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基于成岩储集相分类的致密储层孔隙度建模
引用本文:周游,景成,李治平,张志营.基于成岩储集相分类的致密储层孔隙度建模[J].测井技术,2018(2):175-180.
作者姓名:周游  景成  李治平  张志营
作者单位:中国地质大学(北京)能源学院,北京100083;非常规天然气能源地质评价与开发工程北京市重点实验室,北京100083 西安石油大学石油工程学院,陕西西安,710000 中国石化东北石油局,吉林长春,130000
基金项目:国家科技重大专项课题致密油气藏数值模拟新方法与开发设计(2017ZX05009005),2014年度中央在京高校重大成果转化项目(ZDZH20141141501)
摘    要:致密气储层非均质性极强,孔隙度参数难以利用统一模型准确表征。分析各类成岩储集相的分类评价体系及其对孔隙度变化的主控作用,基于成岩储集相分类确定致密气储层孔隙度。利用分类成岩储集相测井响应特征的匹配关系,建立灰色理论成岩储集相测井多参数定量评价方法和分类成岩储集相储层的孔隙度测井解释模型。建模过程中因各参数对孔隙度进行拟合都具有其合理性,故利用分类模型的偏差度、离散度和相关度多参数联合求取孔隙度,并用实例分析孔隙度计算模型的有效性。结果表明,分类模型中数据点具有相对集中的分布趋势及较为明显的线性关系,为准确建立致密储层参数模型提供了有效方法。

关 键 词:致密气储层  成岩储集相  测井响应  孔隙度  解释模型  联合求取  tight  gas  reservoir  diagenetic  reservoir  facies  logging  response  porosity  evaluation  model  combined  calculation

Porosity Modeling of Tight Reservoir Based on Diagenetic Reservoir Facies Classification
ZHOU You,JING Cheng,LI Zhiping,ZHANG Zhiying.Porosity Modeling of Tight Reservoir Based on Diagenetic Reservoir Facies Classification[J].Well Logging Technology,2018(2):175-180.
Authors:ZHOU You  JING Cheng  LI Zhiping  ZHANG Zhiying
Abstract:It is difficult to accurately evaluate physical parameters such as porosity with a unified model for tight gas reservoir which characterized by strong heterogeneity.To solve this problem, the classification evaluation system of various diagenetic reservoir facies and their dominant role in the change of porosity have been analyzed.Based on the diagenetic reservoir facies classification, the porosity of tight gas reservoirs is determined.Using the matching relation of logging response of the classified diagenetic reservoirs facies,a multi-parameter logging quantitative evaluation method based on grey theory is established for diagenetic reservoirs facies,as well as a porosity logging evaluation model for reservoirs of classified diagenetic reservoirs facies.Because various logging curves have a certain degree of response to porosity,multiple parameters such as deviation degree, dispersion, and correlation of the classification model are used to comprehensively determine the porosity.Applying this model to the actual data processing to verify its effect.It is found that the data points in the classification model have a relatively concentrated distribution trend and a relatively obvious linear relationship, w hich means reasonableness of the model and can be used to evaluate physical parameters of the tight gas res-ervoirs.
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