Switched Reluctance Motor for Electric Submersible Pump

Switched reluctance motors may be advantageous when used as the primary motor for an electric submersible pump system. They are less susceptible to jamming failures due to their high starting torque and ability to reverse direction. Driving these motors requires well-timed pulse waveforms and precise control of the motor based on its rotational position. In general, voltage-based sensing and control systems at the surface see highly unpredictable waveforms with excessive ringing behaviour due to the impedance characteristics of the long cabling between the surface controller and the downhole motor system. In this work, a system is detailed which monitors the current waveforms on the motor coil excitation conductors at the surface as a source of motor performance feedback and control. State-space modelling of the system shows stable current waveforms at the surface controller for both short and long interconnect cable systems. A laboratory demonstration of the surface controller, interconnect cabling, and motor system is shows excellent agreement with the current and voltage waveforms predicted by the state-space system model.

Switched Reluctance Motor for Electric Submersible Pump

Switched reluctance motors may be advantageous when used as the primary motor for an electric submersible pump system. They are less susceptible to jamming failures due to their high starting torque and ability to reverse direction. Driving these motors requires well-timed pulse waveforms and precise control of the motor based on its rotational position. It is demonstrated that the pulses required to drive switched reluctance motors can still be applied over along cable lengths. Additionally, the current at the surface can be used to monitor and control the operation of the motor downhole, even with long cable lengths separating the surface power source and downhole motor.

Autonomous Corrosion and Scale Management in Electric Submersible Pump Wells

Producers find a considerable amount of their operating expense (OPEX) comes from managing risks associated with corrosion and scale. Monitoring and chemical adjustment workflows are typically manual, and performed at low frequencies, leading to delays in event detection. As a result, the potential for negative events such as production shutdowns and well failures increase. This project's scope integrates chemistry domain experience with edge analytics, machine learning models, and intelligent equipment, to transform manual processes into an autonomous solution. The goal is to optimize operations, reduce well failures and workover costs, and maximize production. This solution is currently deployed in an oilfield, that has been historically challenged with a high number of electric submersible pump (ESP) failures due to corrosion and scale that resulted in significant production losses and unforeseen workover costs. The designed digital architecture supports autonomous management of scale and corrosion through remote monitoring and automated chemical injection. Real-time data is acquired from connected equipment, processed in an edge device running artificial intelligence, and autonomously sent to chemical pumps. Data from sensors, connected devices, and models are visualized in cloud applications, or integrated into existing client systems for end user analysis and full visibility of the entire process. The results show highly accurate models, precise chemical injection, and a reduction of well failures.

Overcoming Deployment and Retrieval Challenges with Killed Well Cable Deployed Electric Submersible Pump Systems – Lessons Learned from Five Years of CDESP History

The advantage of cable deployed electric submersible pump (CDESP) systems are beginning to be understood and realized as experience has been gained with the deployment and retrieval of these systems. Cable deployed ESP systems have at times been touted as a temporary system for failed conventional ESP systems. Long-term successes have demonstrated the value of permanently installed CDESP systems, which provide the benefit of reduced production deferral, less costly change-out, and reduced HSE risk. The decision to change from conventional ESP to a rigless CDESP system is not necessarily a simple conclusion. The decision must consider technical, economic, and operational considerations to gain the full benefit from the technology. The learnings developed over multiple deployments and retrievals will benefit decision makers in the evaluation of the technology use. The technology application presented in the paper sheds the light on a journey to develop and bring alternative ESP deployment from concept to reality, overcoming technical and operational challenges. The current CDESP requires a rig to initially construct the permanent completion to accept the rigless CDESP system. Production rates requirements determine the ESP size, and in turn the tubing and wellhead size. Pressure control equipment is installed on top of the Christmas tree. Rigless installation and retrieval of the CDESP is performed on an elevated tower with the wellhead in place. The tower design has been improved to allow the production flowline to remain in place. A minimum of two well barriers, with one barrier well kill fluid, are in place at all times. A key learning of the killed well CDESP system is the need to understand the potential changes to the reservoir after sustained production in planning the replacement of a failed ESP. Kill fluid losses can be higher than expected with restorative well cleanup and production. Actual deployment or retrieval time can be improved with successive change-outs. Long-term operational robustness of the CDESP is proven with a system continuing to operate after 5 years of cumulative operations. This paper shares the lessons learned from an early technology adopter with multiple deployment and retrievals in various well environments including highly fractured reservoirs and high hydrogen sulfide wells.

