Electric submersible pumps account for a considerable proportion in the development of the Bohai Oilfield. Improving the system efficiency of the electric submersible pump wells, ensuring that the units operate in the...Electric submersible pumps account for a considerable proportion in the development of the Bohai Oilfield. Improving the system efficiency of the electric submersible pump wells, ensuring that the units operate in the high-efficiency zone, is essential. Analysis shows that the efficiency of the electric submersible pump system depends on the wear and tear of each component of the submersible pump equipment, the setting of operational parameters, and more importantly, the production status and daily management level of the oil well. Therefore, improving the structural performance of the submersible pump product, optimizing the parameters setting of the oil well, strengthening daily management, establishing a scientific management system, and improving the production management process and system can effectively improve the production efficiency and economic benefits of the oil well, and further achieve the goal of energy saving and emission reduction. In addition, it is necessary to actively promote the concept and technology of energy saving and emission reduction, encourage oilfield enterprises to explore effective measures to reduce the energy consumption of the electric submersible pump system by strengthening the scientific management system, and achieve a green, low-carbon, and high-quality development of oilfield production to achieve the unity of economic benefits, social benefits, and environmental benefits. This article applies the above measures in the P oilfield to achieve energy optimization of submersible electric pump systems, reducing the daily power consumption of single well submersible electric pump systems by 371 kWh per day, increasing the submersible electric pump's lifespan by 200 days, generating considerable project benefits.展开更多
Electric submersible pumps were widely used in agricultural fields,petroleum and various other industries. The pressure pulsation caused fatigue failure due to vibration in electric submersible pump and affects the li...Electric submersible pumps were widely used in agricultural fields,petroleum and various other industries. The pressure pulsation caused fatigue failure due to vibration in electric submersible pump and affects the life and performance of its system. The objective of this study was to experimentally investigate the characteristics of pressure pulsation which were generated at various stages of a multistage electric submersible pump during closed valve operation at different speeds. An electric submersible pump with five stages was selected for conducting experiments. A variable frequency drive( VFD)was used to operate the electric submersible pump at five different speed settings from 40 to 60 Hz. Piezoresistive pressure transducers were mounted at each stage of the electric submersible pump to capture the unsteady pressure signals. At each speed setting,the electric submersible pump was operated at the shut-off condition and the signals of unsteady pressure from all the five stages were captured. A fast fourier transformation( FFT) was carried out on the pressure signals to convert into frequency domain.From the spectra of pressure pulsation signals,the characteristics of pressure pulsation are obtained for each stage and for various speed settings which were then used to understand its variation with speed and stages.展开更多
Artificial lift plays an important role in petroleum industry to sustain production flowrate and to extend the lifespan of oil wells. One of the most popular artificial lift methods is Electric Submersible Pumps (ESP)...Artificial lift plays an important role in petroleum industry to sustain production flowrate and to extend the lifespan of oil wells. One of the most popular artificial lift methods is Electric Submersible Pumps (ESP) because it can produce high flowrate even for wells with great depth. Although ESPs are designed to work under extreme conditions such as corrosion, high temperatures and high pressure, their lifespan is much shorter than expected. ESP failures lead to production loss and increase the cost of replacement, because the cost of intervention work for ESP is much higher than for other artificial lift methods, especially for offshore wells. Therefore, the prediction of ESP failures is highly valuable in oil production and contribute</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">s</span></span></span></span><span><span><span><span style="font-family:""><span style="font-family:Verdana;"> a lot to the design, construction and operation of oil wells. The contribution of this study is to use 3 machine learning algorithms, which are Decision Tree, Random Forest and Gradient Boosting Machine, to build predictive models for ESP lifespan while using both dynamic and static ESP parameters. The results of these </span><span style="font-family:Verdana;">models were compared to find out the most suitable model for </span></span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">the </span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">prediction of ESP life cycle. In addition, this study also evaluated the influence factor of various operating param</span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">e</span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">ters to forecast the most impact parameters on the duration of ESP. The results of this study can provide a better understanding of ESP behavior so that early actions can be realized to prevent potential ESP failures</span></span></span></span><span style="font-family:Verdana;">.展开更多
