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油气层解释评价技术建模方法研究与实践 被引量:3

Study and practice of the method for setting up the model of oil and gas reservoir interpretation and evaluation.
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摘要 气测录井解释评价方法多种多样,然而对不同地区、不同油气层的解释结果不尽相同,究其原因是不同解释方法具有地区适应性问题,也就是说方法形成的基础条件具有地域性的特点,寻找一种建立适用于任何区域解释评价方法的途径已引起人们的关注。针对此问题,从统计学的角度出发,以准噶尔盆地克拉美丽气田为例,在分析不同天然气烃组分特征的基础上,以C_1/∑C_(1-5_和C_3/∑C_(1-5)两个突出反映烃组分关系特征的比值为分析对象并作为聚类中心,探讨了采用统计学中的模糊C均值聚类算法(FCM)建立以这两项比值为横、纵坐标的气测录井解释评价模型的数学分析方法。该数学分析方法适用于任何地域解释评价模型的建立,应用该方法所建立的解释评价图板在准噶尔盆地克拉美丽气田的初步应用中取得了较理想的效果。 There are various gas logging interpretation and evaluation methods,but for different areas and different oil and gas reservoirs,the interpretation results are different,the reason is that the different interpretation methods have their own regional adaptability,that is,the basic conditions of forming these methods have the regional features,and how to seek a way to set up interpretation and evaluation methods which are suitable for any regions has brought to technician's attention.In view of this problem,from the point of the view of statistics,taking Kelameili gas field of Junggar basin as an example,on the basis of analyzing the features of different natural gas hydrocarbon component,taking the ratios of C_1/∑C_(1-5) and C_3/∑C_(1-5) which can outstandingly reflect relationship features of hydrocarbon component as the analytical objects and clustering center,the paper discussed a mathematical analysis method,which adopted Fuzzy C Mean(FCM) clust algorithm of statistics to set up gas logging interpretation and evaluation model with the two ratios as the abscissa and ordinate respectively. This mathematic analysis method is suitable for any regional interpretation and evaluation model establishment.The initial application of the interpretation and evaluation chart which was established with this method in Kelameili gas field of Junggar basin,has obtained the ideal results.
出处 《录井工程》 2009年第2期34-36,共3页 Mud Logging Engineering
关键词 解释评价 气测录井 聚类分析 聚类算法 聚类中心 隶属度 建模方法 interpretation and evaluation gas logging cluster analysis cluster algorithm cluster center grade of membership modeling method
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