Modelling of Electric Submersible Pump Work on Gas-Liquid Mixture by Machine Learning

Oil wells in Western Siberia usually placed on artificial drilling pads, forming well clusters up to 30 wells. The flow rate of each well in the cluster measured by an automatic measuring unit one by one. Often flow rate measurement requires several hours and flow rate of a single well can be measured once a week or less. This led to situation then events affecting well rate can be invisible between measurements. Identifying such events can be extremely useful in many cases, for example for wells with unstable behavior or transient regimes. The same challenges are also faced at distant green fields during their development, there the flow rates can be measured once a month with a mobile unit. The objective of this paper is to develop a virtual flowmeter model based on indirect high-frequency data of well operation and ESP. In Gubkin University, at the Petroleum Reservoir and Production Engineering Department, bench tests of ESP5-50 (118 radial stages) on gas-liquid mixture in a wide range of volumetric gas content (βin = 0-60%), intake pressure (Pin = 0.6-2.1 MPa) and pump shaft speed (n= 2400-3600 rpm) were performed. Three vibration sensors were installed on the unit: on the ESP, at the ESP discharge, on the pipeline, which simulates the wellhead production tree. During the bench tests were recorded series of pressures at the intake, discharge and along the pump length, series of current and power consumption, as well as vibrations with frequency several times per second. Based on the bench test results, we investigated the possibility of indirect determination of well operation parameters during artificial lift modelling by machine learning. As a result, the approaches to modelling taking into account various sets of parameters (features) have been studied: based on hydraulic parameters – ESP intake and outlet pressure;based on hydraulic and electric parameters – current and power consumption;based on hydraulic, electric and vibrating parameters. The analysis of data series allowed to define the boundaries of stable ESP operation, namely the transition to surging and pump starvation. The novelty of the work is: –machine learning modeling of the gas-liquid mixture pumping process by electric submersible pump;–solving both direct and inverse issues: as virtual liquid flowmeter as, virtual gas content flowmeter at the pump intake.

The EVALUATION AND OPTIMIZATION OF ELECTRICAL SUBMERSIBLE PUMP WELLS THAT HAVE A HIGH PI USING VARIABLE SPEED DRIVE WITH FREQUENCY ABOVE 60HZ IN "X" FIELD "Y" WELLS (EVALUASI DAN OPTIMISASI SUMUR ELECTRICAL SUBMERSIBLE PUMP YANG MEMILIKI PI TINGGI DENGAN MENG

The condition of a well if it is produced continuously will cause reservoir pressure to fall, and the flow rate will also go down, as a result the productivity of the well will also decrease. For this reason, there is a need for energy that can help lift fluid up to the surface. In the primary method there are 2 stages of production, namely natural flow where oil is raised directly through the tubing surface, and artificial lift is the method of obtaining oil by using the aid of additional tools. In the oil industry there are various types of artificial lifts, one of which is an electric submersible pump (ESP). Electric Submersible Pump is an electric pump that is immersed into a liquid. This pump is made on the basis of a multilevel centrifugal pump where each level has an impeller and iffuser which aims to push the fluid to the surface. ESP planning is strongly influenced by the roductivity of production wells. The rate of fluid production influences the selection of pump type and size. This is because each pump has its own production rate based on the type and size of each pump used. In the course of producing oil, there will certainly be a problem that will cause a decline in production, therefore it is necessary to evaluate and redesign the ESP pump, in an effort to optimize the production potential of these wells. In this study an evaluation of the performance of the electrical submersible pump will be carried out and a pump redesigned to optimize production using AutographPC software on the well X in the field Y Kondisi suatu sumur jika diproduksikan terus-menerus akan mengakibatkan tekananreservoir turun, dan laju alir akan turun pula, akibatnya produktivitas sumur akan turunjuga. Untuk itu perlu adanya tenaga yang dapat membantu mengangkat fluida sampaikepermukaan. Dalam metode primer terdapat 2 tahapan produksi yaitu natural flowdimana minyak terangkat kepermukaan langsung melalu tubing, dan artificial liftmerupakan metode perolehan minyak dengan menggunakan bantuan alat tambahan.Dalam dunia perminyakan ada berbagai macam jenis pengangkatan buatan salahsatunya adalah electric submersible pump (ESP). Electric Submersibel Pump merupakan pompa listrik yang dibenamkan kedalam cairan.Pompa ini dibuat atas dasar pompa sentrifugal bertingkat banyak dimana setiap tingkatmempunyai impeller dan diffuser yang bertujuan untuk mendorong fluida kepermukaan.Perencanaan ESP sangat dipengaruhi oleh produktivitas sumur produksi. Laju produksifluida berpengaruh terhadap pemilihan jenis dan ukuran pompa. Hal ini dikarenakantiap-tiap pompa memiliki laju produksi sendiri berdasarkan jenis dan ukuran tiap- tiappompa yang dipakai. Dalam kegiatan memproduksikan minyak tentu suatu saat akan terjadi permasalahanyang mengakibatkan menurunnya produksi, Oleh karena itu perlu dilaksanakan evaluasidan design ulang pompa ESP, sebagai upaya untuk mengoptimalkan potensi produksisumur-sumur tersebut. Pada penelitian ini akan dilakukan evaluasi kinerja electricalsubmersible pump dan melakukan desain ulang pompa untuk optimasi produksidengan menggunakan software AutographPC pada sumur X lapangan y Kata kunci: electric submersible pump, AutographPC, laju produksi

