A new technology of offshore oil rod pumping production is developed for offshore heavy oil recovery. A new type of miniature hydraulic pumping unit with long-stroke, low pumping speed and compact structure is designe...A new technology of offshore oil rod pumping production is developed for offshore heavy oil recovery. A new type of miniature hydraulic pumping unit with long-stroke, low pumping speed and compact structure is designed based on the spatial characteristics of offshore platforms. By combining the strengths of sinusoidal velocity curve and trapezoidal velocity curve, a kinematical model of the acceleration, the velocity and displacement of the pumping unit＇s hanging point is established. The results show that the pumping unit has good kinematic characteristics of smooth motion and small dynamic load. The multi-degree-of-freedom dynamic model of the single-well pumping unit is established. The first and second order natural frequencies of the sucker rod string subsystem and the pumping unit subsystem are studied. The results show that the first and the second order natural frequencies among the pumping rod string, pumping unit-platform subsystem and the dynamic excitation have differences over 5 times from each other, indicating that resonance phenomenon will not appear during the operation and the dynamic requirements for field use are met in the system.展开更多
Inspired by the modulation mechanism of neuroendocrine-immune system(NEIs),a novel structure of artificial neural network(ANN) named NEI-NN and its learning method are presented.The NEI-NN includes two parts,i.e.,posi...Inspired by the modulation mechanism of neuroendocrine-immune system(NEIs),a novel structure of artificial neural network(ANN) named NEI-NN and its learning method are presented.The NEI-NN includes two parts,i.e.,positive subnetwork(PSN) and negative sub-network(NSN).The neuron functions of PSN and NSN are designed according to the increased and decreased secretion functions of hormone,respectively.In order to make the novel neural network learn quickly,the novel neuron based on some characteristics of NEIs is also redesigned.Besides the normal input signals,two control signals are considered in the proposed solution.One is the enable/disable signal,and the other is the slope control signal.The former can modify the structure of NEI-NN,and the later can regulate the evolutionary speed of NEINN.The NEI-NN can obtain the optimized network structure by using error back-propagation(BP) learning algorithm.Since the modeling of the beam pumping unit is very difficult by using the conventional method,the modeling of bean bump unit is chosen to examine the performance of the NEI-NN.The experiment results show that the optimized structure and learning speed of NEI-NN are better than those of the conventional neural network.展开更多
基金financially supported by the National Natural Science Foundation of China(Grant No.51174224)the National Science and Technology Major Projects of Oil and Gas(Grant Nos.2016ZX05066 and 2016ZX05042)the Natural Science Foundation of Shandong Province(Grant No.ZR2014El015)
文摘A new technology of offshore oil rod pumping production is developed for offshore heavy oil recovery. A new type of miniature hydraulic pumping unit with long-stroke, low pumping speed and compact structure is designed based on the spatial characteristics of offshore platforms. By combining the strengths of sinusoidal velocity curve and trapezoidal velocity curve, a kinematical model of the acceleration, the velocity and displacement of the pumping unit＇s hanging point is established. The results show that the pumping unit has good kinematic characteristics of smooth motion and small dynamic load. The multi-degree-of-freedom dynamic model of the single-well pumping unit is established. The first and second order natural frequencies of the sucker rod string subsystem and the pumping unit subsystem are studied. The results show that the first and the second order natural frequencies among the pumping rod string, pumping unit-platform subsystem and the dynamic excitation have differences over 5 times from each other, indicating that resonance phenomenon will not appear during the operation and the dynamic requirements for field use are met in the system.
基金the Key Project of the National Natural Science Foundation of China(No.61134009)National Natural Science Foundations of China(Nos.61473078,61271001)+5 种基金Program for Changjiang Scholars from the Ministry of Education,ChinaSpecialized Research Fund for Shanghai Leading Talents,ChinaProject of the Shanghai Committee of Science and Technology,China(No.13JC1407500)the Fundamental Research Funds for the Central Universities,China(No.09CX04026A)Excellent Youth and Middle Age Scientists Fund of Shandong Province,China(No.BS2010DX038)Fundamental Research Funds for the Central Universities,China(No.14CX02171A)
文摘Inspired by the modulation mechanism of neuroendocrine-immune system(NEIs),a novel structure of artificial neural network(ANN) named NEI-NN and its learning method are presented.The NEI-NN includes two parts,i.e.,positive subnetwork(PSN) and negative sub-network(NSN).The neuron functions of PSN and NSN are designed according to the increased and decreased secretion functions of hormone,respectively.In order to make the novel neural network learn quickly,the novel neuron based on some characteristics of NEIs is also redesigned.Besides the normal input signals,two control signals are considered in the proposed solution.One is the enable/disable signal,and the other is the slope control signal.The former can modify the structure of NEI-NN,and the later can regulate the evolutionary speed of NEINN.The NEI-NN can obtain the optimized network structure by using error back-propagation(BP) learning algorithm.Since the modeling of the beam pumping unit is very difficult by using the conventional method,the modeling of bean bump unit is chosen to examine the performance of the NEI-NN.The experiment results show that the optimized structure and learning speed of NEI-NN are better than those of the conventional neural network.
