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储层物性的空间结构特征分析与预测——以青海尕斯库勒油田E_3~1油藏为例
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引用本文:潘懋,李铁锋.2001.储层物性的空间结构特征分析与预测——以青海尕斯库勒油田E_3~1油藏为例[J].地质学报,75(1):.
.2001.[J].Acta Geologica Sinica,75(1):.
DOI:
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潘懋  李铁锋
北京大学地质学系 100871 (潘懋)
,北京大学地质学系 100871(李铁锋)
中文摘要:储层物性受诸多地质因素的影响,经常表现出强烈的非均质性。这种非均质性在一定的空间尺度上往往具有明显的结构特点。本文以青海尕斯库勒油田E_3~1油藏为例,讨论了地质统计学方法在油田储层物性空间结构特征分析与预测中的应用。采用变异函数定量描述了孔隙度和渗透率的空间分布结构特征,并在此基础上利用克立格法进行了最优插值预测。结果表明,研究区储层物性(孔隙度和渗透率)具有显著的空间结构性特点,变程一般在800~2000m之间;不同小层的储层物性具有不同的空间结构方向性。这种特征主要受沉积相带空间展布的影响,各小层孔隙度和渗透率的实验半变异函数均可用具有块金效应的球状模型来拟合并进行预测。作为验证,本文还采用“多重趋势面”预测模型对储层的孔隙度和渗透率进行了预测分析。
中文关键词:储层物性,空间结构特征,克立格插值,多重趋势面分析
 
PAN Mao,LI Tiefeng Department of Geology,Peking University,Beijing,100871
Abstract:The physical properties of an oil reservoir is affected by various geologic factors. It is commonly manifested as inhomogeneity, which is usually characterized by a distinct structure on a certain spatial scale. Take for example the early Late Eogene oil deposits in the Gas Hure oil field, Qinghai Province, the paper discusses the application of the geostatistical method in analysing and predicting the spatial structural characteristics of reservoir physical properties. The spatial structural characteristics of porosity and permeability are quantitatively described with variograms. Based on the experimental variograms and fitted theoretic curves, the authors discuss the optimal interpolating prediction by using the Kriging method. The result indicates that the spatial structural distribution of porosity and permeability in the reservoir is distinct. Most of the ranges of the variograms are around 800-2000 m. The characteristics of porosity and permeability distribution in different reservoir layers are distinct from each other. This feature of porosity and permeability for different layers is mainly affected by the spatial distribution of sedimentary facies. The experimental semi variograms of porosity and permeability of each sedimentary layer can be fitted to a spherical model with the mugget effect. Therefore, the numerical values of porosity and permeability among the observation spots can be interpolated and predicted based on the model. To verify the above result, a multiple trend surface analysis model is used to predict the values of porosity and permeability.
keywords:physical property of oil reservoir,spatial structural characteristics,Kriging interpolation,mul-tiple trend surface analysis
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