Novel physical network algorithm for indirect measurement of polished rod load of beam‐pumping unit

Wang, Ke; Gong, Guoliang; Shen, Rongxuan; Wang, An; Yao, Zhaolin; Mao, Wenyu; Lu, Huaxiang

doi:10.1049/joe.2018.5435

J. eng.

2019

DOI: 10.1049/joe.2018.5435

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Novel physical network algorithm for indirect measurement of polished rod load of beam‐pumping unit

Ke Wang

Guoliang Gong

Rongxuan Shen

et al.

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Cited by 3 publications

References 24 publications

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Improving the Estimation of a Sucker Rod Pumping Dynamometer Card Based on the Terminal Quantities of the Driving Motor

Silva,

Cerqueira,

Oliveira

et al. 2023

IEEE Access

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Rod pumping systems typically require the analysis of dynamometer cards for fault diagnosis. While external instrumentation assists in obtaining these cards, it simultaneously raises monitoring costs and complexity. To address this issue, this paper introduces a parameter estimator that integrates the equivalent circuit model of an induction motor with the beam pumping unit model. We have compared the performance of two practical estimators, utilizing the terminal quantities of the driving motor as inputs. The results demonstrate surface dynamometer cards under varying operational conditions of the oil well. By augmenting the estimator's input variables, the estimated cards align more closely with the actual ones. This practical application proposes an alternative method for acquiring the surface dynamometer card, which can function as a supplementary approach in fault diagnostics and contribute to informed maintenance decisions for the pumping unit.

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Improving the Estimation of a Sucker Rod Pumping Dynamometer Card Based on the Terminal Quantities of the Driving Motor

Silva,

Cerqueira,

Oliveira

et al. 2023

IEEE Access

View full text Add to dashboard Cite

show abstract

A Novel Hybrid Method for Indirect Measurement Dynamometer Card Using Measured Motor Power in Sucker Rod Pumping System

et al. 2022

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Neural Network-Based Beam Pumper Model Optimization

Dehua

et al. 2022

Computational Intelligence and Neuroscience

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Beam pumper is the earliest and most popular rod pumper driven by surface dynamic transmission devices. Drawing on modern theories and methods of industrial model design, the model optimization of beam pumper could promote the diversity, serialization, standardization, generalization, precision balance, and energy reduction of beam pumper design. Therefore, this study tries to optimize the model of beam pumper based on a neural network. Specifically, the system efficiency of beam pumper was decomposed, the surface and downhole working efficiencies were analyzed, and the model optimization flow was explained for beam pumper. Then, a radial basis function (RBF) neural network was established and trained by the sample data on beam pumper model. Besides, the mapping between model parameters and the optimization objective (system efficiency) was constructed. Moreover, the authors summed up the model optimization contents of beam pumper and predicted the relevant parameters of model optimization. The results demonstrate the effectiveness of our model.

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Novel physical network algorithm for indirect measurement of polished rod load of beam‐pumping unit

Cited by 3 publications

References 24 publications

Improving the Estimation of a Sucker Rod Pumping Dynamometer Card Based on the Terminal Quantities of the Driving Motor

Improving the Estimation of a Sucker Rod Pumping Dynamometer Card Based on the Terminal Quantities of the Driving Motor

A Novel Hybrid Method for Indirect Measurement Dynamometer Card Using Measured Motor Power in Sucker Rod Pumping System

Neural Network-Based Beam Pumper Model Optimization

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