WO2016153895A1 - Système et procédé permettant de surveiller une pompe électrique submersible - Google Patents

Système et procédé permettant de surveiller une pompe électrique submersible Download PDF

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Publication number
WO2016153895A1
WO2016153895A1 PCT/US2016/022764 US2016022764W WO2016153895A1 WO 2016153895 A1 WO2016153895 A1 WO 2016153895A1 US 2016022764 W US2016022764 W US 2016022764W WO 2016153895 A1 WO2016153895 A1 WO 2016153895A1
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WO
WIPO (PCT)
Prior art keywords
deviation
pump
health index
critical event
processor
Prior art date
Application number
PCT/US2016/022764
Other languages
English (en)
Inventor
Emmanuel Coste
Neil EKLUND
Original Assignee
Schlumberger Technology Corporation
Schlumberger Canada Limited
Services Petroliers Schlumberger
Schlumberger Technology B.V.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Schlumberger Technology Corporation, Schlumberger Canada Limited, Services Petroliers Schlumberger, Schlumberger Technology B.V. filed Critical Schlumberger Technology Corporation
Publication of WO2016153895A1 publication Critical patent/WO2016153895A1/fr

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Classifications

    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
    • E21B43/12—Methods or apparatus for controlling the flow of the obtained fluid to or in wells
    • E21B43/121—Lifting well fluids
    • E21B43/128—Adaptation of pump systems with down-hole electric drives
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
    • F04D—NON-POSITIVE-DISPLACEMENT PUMPS
    • F04D13/00—Pumping installations or systems
    • F04D13/02—Units comprising pumps and their driving means
    • F04D13/06—Units comprising pumps and their driving means the pump being electrically driven
    • F04D13/08—Units comprising pumps and their driving means the pump being electrically driven for submerged use
    • F04D13/10—Units comprising pumps and their driving means the pump being electrically driven for submerged use adapted for use in mining bore holes
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B47/00—Survey of boreholes or wells
    • E21B47/008—Monitoring of down-hole pump systems, e.g. for the detection of "pumped-off" conditions
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
    • F04D—NON-POSITIVE-DISPLACEMENT PUMPS
    • F04D15/00—Control, e.g. regulation, of pumps, pumping installations or systems
    • F04D15/0088—Testing machines
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G05B23/0254—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2260/00—Function
    • F05D2260/80—Diagnostics
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
    • F05D2270/00—Control
    • F05D2270/70—Type of control algorithm
    • F05D2270/709—Type of control algorithm with neural networks
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/25—Pc structure of the system
    • G05B2219/25428—Field device