Justification of a comprehensive technology for preventing the formation of asphalt-resin-paraffin deposits during the production of highlyparaffinic oil by electric submersible pumps from multiformation deposits

Severe problems accompany the production of abnormal oils with high pour point (with a paraffin content of over 30% by weight) in Kraynego Severa, Russia, due to the intensive formation of asphalt-resin-paraffin deposits (ARPD) in the bottom hole zone of the productive formation and downhole equipment. Possessing many advantages, the existing methods and technologies for coping with ARPD cannot fully solve this problem. As a result, complications arising from the production of high-wax oils lead to a significant decrease in oil production, a reduction in the production wells' maintenance and intertreatment periods, and an increase in dewaxing unit operating costs. The obtained results of theoretical and laboratory studies show that one of the promising approaches to improve the efficiency of wells equipped with electric submersible pumps when exploitation of abnormal oils with high pour point from multilayer deposits of the Timan-Pechora oil and gas province is the use of the new integrated technology based on the joint production of abnormal oil with high pour point with the oil, characterized by a lower wax content and the manifestation of structural and mechanical properties, in conjunction with regulating the parameters of the electric submersible pump. In this paper, the authors also describe a promising scheme of downhole equipment for the simultaneous-separate production of high-wax oil from multilayer deposits. The proposed downhole equipment allows us to separate the perforation zones of two productive formations using a packer-anchor system during simultaneous-separate exploitation of the formations by a double electric submersible pump installation.

Demonstration of Advanced Magnetic Technologies for a Highly Reliable and Retrievable Electric Submersible Pump Topology

This effort designs, builds and tests key enabling technology components of the magnetic drive system (MDS) electric submersible pump (ESP) concept, an advanced high speed ESP that differs from conventional ESP topologies in using magnetic technologies to increase reliability and retrievability. The enabling components include a radial passive magnetic bearing (PMB) system, allowing for a contact-less bearing system and remote removal of rotating components, and magnetic vibration sensors (MVS), enabling prognostics for higher reliability. An MDS ESP preliminary design has been developed through a DeepStar program, from which the size and integration requirements of the PMB and MVS have been defined. These requirements guide the analysis, design and testing of the full-scale components. Empirical analysis tools are used for initial iterations in size and performance of the PMB and MVS, followed by detailed magnetic finite element analysis (FEA) using commercial validated tools for the final performance prediction. With analytical validation of performance, detail designs are developed and hardware fabricated. Hardware testing is done to validate performance predictions and alignment with system requirements. The PMB performance results include testing of stiffness capability. These characteristics are used to validate the integration requirements for load capability and deflection during static load events, all in relation to validating performance for use in the MDS system. This test data is used to validate the analysis approach used as well as to finalize the integration size of the PMB to meet the performance requirements of the MDS system. To identify rotor operating speed and rotor vibration magnitude and frequencies, the MVS is tested for sensing rotor motion rate and frequency, including sub-synchronous and super synchronous frequencies. Identifying data reduction needs, i.e. how data is compiled and presented to focus on specific areas of interest, is also critical to determine the vibration characteristic of specific events happening in the ESP, such as bearing wear or dynamic fluid changes. Testing also includes variations in tubing materials to assess performance impact. These technologies offer bearing and sensor technologies that enhance ESP reliability and active performance monitoring. The PMBs offer a contact-less bearing system that does not require lubrication, can operate with large clearances to allow free fluid flow, and has no operating life limits. The compact MVS offers rotor vibration diagnostics throughout the ESP, including between pump stages, for monitoring performance, detecting ESP mechanical issues or process fluid variations allowing immediately response to increase operational life.

A Predictive Model to Detect the Impending Electric Submersible Pump Trips and Failures

Trips and failures are common occurrences in the Electric Submersible Pump (ESP) systems. The random nature of these trips and failures will lead to low industry run-life and high workover costs for ESP companies and operators. To perform early detection and take corrective actions to handle the potential incidents, ESP operation data collected from downhole and surface sensors are used to perform diagnostics and prognostics to identify trips and failures. In this study, Principal Component Analysis (PCA) method serves as a pre-processing method to retain the most essential principal components to reevaluate the initial ESP system. For a single well system, the Squared Prediction Error (SPE) and Hotelling T-square statistic (T2) equations are employed for numerical visualization in the new principal component space and therefore detection of the potential ESP trips or failures. For the whole well group, the score plot of three principal components provides a solution that enables to distinguish different clusters of stable operation, trip and failure regions, and diagnose the upcoming ESP trips and failures. In this way, the predictive model is bulit to continuously analyze the ESP operation and automatically perform health monitoring for any ESP system. This paper concludes that the predictive model has the potential to construct a real-time proactive surveillance system to identify dynamic anomalies and therefore predict developing trips or failures in the ESP system.