文摘Electric submersible pumps account for a considerable proportion in the development of the Bohai Oilfield. Improving the system efficiency of the electric submersible pump wells, ensuring that the units operate in the high-efficiency zone, is essential. Analysis shows that the efficiency of the electric submersible pump system depends on the wear and tear of each component of the submersible pump equipment, the setting of operational parameters, and more importantly, the production status and daily management level of the oil well. Therefore, improving the structural performance of the submersible pump product, optimizing the parameters setting of the oil well, strengthening daily management, establishing a scientific management system, and improving the production management process and system can effectively improve the production efficiency and economic benefits of the oil well, and further achieve the goal of energy saving and emission reduction. In addition, it is necessary to actively promote the concept and technology of energy saving and emission reduction, encourage oilfield enterprises to explore effective measures to reduce the energy consumption of the electric submersible pump system by strengthening the scientific management system, and achieve a green, low-carbon, and high-quality development of oilfield production to achieve the unity of economic benefits, social benefits, and environmental benefits. This article applies the above measures in the P oilfield to achieve energy optimization of submersible electric pump systems, reducing the daily power consumption of single well submersible electric pump systems by 371 kWh per day, increasing the submersible electric pump's lifespan by 200 days, generating considerable project benefits.
文摘Electric submersible pumps were widely used in agricultural fields,petroleum and various other industries. The pressure pulsation caused fatigue failure due to vibration in electric submersible pump and affects the life and performance of its system. The objective of this study was to experimentally investigate the characteristics of pressure pulsation which were generated at various stages of a multistage electric submersible pump during closed valve operation at different speeds. An electric submersible pump with five stages was selected for conducting experiments. A variable frequency drive( VFD)was used to operate the electric submersible pump at five different speed settings from 40 to 60 Hz. Piezoresistive pressure transducers were mounted at each stage of the electric submersible pump to capture the unsteady pressure signals. At each speed setting,the electric submersible pump was operated at the shut-off condition and the signals of unsteady pressure from all the five stages were captured. A fast fourier transformation( FFT) was carried out on the pressure signals to convert into frequency domain.From the spectra of pressure pulsation signals,the characteristics of pressure pulsation are obtained for each stage and for various speed settings which were then used to understand its variation with speed and stages.
文摘Artificial lift plays an important role in petroleum industry to sustain production flowrate and to extend the lifespan of oil wells. One of the most popular artificial lift methods is Electric Submersible Pumps (ESP) because it can produce high flowrate even for wells with great depth. Although ESPs are designed to work under extreme conditions such as corrosion, high temperatures and high pressure, their lifespan is much shorter than expected. ESP failures lead to production loss and increase the cost of replacement, because the cost of intervention work for ESP is much higher than for other artificial lift methods, especially for offshore wells. Therefore, the prediction of ESP failures is highly valuable in oil production and contribute</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">s</span></span></span></span><span><span><span><span style="font-family:""><span style="font-family:Verdana;"> a lot to the design, construction and operation of oil wells. The contribution of this study is to use 3 machine learning algorithms, which are Decision Tree, Random Forest and Gradient Boosting Machine, to build predictive models for ESP lifespan while using both dynamic and static ESP parameters. The results of these </span><span style="font-family:Verdana;">models were compared to find out the most suitable model for </span></span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">the </span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">prediction of ESP life cycle. In addition, this study also evaluated the influence factor of various operating param</span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">e</span></span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">ters to forecast the most impact parameters on the duration of ESP. The results of this study can provide a better understanding of ESP behavior so that early actions can be realized to prevent potential ESP failures</span></span></span></span><span style="font-family:Verdana;">.
