Characterization and performance enhancement of electrical submersible pump (ESP) using artificial intelligence (AI)

被引：0
作者：
Panbarasan, M. [1 ]
Sankar, Subhashini [2 ]
Venkateshbabu, S. [3 ]
Balasubramanian, A. [4 ]
机构：
[1] AMET Univ, Dept Petr Engn, Chennai 603112, Tamil Nadu, India
[2] VELS Inst Sci Technol & Adv Studies VISTAS, Dept Petr Engn, Chennai 600117, Tamil Nadu, India
[3] JCTCET, Dept Petr Engn, Coimbatore 641105, Tamil Nadu, India
[4] Saveetha Engn Coll, Dept Chem Engn, Chennai 602105, Tamil Nadu, India
来源：
MATERIALS TODAY-PROCEEDINGS | 2022年 / 62卷
关键词：
Airborne survey; Annulus pressure; Gas-Oil ratio; Lube match; Machine Learning; Naive Bayes; NEURAL-NETWORKS; PREDICTION;
D O I：
10.1016/j.matpr.2022.05.101
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Electrical submersible pump (ESP) technology is the first choice of artificial lift for the operators both in offshore and onshore to increase the rate of production in all types of reservoirs. Even though, the ESP was designed, engineered and fabricated to withstand in harsh subsurface natural and man-made environment such as corrosion, high temperature and extreme pressure but it fails under these circumstances without any prerequisite signal. Even the monitoring systems in place failed to notify the failure of ESP. These ESP failures cut off the production and revenue circulation in the firm. The cost required for the repair and replacement of the ESP is also high and is time consuming. The prevention of ESP failures using machine learning technique is discussed.
引用
收藏
页码：6864 / 6872
页数：9
相关论文
共 25 条
  • [1] Abdelaziz M, 2017, AB DHAB INT PETR EXH, P17, DOI DOI 10.2118/188513-MS
  • [2] Al Maghlouth A., 2013, SPE 164382 MS
  • [3] Al-Qutami TA, 2017, INT J SMART SENS INT, V10, P199, DOI 10.21307/ijssis-2017-209
  • [4] Ambade A., 2021, SPE S ART INT RES EF, DOI [10.2118/208649-MS, DOI 10.2118/208649-MS]
  • [5] [Anonymous], 2019, NBM CW INFRA CON AUG
  • [6] [Anonymous], 2016, 181510 SPE
  • [7] Breit Steve, 2008, ELECT SUBMERSIBLE PU
  • [8] Chinn Matthew, 2019, WORLD OIL, P51
  • [9] Duru Ugochukwu Ilozurike, J PETROLEUM ENG TECH, V11
  • [10] Guo D., 2015, 2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC). Proceedings, P1, DOI 10.1109/PVSC.2015.7355706
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