Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

He, Yun-Peng; Cheng, Hai-Bo; Zeng, Peng; Zang, Chuan-Zhi; Dong, Qing-Wei; Wan, Guang-Xi; Dong, Xiao-Ting

doi:10.1016/j.petsci.2023.08.031

Cited by 7 publications

(1 citation statement)

References 34 publications

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“…Many advanced methods have been applied in diagnostic technology based on fault dynamometer cards, such as the continuous hidden Markov model [8], supervised dictionary-based transfer subspace learning [9], optimized density peak clustering [10], oil-Net 1-D/2-D identification models from time-series and computer vision perspectives [11], four-segment time-frequency signature matrices, and deep learning [12].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Method for Solving the One-Dimensional Wave Equation of Tapered Sucker-Rod Strings

Yin,

2024

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Simulating surface conditions by solving the wave equation of a sucker-rod string is the theoretical basis of a sucker-rod pumping system. To overcome the shortcomings of the conventional finite difference method and analytical solution, this work describes a novel hybrid method that combines the analytical solution with the finite difference method. In this method, an analytical solution of the tapered rod wave equation with a recursive matrix form based on the Fourier series is proposed, a unified pumping condition model is established, a modified finite difference method is given, a hybrid strategy is established, and a convergence calculation method is proposed. Based on two different types of oil wells, the analytical solutions are verified by comparing different methods. The hybrid method is verified by using the finite difference method simulated data and measured oil data. The pumping speed sensitivity and convergence of the hybrid method are studied. The results show that the proposed analytical solution has high accuracy, with a maximum relative error relative to that of the classical finite difference method of 0.062%. The proposed hybrid method has a high simulation accuracy, with a maximum relative area error relative to that of the finite difference method of 0.09% and a maximum relative area error relative to measured data of 1.89%. Even at higher pumping speeds, the hybrid method still has accuracy. The hybrid method in this paper is convergent. The introduction of the finite difference method allows the hybrid method to more easily converge. The novelty of this work is that it combines the advantages of the finite difference method and the analytical solution, and it provides a convergence calculation method to provide guidance for its application. The hybrid method presented in this paper provides an alternative scheme for predicting the behavior of sucker-rod pumping systems and a new approach for solving wave equations with complex boundary conditions.

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