摘要
桩23北区储层低孔、低渗,自然投产效果差,需进行高效压裂改造提高产能。从储层和施工参数两个方面确定了影响该区压裂改造效果的影响因素和影响因素的关联度及权重。采用灰色关联模糊层次分析法评价影响因素,进一步明确了影响该区块改造效果的主控因素。研究结果表明:影响该区块储层改造效果的主控因素为支撑剂和压裂液总量;灰色关联模糊层次分析法能对该区10口井储层改造效果进行预测分析,偏差率在10%以内。灰色关联模糊层次分析法对桩23北区储层改造参数预测和后期投产具有一定的指导意义。
The reservoir in the north of zhuang 23 has the characteristics of low porosity and low permeability,and the natural production effect is poor.It is necessary to improve the production capacity through fracturing transformation.In order to achieve efficient transformation,it is necessary to analyze and study the factors affecting the transformation.Under the premise of analyzing the fracturing and transformation well in this area,the correlation and weight of the influencing factors and influencing factors affecting the effect of fracturing transformation in this area are determined from two aspects:reservoir and construction parameters.The gray correlation fuzzy hierarchy analysis method is used to evaluate the influencing factors,and further clarify the main control factors affecting the transformation effect of the block.The research results show that:The main control factor affecting the transformation effect of the reservoir in this block is the total amount of support agent and fracturing fluid;The gray correlation fuzzy hierarchy analysis method can predict and analyze the transformation effect of the reservoir in this area,and there is a good linear correlation between the two.The conclusion is that the gray correlation fuzzy hierarchy analysis method has certain guiding significance for the prediction of reservoir transformation parameters in the north area of zhuang 23 and the later production.
作者
王坤杰
WANG Kunjie(Downhole Operation Branch,Southwest Petroleum Engineering Co.,Ltd.,Sinopec,Deyang,Sichuan 618000,China)
出处
《油气井测试》
2023年第6期29-33,共5页
Well Testing
关键词
桩23北区
灰色关联
储层改造效果
模糊层次分析法
高效压裂
影响因素
低孔低渗
预测分析
North area of zhuang 23
grey correlation
reservoir transformation effect
fuzzy hierarchy process
high-efficiency fracturing
influencing factors
low porosity and low permeability
predictive analysis
