| 多物源条件下的储层地质建模方法 |
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| 引用本文： | 李少华,张昌民,尹艳树,尹太举,严申斌.多物源条件下的储层地质建模方法[J].地学前缘,2008,15(1):196-201. |
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| 作者姓名： | 李少华 张昌民 尹艳树 尹太举 严申斌 |
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| 作者单位： | 长江大学,地球科学学院,剩余资源研究组,湖北,荆州,434023 |
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| 基金项目： | 国家重点基础研究发展计划(973计划)
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湖北省教育厅青年基金 |
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| 摘 要： | 濮城沙三中油藏具有两个主物源,分别为NE向与SE向。油藏数值模拟需要在一套地质网格中对其进行模拟。经典的地质统计学利用变差函数描述区域化变量的空间几何结构特性。变差函数的计算是基于两点进行统计的,对其描述主要涉及方位角、变程、块金值和基台值。为了在一套模拟网格中模拟出多个物源条件下储层的分布特征,必须在不同的位置设置不同的变差函数参数。文中给出了两种方法实现这一目的:一是采用人为分区,把不同物源影响的区域分成不同的区块,分别对不同的区块设置不同的变差函数参数;二是采用变方位角,即根据不同的位置设置不同的变差函数方位角。这两种方法都实现了在一套网格中模拟具有多个物源方向的储层分布,更真实地再现了储层的空间展布特征。
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| 关 键 词： | 多物源 储层 随机建模 地质统计学 |
| 文章编号： | 1005-2321（2008）01-0196-06 |
| 收稿时间： | 2007-11-20 |
| 修稿时间： | 2007-12-13 |
Stochastic modeling of reservoir with multi-source |
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| Li Shaohua,Zhang Changmin,Yin Yanshu,Yin Taiju,Yan Shenbin.Stochastic modeling of reservoir with multi-source[J].Earth Science Frontiers,2008,15(1):196-201. |
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| Authors: | Li Shaohua Zhang Changmin Yin Yanshu Yin Taiju Yan Shenbin |
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| Abstract: | There are two major sedimentary sources in the Es3^M reservoir of the Pucheng oilfield. One sedimentary source is from the northeast, and the other is from the southeast. The reservoir simulation needs a whole grid for the Es3^M reservoir. The variogram is the most common tool used to measure the spatial correlation for the cell-based facies modeling, and the porosity and permeability modeling. The calculation of variogram is based on two point statistics. It is characterized by azimuth, range, nugget and sill. We should give different varlogram parameters in different areas in order to model the reservoir distribution controlled by multi-source. Two methods are applied to fulfilling this purpose. First method is to divide the research area into several segments artificially according to the area controlled by different sedimentary sources, and then different variogram parameters are set for each segment by using the function of grid filter. The second method is to adopt local varying azimuth. In this way, the reservoir with multi-source can be modeled in a single modeling grid system. The result shows that these two methods are better than the traditional SIS method in characterizing reservoir distribution with multi-source. |
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| Keywords: | multi-source reservoir stochastic modeling geostatistics |
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