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Petroleum Science 2022年第2期19卷 743-760页

作者： Xiao-Xiao Lv Han-Xiang Wang Zhang Xin Yan-Xin Liu Peng-Cheng Zhao College of Mechanical and Electrical Engineering China University of PetroleumQingdao266580China

A highly precise and timely diagnosis technology can help effectively monitor and adjust the sucker rod production system(SRPS)used in oil wells to ensure a safe and efficient *** current diagnosis method is pattern recognition of a dynamometer card(DC)based on feature extraction and *** premise of this method is that the training and target data have the same ***,the training data are collected from a field SRPS with different system parameters designed to adapt to production conditions,which may significantly affect the diagnostic *** address this issue,in this study,an improved model of the sucker rod string(SRS)is derived by adding faultparameter dimensions,with which DCs under 16 working conditions could be *** an adaptive diagnosis method is proposed by taking simulated DCs generated near the working point of the target SRPS as training ***,to further improve the accuracy of the proposed method,the DC features are improved by relative normalization and using additional features of the DC position to increase the distance between different types of *** parameters of the perceptron are optimized to promote its ***,the accuracy and real-time performance of the proposed adaptive diagnosis method are validated using field data.

关键词： Sucker rod pump dynamometer card Adaptive fault diagnosis Sucker rod dynamics Output metering

Approach to the Design Calculation of Sucker Rod Pumping Systems in Coalbed Methane Wells

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Chinese Journal of Mechanical Engineering 2011年第6期24卷 983-991页

作者： WANG Fudong LIU Xinfu Guan Zhichuan LIU Chunhua School of Petroleum Electronic Engineering China University of Petroleum Qingdao 266555 China Qingdao TSC Offshore Equipment Co Ltd. Qingdao 266108 China

The existing design of the pumping systems mainly focuses on the approximate computational formulae and procedures,which are developed based on the analytic approaches of conventional oil/gas *** calculation of polished rod loads usually just concerns about the static and inertial *** the computation of gearbox torque generally uses empirical formulae and correction *** above modeling procedures,if applied to the coalbed methane（CBM） wells,can not give the desired accuracy of the system design and its pertinent *** this paper,based on the kinematic and dynamic analysis of the pumping system,the kinematic relation of polished rod is analyzed,and the variation of the total loads of polished rod is developed with the limits of CBM well conditions along the *** gearbox torque calculation model is established by combining the counterbalance effect with the calculated dynamometer cards and torque *** application characteristics of this model are demonstrated by the example of ZH002-4 well in Qinshui *** interpretations of results show that the cranks of beam units should rotate in a counter clockwise direction viewed with the wellhead to the *** with oil？gas fields,the dynamic and friction to polished rod load ratios are relatively high and the computation of polished rod loads should involve the static and inertial loads,as well as vibration and friction *** the dynamic load ratio decreases rapidly during the ***,the total deformation of the string is small in CBM *** for balanced operation,the gearbox torque load usually has two approximately equal peaks and the magnitudes of instantaneous torque are just within 50% of unbalanced gearbox *** proposed research improves efficiency of the pumping system,loads the pumping unit more uniformly,and provides the reasonable basis for selecting the units.

关键词： sucker rod pump kinematic analysis polished rod load dynamometer card gearbox torque

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

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Petroleum Science 2024年第1期21卷 641-653页

作者： Yun-Peng He Hai-Bo Cheng Peng Zeng Chuan-Zhi Zang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016LiaoningChina Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016LiaoningChina Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169LiaoningChina University of Chinese Academy of Sciences Beijing100049China School of Artifcial Intelligence Shenyang University of TechnologyShenyang 110870LiaoningChina

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well *** learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis ***,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational ***,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different ***,there is heterogeneity in field data,which can dramatically impair the diagnostic *** solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this ***,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC ***,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data ***,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the *** on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational *** the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

关键词： Sucker-rod pumping system dynamometer card Working condition recognition Deep learning Time-frequency signature Time-frequency signature matrix

Using the curve moment and the PSO-SVM method to diagnose downhole conditions of a sucker rod pumping unit

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Petroleum Science 2013年第1期10卷 73-80页

作者： Li Kun Gao Xianwen Tian Zhongda Qiu Zhixue College of Information Science and Engineering Northeastern University

Downhole working conditions of sucker rod pumping wells are automatically identified on a computer from the analysis of dynamometer cards. In this process, extraction of feature parameters and pattern classification are two key steps. The dynamometer card is firstly divided into four parts which include different production information according to the ＂four point method＂ used in actual oilfield production, and then the moment invariants for pattern recognition are extracted. An improved support vector machine （SVM） method is used for pattern classification whose error penalty parameter C and kernel function parameter g are optimally chosen by the particle swarm optimization （PSO） algorithm. The simulation results show the method proposed in this paper has good classification results.

