Electrical Submersible Pump Performance Research Articles

Best Practices and Innovations for Improved ESP Performance

This article, written by Assistant Technology Editor Karen Bybee, contains highlights of paper SPE 136407, ’Best Practices & Innovations for Improved ESP Performance; Mature Field Case History; TNK-BP Company, Russian Federation,’ by D.C. Borling, SPE, BP, and S.V. Sviderskiy, SPE, and, S.F. Gorlanov, SPE, TNK-BP, originally prepared for the 2010 SPE Russian Oil & Gas Technical Conference and Exhibition, Moscow, 26-28 October. The paper has not been peer reviewed. Leadership, teamwork, and technical ingenuity were critical strategy elements that resulted in an 82% run-life improvement for electrical-submersible-pump (ESP) systems in the TNK-BP company. During the past 4 years, the 12-month rolling mean time between failure (MTBF) steadily improved from 295 days during January 2006 to the current 541 days in July 2010. This 246-day improvement was achieved across more than 14,250 ESPs and achieved USD 307 million value to date. Introduction TNK-BP is a privately owned oil and gas joint venture. The company was formed in 2003 and for the past 7 years its upstream producing operations were located primarily in West Siberia (Khanty-Mansiysk and Yamalo-Nenets Autonomous Districts, Tyumen Region), East Siberia (Irkutsk Region), and Volga-Urals (Orenburg Region). As of July 2010, the company operated more than 200 hydrocarbon-bearing fields with approximately 15,700 active producing oil wells. More than 98% of these wells used artificial lift. In TNK-BP, ESP systems refer to both surface and downhole equipment components. Surface components include transformer, switchboard (and/or variable-speed motor controller), and a relatively short surface power cable. Downhole components include pump intake (and/or gas separator), seal element, motor, and a long downhole cable (used to transfer power from the surface to the motor). Operating Conditions Each of the company’s 14 regional business locations has unique operating conditions. By mid-2010, more than 50 different types of ESP equipment were deployed across the company to lift a wide range of produced-fluid rates and gas and solid content. Approximately 92% of all deployed ESP equipment was manufactured within the Russian Federation. The remaining 8% was imported for use in complicated well conditions and harsh downhole operating environments. TNK-BP deployed ESP equipment in almost every type of downhole condition imaginable. Harshest conditions included a mixture of high temperature, abrasive solids, scaling, asphaltene, paraffin, high free-gas content, and corrosive fluids. Teamwork Without good teamwork on a massive scale across five business segments and 14 regional businesses, the TNK-BP ESP-MTBF-improvement initiative would not have achieved the intended results. A best practice was the method used to align ESP MTBF key performance indicators and work plans at the start of each year. While this alignment was a big undertaking, it proved itself to be worth the effort each year.

Simple model of electric submersible pump in gassy well

Electric submersible pump (ESP) is a widely used artificial lift method for oil production. Free gas at the pump intake can degrade the ESP performance. Degradation can be in the form of reduced head, surging and gas locking. This paper presents a new easy-to-use model intended for the field engineer. The model's parameters are obtained by using linear multiple regression analysis on measured data. The model is not pump-specific as it uses dimensionless head and rate. In addition, a critical model and a simple equation are presented to predict the start of surging, which can cause pump instability and even gas lock. The study also gives the field engineer an idea of how the liquid-only affinity laws are impacted in multiphase flow conditions. Compared with available models, the presented pump head degradation model and the critical model are both the best.

Influence of Viscosity on ESP Performance

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 110661, "On the Influence of Viscosity on ESP Performance," by Gilmar Amaral and Valdir Estevam, Petroleo Brasileiro S.A, and Fernando A. Franca, SPE, State University of Campinas, prepared for the 2007 SPE Annual Technical Conference and Exhibition, Anaheim, California, 11–14 November. The paper has not been peer reviewed. Experimental data and a preliminary analysis of the operation of centrifugal pumps with viscous liquids are presented. Two centrifugal pumps, a conventional radial and a semiaxial electrical submersible pump (ESP), were instrumented and tested with water and clear glycerin. The glycerin viscosity was varied from 67 to 1,020 cp by changing the temperature, encompassing the viscosity range of light-to-heavy oils. The main purpose of these tests, besides measuring the influence of viscosity on the pump overall performance, was to supply detailed information on the energy-transfer processes taking place in the pumps' internal components. Introduction ESPs have been used increasingly as an artificial-lift method to produce medium-to-heavy oils in deep offshore fields. The pump may be inside the well or, depending on technical requirements, above the seabed to reduce intervention costs, as is the case in Jubarte field in Campos basin, Brazil. When the oil viscosity is too high to allow efficient pump operation, the oil viscosity can be reduced by injecting light oil (usually referred to as a downgrading technique) or solvents upstream of the pump suction or by raising the mixture temperature. When installed on the seabed, series- or parallel-arranged pump systems can be used to reduce the power required by each pump. Thus, new operation strategies and different equipment allocation and arrangements have been used to exploit heavy oils in these harsh environments. In Jubarte field, an ESP was installed in the production riser, just above the tree, to lift the raw mixture to the platform. When the ESP is on the seabed, the fluid temperature may be lower than the reservoir temperature. The heat generated in the ESP, which reduces the fluid viscosity and increases pump performance, is partially lost to the surrounding cold water. As the pumped mixture cools and attains a higher viscosity, pump performance is affected. Additionally, a pump at seabed level operates at a reduced inlet pressure compared with an in-well pump and may increase the free-gas content, additionally reducing pump performance. Therefore, fluid viscosity is a key technical issue when selecting an ESP to lift medium-to-heavy oil in offshore fields. The performance of pumps operating with liquids of various viscosities is obtained by either empirical or deterministic methods. Empirical methods usually try to adjust the pump performance starting with the published pump-characteristic curves for water. Nondimensional parameters and correcting coefficients for hydrostatic head and efficiency for a given flow rate and fluid viscosity are used to estimate the actual characteristics on the basis of those for water. However, the database is limited in terms of pump characteristics and operational conditions.

