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E3^1油藏为例，讨论了地质统计学方法在油田储层特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成插值预测。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。
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.
出处
《地质学报》
EI
CAS
CSCD
北大核心
2001年第1期121-126,共6页
Acta Geologica Sinica
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
孔隙度
渗透率
石油地质
physical property of oil reservoir
spatial structural characteristics
Kriging interpolation
mul-tiple trend surface analysis