关键词： Sucker rod pumping unit diagnosis of downhole conditions dynamometer card curvemoment support vector machine particle swarm optimization

Multiple fault diagnosis of down-hole conditions of sucker-rod pumping wells based on Freeman chain code and DCA

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Petroleum Science 2013年第3期10卷 347-360页

作者： LI Kun GAO Xian-wen YANG Wei-bing DAI Ying-long TIAN Zhong-da College of Information Science and Engineering Northeastern University

It is important to achieve continuous, stable and efficient pumping well operation in actual oilfield operation. Down-hole pumping well working conditions can be monitored in real-time and a reasonable production scheme can be designed when computer diagnosis is used. However, it is difficult to make a comprehensive analysis to supply efficient technical guidance for operation of the pumping well with multiple faults of down-hole conditions, which cannot be effectively dealt with by the common methods. To solve this problem, a method based on designated component analysis （DCA） is used in this paper. Freeman chain code is used to represent the down-hole dynamometer card whose important characteristics are extracted to construct a designated mode set. A control chart is used as a basis for fault detection. The upper and lower control lines on the control chart are determined from standard samples in normal working conditions. In an incompletely orthogonal mode, the designated mode set could be divided into some subsets in which the modes are completely orthogonal. The observed data is projected into each designated mode to realize fault detection according to the upper and lower control lines. The examples show that the proposed method can effectively diagnose multiple faults of down-hole conditions.

关键词： Sucker-rod pumping wells multiple faults designated component analysis control chart Freeman chain code dynamometer card

Motor Power Based Inversion of dynamometer cards Using Hybrid Model

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Motor Power Based Inversion of Dynamometer Cards Using Hybri...

An Intelligent Diagnosis Method of the Working Conditions in Sucker-Rod Pump Wells Based on Convolutional Neural Networks and Transfer Learning

第32届中国控制与决策会议

作者： Dezhi Hao Xianwen Gao Xianyu Li School of Information Science and Engineering Northeastern University School of Automation and Electrical Engineering Shenyang Ligong University

The dynamometer card sensors’ poor real-time performance and high maintenance costs limit the control and diagnosis for sucker rod pumps（SRP） in oil exploitation. The motor which is the power source of the whole pumping process can reflect the working state of the entire equipment. The motor power can be accessed easily and ***, this paper proposes a method to measure the dynamometer cards based on the motor power. Firstly, a mathematical function relationship between the polished rod load and the motor power is established by fully considering many crucial factors in this process. Moreover, the data is compensated by the support vector machine for the top and bottom dead centers and the error of the mechanism model. At last, the proposed method is validated by a set of motor power data collected from wells by a self-developed device. The experimental result demonstrates the effectiveness of the proposed method for the inversion.

关键词： Sucker Rod Pump dynamometer card Motor Power Hybrid Modeling

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Energy Engineering 2021年第4期118卷 1069-1082页

作者： Ruichao Zhang Liqiang Wang Dechun Chen Shengli College China University of Petroleum Dongying257061China China University of Petroleum(East China) Qingdao266580China

In recent years,deep learning models represented by convolutional neural networks have shown incomparable advantages in image recognition and have been widely used in various *** the diagnosis of sucker-rod pump working conditions,due to the lack of a large-scale dynamometer card data set,the advantages of a deep convolutional neural network are not well reflected,and its application is ***,this paper proposes an intelligent diagnosis method of the working conditions in sucker-rod pump wells based on transfer learning,which is used to solve the problem of too few samples in a dynamometer card data *** on the dynamometer cards measured in oilfields,image classification and preprocessing are conducted,and a dynamometer card data set including 10 typical working conditions is *** this basis,using a trained deep convolutional neural network learning model,model training and parameter optimization are conducted,and the learned deep dynamometer card features are transferred and applied so as to realize the intelligent diagnosis of dynamometer *** experimental results show that transfer learning is feasible,and the performance of the deep convolutional neural network is better than that of the shallow convolutional neural network and general fully connected neural *** deep convolutional neural network can effectively and accurately diagnose the working conditions of sucker-rod pump wells and provide an effective method to solve the problem of few samples in dynamometer card data sets.

关键词： Sucker-rod pump well dynamometer card convolutional neural network transfer learning working condition diagnosis