基于聚类分析的石油储层中含油性识别方法

Identification Method of Oil Content in Petroleum Reservoir Based on Cluster Analysis

储层含油性预测是油藏描述的重要内容之一。用聚类分析方法对测井资料进行油气、水层识别的思路。油储层的预测即是在井位处获取测井数据,进行储层含油性识别,从而得到储层在一个井位的精确认识,可以使得识别更加客观,进而得到对储层的完整认识,而选择一个合适的算法进行属性提取,可以提高方法的准确性和高效性。所以本文将重点研究,基于K-Means聚类分析的石油储层中含油性识别。

Reservoir oiliness prediction is one of the important contents of reservoir description. The method of cluster analysis is used to identify oil, gas and water layers from well logging data. The prediction of oil reservoir is to obtain logging data at the well location and identify the oil content of the reservoir, so as to obtain an accurate understanding of the reservoir at a well location, which can make the identification more objective and obtain a complete understanding of the reservoir. In addition, selecting a suitable algorithm for attribute extraction can improve the accuracy and efficiency of the method. Therefore, this paper will focus on the identification of oil content in petroleum reservoirs based on K-Means cluster analysis.