Diagnosis of Sucker Rod Pump based on generating dynamometer cards. (May 2019)

• Record Type: Journal Article
• Authors: Zheng, Boyuan; Gao, Xianwen; Li, Xiangyu
• Is Part Of: Journal of process control. Volume 77(2019)
• Page Start: 76
• Page End: 88
• Publication Date: 2019-05
• Subjects: Diagnosis -- Generated dynamometer card -- Dynamic analysis of pump pressure -- Hidden Markov Models -- Sucker Rod Pump; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2019.02.008
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: The paper detailedly analyzes the working mechanism of sucker rod pumping. A novel method is proposed for generating dynamometer cards based on the mechanism of sucker rod pumping. Beside of normal working state, dynamometer cards in the five faulty working states are also generated. The hidden Markov model is applied in the diagnosis of sucker rod pumping. Actual production data is adopted to testify the feasibility of the proposed method. Abstract: The dynamometer cards (DC) are the data shown as closed curves collected from Sucker Rod Pumps, which are essential evidence to monitor the working states in modern oil are engineering. To meet the actual needs of oil fields, recently, the computer-aided diagnosis techniques are becoming useful measurements to help engineers monitoring the wells. Nevertheless, how to collect the various kinds of fault data from a well is always a puzzle for the application of the computer-aided methods, because of a well hardly experiences many types of faulty working states. The typical solution for this problem is building an album containing DCs collected from different wells, but this approach neglects the property differences between wells, which may influence the diagnosis accuracy. In order to address this tough issue, in this paper, a novel approach regarding generating DCs is proposed based on the analysis of the mechanism of a sucker rod pump (SRP) at normal and several faulty scenarios. This method could use the productive parameters and operation rules of a well to calculate the DCs at different working states based on dynamic mechanism analysis. Subsequently, according to the data support of generating DCs, the Hidden Markov Models under a specifically designed framework is used to build the relationships between DCs and working states. At last, the proposed method is verified experimentally through the productive parameters of many wells collected from an oilfield, and then some conventional techniques are employed in the comparison studies. The obtained results demonstrate the effectiveness of the proposed method for diagnosing the working states of Sucker Rod Pumps.