Definitions

  • Electric submersible pumps may be deployed for any of a variety of pumping purposes, and often comprise a submersible pump powered by a submersible motor which is protected by a motor protector.
  • a substance e.g., hydrocarbons in an earthen formation
  • an ESP may be implemented to artificially lift the substance.
  • Downhole ESPs and their motors operate in harsh environments and may fail over time. Even if such equipment does not completely fail, the performance of the motor and ESP may be impaired due to, for example, mechanical wear or failure caused by bearing wear, impeller wear, and the like, as well as electrical failures.
  • sensors or other detectors are used to detect pumping system failure and to output a warning regarding pumping system failure.
  • some well-related pumping applications employ sensors to monitor aspects of the pumping system operation, and surveillance engineers are employed to monitor the data and to make decisions regarding pumping system operation based on that data.
  • such techniques may not address pumping system issues soon enough and may be subject to errors, including raising false alarms of ESP degradation, which may result in an overreaction by an operator, such as ceasing operation or removing the ESP from the pumping environment prematurely.
  • Certain embodiments of the present disclosure are directed toward a system for monitoring an electric submersible pump.
  • the system includes an electric submersible pump and a pump monitoring device configured to monitor at least one variable associated with performance of the pump.
  • the system also includes a processor configured to receive data from the pump monitoring device related to the performance of the pump, determine a health index of the pump based at least in part on the data from the pump monitoring device, and as a result of the health index deviating from a defined operating range, determine whether a critical event has occurred proximate in time to the deviation.
  • Other embodiments of the present disclosure are directed toward a method of monitoring an electric submersible pump.
  • the method includes obtaining data related to performance of the pump, determining a health index of the pump based at least in part on the data from the pump monitoring device, and as a result of the health index deviating from a defined operating range, determining whether a critical event has occurred proximate in time to the deviation.
  • Still other embodiments of the present disclosure are directed toward a non-transitory computer-readable medium containing instructions that, when executed by a processor, cause the processor to carry out one or more of the methods or processes described herein.
  • Figure 1 illustrates an example of a pumping system and an associated control and monitoring system deployed in a wellbore environment in accordance with various embodiments of the present disclosure
  • Figure 2 shows an example of a pump life timeline including exemplary critical event occurrences in accordance with various embodiments of the present disclosure
  • Figure 3 shows an example flow chart of a method for monitoring a pumping system in accordance with various embodiments of the present disclosure
  • Figure 4 shows an example of health indicator modeling methodologies for monitoring a pumping system in accordance with various embodiments of the present disclosure
  • Figure 5 shows an example output of a system in accordance with various embodiments of the present disclosure
  • Figure 6 shows a block diagram of a system for monitoring a pumping system in accordance with various embodiments of the present disclosure.
  • references to "based on” should be interpreted as “based at least on.” For example, if the calculation of parameter X is "based on" value Y, then the calculation of X is based at least on the value of Y; the calculation of X may be based on other values as well.
  • Coupled or “couples” is intended to mean either an indirect or direct connection.
  • the connection between the components may be through a direct engagement of the two components, or through an indirect connection that is accomplished via other intermediate components, devices and/or connections. If the connection transfers electrical power or signals, the coupling may be through wires or other modes of transmission.
  • one or more components or aspects of a component may be not displayed or may not have reference numerals identifying the features or components that are identified elsewhere in order to improve clarity and conciseness of the figure.
  • the present disclosure generally relates to a system and method for monitoring a pumping system, such as an electric submersible pump (ESP).
  • ESP electric submersible pump
  • Systems and methods are described that leverage an automated critical event detection algorithm to detect and identify external critical events.
  • the identified critical event(s) may be used in conjunction with an output of one or more failure prediction algorithm(s) to flag, discard, and or provide further contextual information regarding corresponding anomalies.
  • the systems and methods described in the present disclosure may be applied to a wide variety of oilfield components, including artificial lift components. The ability to predict the failure of components can give the operator time to mitigate the associated financial impact.
  • ESPs may be deployed for any of a variety of pumping purposes. For example, where a substance does not readily flow responsive to existing natural forces, an ESP may be implemented to artificially lift the substance.
  • Commercially available ESPs such as the RED ATM ESPs marketed by Schlumberger Limited, Houston, Tex.
  • ESPs may find use in applications that require, for example, pump rates in excess of 4,000 barrels per day and lift of 12,000 feet or more.
  • the ESP system 100 includes a network 101, a well 103 disposed in a geologic environment, a power supply 105, an ESP 1 10, a controller 130, a motor controller 150, and a variable speed drive (VSD) unit 170.
  • the power supply 105 may receive power from a power grid, an onsite generator (e.g., a natural gas driven turbine), or other source.
  • the power supply 105 may supply a voltage, for example, of about 4.16 kV.
  • the well 103 includes a wellhead that can include a choke (e.g., a choke valve).
  • a choke e.g., a choke valve
