利用系统对不同储层细菌总数的影响分析与预测

I. Radojević, A. Ostojić, N. Stefanović
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引用次数: 0

摘要

本研究使用SeLaR信息系统(IS)进行。SeLaR IS结合了塞尔维亚油藏的相关数据,采用了统计分析和数据挖掘等先进的分析方法。为了进行数据分析,我们选择了三个具有不同形态特征、营养状况和优势微生物群落的群落:Gruža、Grošnica和Bovan。本研究的材料是数据集,包括某些时期淡水的标准常规和更广泛的科学水文生物学测试。数据包括物理化学、生物化学、微生物学和其他生物学参数。分析的目的是确定实体之间的关系,发现未知的关系,特定特征的动态规律,并进行预测。采用分类、影响参数分析、情景分析等方法进行分析。结果表明细菌总数的值有明确的分类。所获得的模型具有少量有影响的参数(1到4个),对每个类别分别具有较大的相对影响。不同累积的影响参数是不同的。对于细菌总数的预测,所选择的工具对所有三个储层都不能提供令人满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IMPACT ANALYSIS AND PREDICTION OF THE TOTAL NUMBER OF BACTERIA IN DIFFERENT RESERVOIRS USING SELAR INFORMATION SYSTEM
This study was performed using the SeLaR information system (IS). SeLaR IS combines relevant data on reservoirs in Serbia and enables advanced methods of analysis, such as statistical analysis and data mining. For the data analysis, three accumulations with different morphometric properties, trophic status, and dominant community of microorganisms were selected: Gruža, Grošnica, and Bovan. The material in this research is data sets that include standard routine and broader scientific hydrobiological tests of freshwater from certain periods. The data include physicochemical, biochemical, microbiological, and other biological parameters. The analysis aimed to determine the relationship between the entities, to discover unknown relations, the regularity in the dynamics of the specific characteristics, and for predictions. Classification, analysis of influential parameters, and scenario analysis were used for this analysis. The results indicate a clear classification of the values of the total number of bacteria. The obtained models have a small number of influential parameters (one to four) with a large relative impact for each class separately. Influence parameters are different for distinct accumulations. For prediction of the total number of bacteria selected tools did not provide satisfactory results for all three reservoirs.
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