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基于储层分类的低孔隙度低渗透率储层产能预测方法研究
引用本文:张占松,张超谟,郭海敏.基于储层分类的低孔隙度低渗透率储层产能预测方法研究[J].测井技术,2011,35(5):482-486.
作者姓名:张占松  张超谟  郭海敏
作者单位:长江大学油气资源与勘探技术教育部重点实验室,湖北 荆州,434023
基金项目:国家863项目06Z2课题“研究特殊储层测井识别与地层参数定量评估计算(编号:2006AA06Z220)”;中国石油天然气集团公司项目“三低油气层测井解释方法和解释模型研究(编号:06A30102)”资助
摘    要:利用研究区内22块压汞样品及4440块有效物性分析样品,建立起低孔隙度低渗透率储层的分类标准,为基于测井数据进行储层分类提供参考依据与标准.依据标准对253个储层进行了类别划分,优选了用于储层类别划分的测井特征参数,建立了3类储层特征参数分布范围及均值.借助自适应BP神经网络技术建立了适合研究区长63段的储层分类判别模...

关 键 词:测井解释  低渗透率储层  储层分类  产能预测  储层指数

On Productivity Prediction of Low Porosity and Permeability Reservoirs Based on Reservoirs Classification
ZHANG Zhansong,ZHANG Chaomo,GUO Haimin.On Productivity Prediction of Low Porosity and Permeability Reservoirs Based on Reservoirs Classification[J].Well Logging Technology,2011,35(5):482-486.
Authors:ZHANG Zhansong  ZHANG Chaomo  GUO Haimin
Affiliation:(Key Laboratory of Exploration Technologies for Oil and Gas Resources,Ministry of Education, Yangtze University,Jingzhou,Hubei 434023,China)
Abstract:Based on 22 mercury injection samples and 4 440 effective physical properties analysis samples,established is a classification standard of low porosity and permeability reservoirs.This is the classification standard based on log data.According to this classification standard,the 253 reservoirs are classified,the log characteristic parameters of reservoirs classification are selected, the range and the average value of the parameters on 3 types of reservoirs are established.Meanwhile self-adapted neural networks technology is used to establish reservoir classification model in Chang 63 block,and its results are close to the comprehensive analysis results.Through analyzing the relation between the reservoirs index and productivity of hydrocarbon reservoirs,there is a well correlation between the reservoirs index and the productivity.This model of productivity prediction based on reservoirs classification has been successfully applied to Chang 63 block, Baibao area.
Keywords:log interpretation  low permeability reservoir  reservoir classification  productivity prediction  reservoir index
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