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

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.

Fault diagnosis for down-hole conditions of sucker rod pumping systems based on the FBH-SC method

Dynamometer cards are commonly used to analyze down-hole working conditions of pumping systems in actual oil production. Nowadays, the traditional supervised learning methods heavily rely on the classification accuracy of the training samples. In order to reduce the errors of manual classification, an automatic clustering algorithm is proposed and applied to diagnose down-hole conditions of pumping systems. The spectral clustering （SC） is a new clustering algorithm, which is suitable for any data distribution. However, it is sensitive to initial cluster centers and scale parameters, and needs to predefine the cluster number. In order to overcome these shortcom- ings, we propose an automatic clustering algorithm, fast black hole-spectral clustering （FBH-SC）. The FBH algo- rithm is used to replace the K-mean method in SC, and a CritC index function is used as the target function to automatically choose the best scale parameter and clus- tering number in the clustering process. Different simulation experiments were designed to define the relationship among scale parameter, clustering number, CritC index value, and clustering accuracy. Finally, an example is given to validate the effectiveness of the proposed algorithm.

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

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 fields.The calculation of polished rod loads usually just concerns about the static and inertial loads.And the computation of gearbox torque generally uses empirical formulae and correction factors.The above modeling procedures,if applied to the coalbed methane（CBM） wells,can not give the desired accuracy of the system design and its pertinent analysis.In 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 string.The gearbox torque calculation model is established by combining the counterbalance effect with the calculated dynamometer cards and torque factors.The application characteristics of this model are demonstrated by the example of ZH002-4 well in Qinshui basin.The interpretations of results show that the cranks of beam units should rotate in a counter clockwise direction viewed with the wellhead to the right.Compared 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 loads.And the dynamic load ratio decreases rapidly during the production.Besides,the total deformation of the string is small in CBM wells.As 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 loadings.The proposed research improves efficiency of the pumping system,loads the pumping unit more uniformly,and provides the reasonable basis for selecting the units.

Adaptive fault diagnosis of sucker rod pump systems based on optimal perceptron and simulation data

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 production.The current diagnosis method is pattern recognition of a dynamometer card(DC)based on feature extraction and perceptron.The premise of this method is that the training and target data have the same distribution.However,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 accuracy.To 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 generated.Subsequently an adaptive diagnosis method is proposed by taking simulated DCs generated near the working point of the target SRPS as training data.Meanwhile,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 samples.The parameters of the perceptron are optimized to promote its discriminability.Finally,the accuracy and real-time performance of the proposed adaptive diagnosis method are validated using field data.

Analytical model for thermal lensing and spherical aberration in diode side-pumped Nd:YAG laser rod having Gaussian pump profile

In this paper, according to the temperature and strain distribution obtained by considering the Gaussian pump profile and dependence of physical properties on temperature, we derive an analytical model for refractive index variations of the diode side-pumped Nd：YAG laser rod. Then we evaluate this model by numerical solution and our maximum relative errors are 5% and 10% for variations caused by thermo–optical and thermo–mechanical effects; respectively. Finally, we present an analytical model for calculating the focal length of the thermal lens and spherical aberration. This model is evaluated by experimental results.