Optimizing Artificial Lift Operations Through the Use of Wireless Conveyed Real Time Bottom Hole Data

10.2118/96-33 ◽  
1996 ◽  
Author(s):  
T. Bandy ◽  
B. Campbell

1996 ◽  
Author(s):  
Bryan Campbell ◽  
James MacKinnon ◽  
Thomas R. Bandy ◽  
Tom Hampton


2009 ◽  
Author(s):  
Muhammad Mirza ◽  
Rini Eka A Soegiyono ◽  
Ahmad Syaifudin ◽  
Said Amor Al Habsi ◽  
Tamer Ahmed ElSherif


2017 ◽  
pp. 66-71
Author(s):  
V. V. Mukhametshin

The authors of the paper observed considerable effect on performance time factor based onthe experience of bottom hole zone treatment with the use of hydrochloric acid solution preventing emulsification. The paper presents models and algorithms allowing planning effectiveness, choice of wells and technologies considering this factor in the real time mode.



2018 ◽  
Vol 7 (2.23) ◽  
pp. 133
Author(s):  
O A. Gribennikov ◽  
L N. Balandin ◽  
V I. Astafev

While operating the wells with ESP it’s impossible to make the direct measurement of the formation pressure with the use of bottom-hole pressure gauge. That is why they presently use various indirect methods to evaluate formation pressure that are based upon the re-calculation of static fluid level in well annulus for the fluid column pressure. The authors consider the procedure to evaluate formation pressure that was designed for the wells equipped with ESP. This procedure is a simple one and enables to perform real-time formation pressure metering. The obtained results have been compared with hydro-dynamic studies and have demonstrated their high convergence.  



2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Chavali M

Linear gel is prepared by treating bio-diesel with various water samplescollected from different water bodies. The new biodiesel based linear gel was employed in the recovery of oil wells through hydro fracturing and pilot tests were conducted for the first time. Viscosity of gel was measured at various bottom hole-circulating temperatures and it was found to vary from 32 to zero dial reading in the range of 45°C to 60°C. Gelwasobservedto break at 45°C and 60°C in 120 minutes. So, the final temperature was selected as 60°C for the application of gel for coal bed methane (CBM) wells. It was observed that higher levels of salinity in water helped in optimum utilization of gel in real time application.



2021 ◽  
Author(s):  
Oki Maulidani ◽  
Christian Bonilla ◽  
Monica Paredes ◽  
Pedro Escalona ◽  
Jorge Villalobos ◽  
...  

Abstract Electrical submersible pump (ESP) is the main artificial lift system in Shushufindi field. These systems besides facing high gas production, high scale and corrosion tendencies, also have to deal with surface fluid handling and electrical power limitations which combined impose challenges to optimize the ESP system. In perspective, the digitalization initiative has been key to integrate data in order to have a big picture of the actual field condition and ultimately to enhance oil production. Various dashboards have been created using the business intelligence tool to provide real time information. ESP dashboard shows opportunities to optimize the ESP unit by integrating real time and manual entry data to optimize frequency, surface equipment, opportunities for pump upsizing, and re-designing the ESP downhole equipment. The result of this analysis is derived from ESP simulation, nodal analysis, chemical treatment monitoring and real time surveillance of the ESP parameters. Dashboards of water handling, electrical power, and chemical treatment are utilized to support process analysis providing current field status, with also the feedback from operational and engineering recommendations. Comprehensive real time monitoring resulted in average of 500 bopd less production deferment in the last 12 months as the result of early detection and a proper operational optimization (chemical treatment, gas flaring, and choke optimization) of the unstable wells. Strategic decisions have been executed to ensure the availability of water handling capacity and electrical power for each production station such as stimulating disposal wells, cleaning injection flowlines, and repairing power generations. Up to 3,000 bopd total incremental has been generated in the last 12 months as the result of 17 upsizing operations, optimizing frequency in 68 wells, and optimizing surface equipment in 35 wells. The associated mean time between failures (MTBF) of ESP system has increased over the time from 224 days in 2013 to 674 days in 2020. Digitalization is a game changer for optimizing the oilfield production and to reduce associated operation risks from features as of real time surveillance, EDGE computing, remote actuation, and big data intelligence. This paper will elaborate in detail on how digitalization can be valuable in optimizing ESP system with a successful case study in Shushufindi field.





2020 ◽  
Vol 60 (1) ◽  
pp. 197
Author(s):  
Fahd Saghir ◽  
M. E. Gonzalez Perdomo ◽  
Peter Behrenbruch

In Queensland, progressive cavity pumps (PCPs) are the artificial lift method of choice in coal seam gas (CSG) wells, and this choice of artificial lift production stems from the ability of PCPs to better manage the production of liquids with suspended solids. As with any mechanical pumping system, PCPs are prone to natural wear and tear over their operational life, and with the production of coal fines and inter-burden, the run life of PCPs in CSG wells is significantly reduced. Another factor to consider with the use of PCPs is their reliability. As per the CSG production data available through the Queensland Government Data Portal, there are approximately 6400 wells operational in the state as of December 2018. This number is expected to grow significantly over the next decade to meet both international and domestic gas utilisation requirements. Operators supervising these wells rely on a reactive or exception-based approach to manage well performance. In order to efficiently operate thousands of PCP wells, it is pertinent that a benchmark methodology is devised to autonomously monitor PCP performance and allow operators to manage wells by exception. In this study, we will cover the application of machine learning methods to understand anomalous PCP behaviour and overall pump performance based on the analysis of multivariate time-series data. An innovative time-series data approximation and image conversion technique will be discussed in this paper, along with machine learning methods, which will focus on a scalable and autonomous approach to cluster PCP performance and detection of anomalous pump behaviour in near real-time. Results from this study show that clustering real-time data based on converted time-series images helps to pro-actively detect change in PCP performance. Discovery of anomalous multivariate events is also achieved through time-series image conversion. This study also demonstrates that clustering time-series data noticeably improves the real-time monitoring capabilities of PCP performance through improved visual analytics.



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