Survival Analysis: The Statistically Rigorous Method for Analyzing Electrical Submersible Pump System Performance

Summary A rigorous statistical methodology using survival analysis (SA) was developed and applied to electrical submersible pump (ESP) system performance data. The approach extracts unbiased information from performance data and permits lifetime modeling, with parameter combinations employing all available data. The analysis explicitly accounts for ESPs that are still operational at the time of the study, thus removing a historical source of statistical bias. The analysis uses Kaplan-Meier (KM) (Kaplan and Meier 1958) and Cox proportional hazards (CPHs) (Cox 1972) modeling to determine statistical significance of explanatory variables (EVs). Methods developed to facilitate EV factor collapsing are also discussed (the partitioning of levels of each factor into nonempty subsets of statistically similar response), so that an acceptable degree of parsimony is achieved. Essential definitions necessary for preliminary data structure are also covered. We demonstrate the practical utility of this methodology on a comprehensive data set to enable unbiased and conclusive appraisal of ESP performance, thereby resolving a common concern about comparative-system reckoning. The paper concludes that SA, suitably applied to properly censored data, is essentially the only reliable method of evaluating ESP system performance (and other types of time-to-event data). Introduction The critical importance of ESP system performance to field economics and deliverability has been well documented (Allis and Capps 1984; Upchurch 1990; Brookbank 1996). What has been missing, however, is agreement as to what constitutes the most appropriate methodology for analyzing the wealth of performance data that are collected. The manner in which the available data are scrutinized, analyzed, qualified, and presented is influential to timely, economic, and accurate well and field design. This paper shows how we can extract the full profundity of useful information that inhabits even a moderately sized data set through application of, what we consider to be, the only truly appropriate technique for analyzing time-to-event data: SA. The objective of any SA is to identify variables that influence survival and to predict survival probabilities. This is achieved by finding a suitable statistical model that fits the data closely. We then examine variables included in the model and, finally, make predictions about ESP system performance for well- and field-planning purposes. The structure of this article is as follows:First, we outline the problems and inconsistencies inherent with existing (non-SA) analysis approaches to ESP performance analysis.Background on SA is then provided, along with an outline of the three main classes of SA methodology.We define terminology; in particular, the terms "system" and "components."We then present a summary of the extensive data set employed in the analysis.The remainder of the paper presents a detailed and sequential SA for a rich data set to demonstrate how parameter interaction, factor collapsing, and appropriate goodness-of-fit measures can be employed to achieve a parsimonious model of the given data. Note that a parsimonious model, in this context, refers to one containing the minimum number of significant parameters that adequately represents the data.Finally, we conclude that SA is the only viable and appropriate unbiased time-to-event methodology for evaluating ESP system performance. The analytical process we propose represents the given data parsimoniously and provides performance indicators (with confidence bounds) in response to specific questions. At the risk of premature presentation of results, Fig. 1 shows just one such SA plot that can be generated. This plot provides unbiased answers to a specific question: "What is the performance between Cable Manufacturers A, B, and C when required to last 500 days, when installed with Motor Series "D" in a well that has sand (abrasion) present" Also, "What degree of confidence can we have in these results" We see from Fig. 1 that 57% of pumps installed with Cable Manufacturer "A" are expected to survive to 500 days, while only approximately 33% of pumps with Cable Manufacturer "B and C" survived to this time (note that B and C are grouped together, as are Motor Series Types "D, L, and I," because there is no statistical difference between them). For Cable Manufacturer A, we are 95% confident that the interval between 40 and 80% covers the true (unknown) proportion surviving to 500 days. The equivalent range for Cable Manufacturers B and C is between 25 and 48%. We conclude, therefore, that for the specific conditions stated in the question (and everything else being equal), Manufacturer A performs better than B and C by the margins stated. Associated validation statistics also conclude that we may draw reliable statistical inference from these results. We now have a solid platform upon which to base performance contracts. By the end of this article, we hope to have demonstrated a rigorous and unbiased methodology for analyzing ESP system performance data and essentially any time-to-event data.