Abstract
AbstractAt present, oil companies are committed to applying the theory and means of mathematics or data science to the research of oilfield data rules. However, for some old oil wells, aging equipment, complex environment and backward management, cause the authenticity and accuracy of the data collected by the equipment cannot be determined. According to the actual engineering demand of the old wells, this paper proposes a method based on principal component analysis, cluster analysis and regression analysis to mine and analyze the data of polished rod load of old oil wells, so as to judge the working conditions of the oil wells. Combined with the application of this study in several operation areas of some oilfields, the findings of this study can help for better understanding of the working condition information hidden in "big data" of oilfield. Meanwhile, the PCA method can reduce the complexity of the original data, the regression equation can calculate the size of the polished rod load more accurately, and the prediction model can effectively judge the working conditions of the old oil wells on site.
Funder
Sichuan Youth Science and Technology Foundation
Publisher
Springer Science and Business Media LLC
Subject
General Energy,Geotechnical Engineering and Engineering Geology
Reference24 articles.
1. Canelon MAR, Morles EC (2008) Fuzzy clustering based models applied to petroleum processes[J]. Wseas Trans Syst Control 3:159–171
2. Chaodong T, Jiancheng C, Zhihai L et al (2015) Prospects for the application of big data mining technology in petroleum engineering[J]. China Pet Chem Ind 01:49–51
3. Gibbs SG, Neely AB (1966) Computer diagnosis of down-hole conditions in sucker rod pumping wells,[J]. J Pet Tech 18:91–98
4. He Yanfeng Wu, Xiaodong HG et al (2008) A new method for spectrum analysis of indicator diagrams[J]. Acta Pet Sin 04:619–624
5. Jain A K, Duin R P W, Jianchang Mao (2000) Statistical pattern recognition: a review. Pattren analysis and machine intelligence[J]. IEEE Transactions 22(1): 4–37
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