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低渗透河流相储层建模方法与应用——以苏里格气田苏6加密试验区块为例
引用本文:赵勇,李进步,张吉,张清.低渗透河流相储层建模方法与应用——以苏里格气田苏6加密试验区块为例[J].天然气工业,2010,30(7):32-35.
作者姓名:赵勇  李进步  张吉  张清
作者单位:中国石油长庆油田公司苏里格研究中心
摘    要:储层地质模型既是油气藏综合评价的地质基础,也是油气藏数值模拟的必要参数和开发调整方案的直接依据。在综合利用地质、测井和生产动态资料基础上,开展了低渗透河流相储层建模方法的研究。结果认为:细分沉积单元、分相进行储层参数变差函数结构分析能够精细地刻画储层的非均质性;应用相控条件模拟进行井间储层参数的预测,能有效地反映出低渗透储层物性的局部变化;应用储层属性模型,可以直接预测有效储层的规模大小及其空间分布,为气田开发井网的部署和调整提供地质依据。应用低渗透河流相储层建模方法预测的结果得到了生产实际的动态验证,该建模方法为同类气藏储层建模提供了参考。

关 键 词:低渗透油气藏  有效储层  河流相  地质模型  测井  生产动态  鄂尔多斯盆地

Methodology for geologic modeling of low-permeability fluvial sandstone reservoirs and its application:A case study of the Su-6 infilling drilling pilot in the Sulige Gas Field
Zhao Yong , Li Jinbu , Zhang Ji , Zhang Qing.Methodology for geologic modeling of low-permeability fluvial sandstone reservoirs and its application:A case study of the Su-6 infilling drilling pilot in the Sulige Gas Field[J].Natural Gas Industry,2010,30(7):32-35.
Authors:Zhao Yong  Li Jinbu  Zhang Ji  Zhang Qing
Affiliation:Sulige Research Center, Changqing Oilfield Company, PetroChina , Xi’an, Shaanxi 710018, China
Abstract:A reservoir geologic model provides not only the basis for comprehensive evaluation of oil/gas pools, but also the necessary parameters for numerical simulation of reservoirs and direct data for the adjustment of a development plan. Based on an integrated analysis of geologic, logging and production performance data, a study is performed on geologic modeling of fluvial sandstone reservoirs with low permeability. The heterogeneity of reservoirs can be described in detail through subdivision of sedimentary units and structural analysis of variation function of reservoir parameters according to facies. Prediction of inter well reservoir parameters through facies controlled conditional simulation can effectively reflect the local variation of the poroperm characteristics of the low permeability reservoirs. The reservoir attribute model can be directly used to predict the scale and spatial distribution of effective reservoirs, providing a geologic basis for the deployment and adjustment of development well pattern. The prediction results of this model have been verified by the real production performance data, thus this methad can be used to guide the geologic modeling of similar gas reservoirs.
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