率,采用决策树方法建立储层分类的定量评价模式.实际资料证明,决策树具有更好的效果,提高了储层分类评价的效果.
Reservoir classification is one of the important parts of the study involving oil and gas exploration and development. Engineering data indicate that reserves of tight sandstone reservoir account for a large proportion of the total reserves in low permeability reservoirs, therefore it is meaningful to work on the tight sandstone reservoir classification. Considering the specialty and various kinds of parameters of the tight sandstone gas field of Xinchang Xu-2 formation in the west part of Sichuan Province, the four parameters, that is, porosity, permeability, flow unit, and shale content are selected as reservoir parameters, and the K-means clustering method is used to divide the formations into five categories. On basis of this, by comparing the accuracy of the discriminant analysis with that of decision tree, the decision tree classification method is used to build the quantitative evaluation of the reservoir model. It is proved by the actual data that decision tree has a better result for enhancing the effect of reservoir classification and evaluation.
reservoir classification and evaluation
/
cluster analysis
/
decision tree
王礼常;王志章;陶果.
致密砂岩气藏储层分类新方法.
科技导报,
2011
, 29
(24)
: 47
-50
.
DOI: 10.3981/j.issn.1000-7857.2011.24.006
WANG Lichang;WANG Zhizhang;TAO Guo.
A Novel Classification Method for the Tight Sandstone Reservoir[J].
Science & Technology Review ,
2011
, 29
(24)
: 47
-50
.
DOI: 10.3981/j.issn.1000-7857.2011.24.006
2011年第29卷第24期
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文章信息
doi: 10.3981/j.issn.1000-7857.2011.24.006
接收时间:2011-03-03
首发时间:2011-08-28
出版时间:2011-08-28
收稿日期:2011-03-03
修回日期:2011-07-15
通讯作者:
王志章,教授,研究方向为油气田开发地质,电子信箱:whx3998@vip.sina.com
https://castjournals.cast.org.cn/joweb/kjdb/CN/10.3981/j.issn.1000-7857.2011.24.006
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2种不同金属材料的力学参数
科 Family 属数 Number of genus 种数 Number of species 占总种数比例 Percentage of total species (%) 属 Genus 种数 Number of species 占总种数比例 Percentage of total species (%) 鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78 小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39 多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39 红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87 小菇属 Mycena 11 5.26 光柄菇属 Pluteus 5 2.39 红菇属 Russula 17 8.13 栓菌属 Trametes 5 2.39
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