A Case Study of Energy Storage Stimulation for Ultra-Low Permeability Oil Reservoir

2017 ◽  
Author(s):  
Wei Liu ◽  
Kai Zhang ◽  
Tao Jiang ◽  
LiMin Yu ◽  
ZhiDong Bao ◽  
...  
2014 ◽  
Author(s):  
Justin Ezekiel ◽  
Yuting Wang ◽  
Yanmin Liu ◽  
Liang Zhang ◽  
Junyu Deng ◽  
...  

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiangwu Bai ◽  
Zhiping Li ◽  
Fengpeng Lai

Low-permeability oil reservoirs account for more than two-thirds of China’s proven reserves, and most of them are multilayered; the traditional sweet spots focus on single-layered reservoirs. The sweet spots of low-permeability reservoirs have two meanings: the geologically superior reservoir and the beneficial development of the reservoir. In this study, a concept of reservoir stratification coefficient is proposed to evaluate the characteristics of multilayered reservoirs, and three indicators are proposed, namely, reservoir stratification coefficient, energy storage coefficient, and stratigraphic coefficient, as the indicators of sweet spots of multilayered reservoirs. The three indicators are combined into a single indicator using a weighted approach, and the sweet spots can be identified based on the combined indicator. The Xiliu A area of the North China oilfield was selected for a case study. According to the structural, sedimentary, and reservoir characteristics of the block, combined with the development and production conditions, the Sha 3 Member I oil group was selected as the study object of sweet spots of the low-permeability reservoir. The results show that the reservoir stratification coefficient, energy storage coefficient, and stratigraphic coefficient proposed in this study are effective indicators for the preferential selection of sweet spots, which can reflect the longitudinal heterogeneity, energy storage size, and flow capacity of multilayered reservoirs. After a comparative analysis with actual blocks, it was found that the results obtained using the method are consistent with the actual capacity of the reservoir. The production capacity is high. The evaluation effect is ideal, and the applicability is good. Thus, this study provides a new technical method for the evaluation of similar multilayered reservoirs. The findings of this study can help for a better understanding of the development and production conditions and optimization basis of low-permeability reservoirs.


2014 ◽  
Author(s):  
Justin Ezekiel ◽  
Yuting Wang ◽  
Yanmin Liu ◽  
Liang Zhang ◽  
Junyu Deng ◽  
...  

2016 ◽  
Author(s):  
J. R. Shaoul ◽  
W. J. Spitzer ◽  
S. Fekkai ◽  
L. Sepulveda

2016 ◽  
Author(s):  
Peng Yi ◽  
Weng Dingwei ◽  
Xu Yun ◽  
Wang Liwei ◽  
Lu Yongjun ◽  
...  

2021 ◽  
Vol 13 (8) ◽  
pp. 4549
Author(s):  
Sara Salamone ◽  
Basilio Lenzo ◽  
Giovanni Lutzemberger ◽  
Francesco Bucchi ◽  
Luca Sani

In electric vehicles with multiple motors, the torque at each wheel can be controlled independently, offering significant opportunities for enhancing vehicle dynamics behaviour and system efficiency. This paper investigates energy efficient torque distribution strategies for improving the operational efficiency of electric vehicles with multiple motors. The proposed strategies are based on the minimisation of power losses, considering the powertrain efficiency characteristics, and are easily implementable in real-time. A longitudinal dynamics vehicle model is developed in Simulink/Simscape environment, including energy models for the electrical machines, the converter, and the energy storage system. The energy efficient torque distribution strategies are compared with simple distribution schemes under different standardised driving cycles. The effect of the different strategies on the powertrain elements, such as the electric machine and the energy storage system, are analysed. Simulation results show that the optimal torque distribution strategies provide a reduction in energy consumption of up to 5.5% for the case-study vehicle compared to simple distribution strategies, also benefiting the battery state of charge.


Energy ◽  
2021 ◽  
Vol 221 ◽  
pp. 119902
Author(s):  
Amir Reza Razmi ◽  
M. Soltani ◽  
Armin Ardehali ◽  
Kobra Gharali ◽  
M.B. Dusseault ◽  
...  

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