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By integrating core test with petrophysics logs data to classify flow units and to built the accurate permeability prediction model for identifying oil and water formation and interpreting the degree of water flooded layers. Putaohua reservoir would be divided into four distinct sub flow units on the principles of the flow unit classification, therefore the relationship between porosity and permeability is significantly improved, and different flow units are identified based on core data and wire-logging. The multiple-statistic equation of the Flow Zone Indicator (FZI) is built up by screening compensation density log, deep induction resistivity log, and middle induction resistivity log which are able to best characterize the accumulation property of reservoir, and an identification model of flow unit is obtained. The porosity permeability models of each flow unit are established by using core analysis data, which obtain effective result in Putaohua reservoir of D404 Block, and permeability prediction accuracy is improved. The workflow methodology could be used in other sandstone formation., authors=SONG Ning1,2, LIU Zhen1, ZHANG Jianfeng3, YANG Shuaishuai1, GUO Haiying1, authorsList=SONG Ning;LIU Zhen;ZHANG Jianfeng;YANG Shuaishuai;GUO Haiying, authorCompany=1. School of Petroleum Engineering, Changzhou University, Changzhou 213016, Jiangsu Province, China;2. Oil and Gas Company, China Huadian Engineering (Group) Co. Ltd., Beijing 100035, China;3. 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基于流动单元分类的非均质砂岩储集层渗透率预测
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宋宁;刘振;张剑风;杨帅帅;郭海莹
科技导报 | 研究论文 2013,31(2): 68-71
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科技导报 | 研究论文 2013, 31(2): 68-71
基于流动单元分类的非均质砂岩储集层渗透率预测
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宋宁;刘振;张剑风;杨帅帅;郭海莹
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Permeability Prediction of Heterogeneous Sand Reservoir Based on Flow Units Classification
SONG Ning;LIU Zhen;ZHANG Jianfeng;YANG Shuaishuai;GUO Haiying
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出版时间: 2013-01-18 doi: 10.3981/j.issn.1000-7857.2013.02.009
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综合岩心分析测试和测井资料,对松辽盆地新站油田D404区块葡萄花油层进行流动单元划分,建立中低孔、中低渗非均质砂岩的渗透率预测模型.首先,将葡萄花油层划分为4个特征明显的流动单元,分类后的孔隙度与渗透率关系明显改善;其次,筛选最能表征储集层储集性能的补偿密度、深感应电阻率和中感应电阻率为变量,建立了流动单元指数FZI的测井响应多元回归方程,为应用测井曲线划分流动单元奠定基础;第三,应用与孔隙度关系最密切的补偿密度测井预测孔隙度;最后,应用基于流动单元分类的孔隙度与渗透率关系,预测非均质储集层渗透率,精度明显提高.研究结果为中低孔中低渗砂岩储集层解决非均质问题提供有效途径.
非均质储集层  /  流动单元指数  /  渗透率预测  /  储集层分类
Putaohua sand reservoir with medium-low porosity and medium-low permeability is heterogeneity in nature at D404 block of Xinzhan oilfield, Songliao Basin. By integrating core test with petrophysics logs data to classify flow units and to built the accurate permeability prediction model for identifying oil and water formation and interpreting the degree of water flooded layers. Putaohua reservoir would be divided into four distinct sub flow units on the principles of the flow unit classification, therefore the relationship between porosity and permeability is significantly improved, and different flow units are identified based on core data and wire-logging. The multiple-statistic equation of the Flow Zone Indicator (FZI) is built up by screening compensation density log, deep induction resistivity log, and middle induction resistivity log which are able to best characterize the accumulation property of reservoir, and an identification model of flow unit is obtained. The porosity permeability models of each flow unit are established by using core analysis data, which obtain effective result in Putaohua reservoir of D404 Block, and permeability prediction accuracy is improved. The workflow methodology could be used in other sandstone formation.
heterogeneous reservoirs  /  flow zone indicator  /  permeability prediction  /  reservoir classification
宋宁;刘振;张剑风;杨帅帅;郭海莹. 基于流动单元分类的非均质砂岩储集层渗透率预测. 科技导报, 2013 , 31 (2) : 68 -71 . DOI: 10.3981/j.issn.1000-7857.2013.02.009
SONG Ning;LIU Zhen;ZHANG Jianfeng;YANG Shuaishuai;GUO Haiying. Permeability Prediction of Heterogeneous Sand Reservoir Based on Flow Units Classification[J]. Science & Technology Review, 2013 , 31 (2) : 68 -71 . DOI: 10.3981/j.issn.1000-7857.2013.02.009
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doi: 10.3981/j.issn.1000-7857.2013.02.009
  • 接收时间:2012-11-05
  • 首发时间:2013-01-18
  • 出版时间:2013-01-18
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  • 收稿日期:2012-11-05
  • 修回日期:2012-12-21
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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