  • the well 103 can include a choke valve to control various operations such as to reduce pressure of a fluid from high pressure in a closed wellbore to atmospheric pressure.
  • Adjustable choke valves can include valves constructed to resist wear due to high velocity, solids-laden fluid flowing by restricting or sealing elements.
  • a wellhead may include one or more sensors such as a temperature sensor, a pressure sensor, a solids sensor, and the like.
  • the ESP 1 10 includes cables 1 1 1, a pump 1 12, gas handling features 1 13, a pump intake 1 14, a motor 1 15 and one or more sensors 1 16 (e.g., temperature, pressure, current leakage, vibration, etc.).
  • the well 103 may include one or more well sensors 120, for example, such as the commercially available OpticLineTM sensors or WellWatcher BriteBlueTM sensors marketed by Schlumberger Limited (Houston, Tex.). Such sensors are fiber-optic based and can provide for real time sensing of downhole conditions. Measurements of downhole conditions along the length of the well can provide for feedback, for example, to understand the operating mode or health of an ESP.
  • Well sensors may extend thousands of feet into a well (e.g., 4,000 feet or more) and beyond a position of an ESP.
  • the controller 130 can include one or more interfaces, for example, for receipt, transmission or receipt and transmission of information with the motor controller 150, a VSD unit 170, the power supply 105 (e.g., a gas fueled turbine generator or a power company), the network 101, equipment in the well 103, equipment in another well, and the like.
  • the controller 130 may also include features of an ESP motor controller and optionally supplant the ESP motor controller 150.
  • the motor controller 150 may be a commercially available motor controller such as the UniConnTM motor controller marketed by Schlumberger Limited (Houston, Tex.).
  • the UniConnTM motor controller can connect to a SCADA system, the espWatcherTM surveillance system, etc.
  • the UniConnTM motor controller can perform some control and data acquisition tasks for ESPs, surface pumps, or other monitored wells.
  • the UniConnTM motor controller can interface with the Phoenix monitoring system, for example, to access pressure, temperature, and vibration data and various protection parameters as well as to provide direct current power to downhole sensors.
  • the UniConnTM motor controller can interface with fixed speed drive (FSD) controllers or a VSD unit, for example, such as the VSD unit 170.
  • FSD fixed speed drive
  • the controller 130 may include or be coupled to a processing device 190.
  • the processing device 190 is able to receive data from ESP sensors 1 16 and/or well sensors 120.
  • the ESP sensors 116 and/or well sensors 120 may be situated in various locations among the system 100.
  • These sensors 116, 120 may be used to measure various parameters disclosed above, such as drive current, motor temperature, pump intake pressure, pump discharge pressure, static intake pressure, drive frequency, pump flow rate, and the like.
  • the sensors 116, 120 may be generally referred to as pump monitoring devices, and they may produce data indicative of values of the various parameters described above for subsequent processing.
  • the processing device 190 analyzes the data received from the sensors 1 16 and/or 120, possibly with the addition of sensors from the VSD 170 and the controller 130, to provide enhanced monitoring of the ESP 110, which may then be used to control the operation of the ESP 110 to prolong its life and/or avoid downtime of the ESP 110, to generate various alerts or alarms, to avoid generation of false indications of declining system health or performance, and/or to take other remedial action relating to the ESP 110.
  • the processing device 190 calculates or generates a health index of the ESP 110. The health index may be calculated based on a failure prediction algorithm developed from a historical analysis of pump sensor data using machine learning or other adaptive learning techniques.
  • the health index may also be calculated based on a physics-based model of the pump. Certain examples of the present disclosure leverage both analysis of historical sensor data using adaptive learning techniques and a physics-based model to calculate the health index for the ESP 1 10. It should be appreciated that sensor data may be, for example, data received by the processing device 190 from sensors 1 16 and/or 120.
  • the processing device 190 In addition to generating the health index, the processing device 190 identifies a defined operating range (e.g., a range of values), a health index inside of which indicates that the ESP 1 10 is in a normal or healthy range of operation. Conversely, when the health index deviates from the defined operating range that typically indicates that the ESP 1 10 is in danger of failure, at which point an automated remedial action may occur, or an operator may be alerted and may instigate a remedial or corrective action for the ESP 1 10.
  • a defined operating range e.g., a range of values
  • critical events may occur during the lifespan of the ESP 1 10 that may anomalously impact the health index; that is, these critical events are not actually indicators of the integrity of the pump, although they may still impact data acquired related to the pump (e.g., from sensors 1 16 and/or 120).
  • Critical events may include, but are not limited to, insufficient lift, dead head (either surface or downhole), the pump being off, and gas or sand interference.
  • critical events refer to low-flow events, which compromise the cooling of the motor 1 15 in particular.
  • the processing device 190 also identifies the occurrence of such low-flow critical events, also based on analysis of data from sensors 1 16 and/or 120.
  • embodiments of the present disclosure determine whether a critical event has occurred proximate in time to a deviation of the health index from the defined operating range. That is, if the processing device 190 may both calculate the health index and detect critical events. Then, if a deviation of the health index occurs, the processing device 190 is able to ascertain whether a critical event has occurred contemporaneously (or nearly contemporaneously) that impacted the health index in an anomalous manner. If the processing device 190 determines that the deviation of the health index was caused by the critical event, the deviation may be flagged or discarded.
  • the processing device 190 will generate an alert or an alarm to a user when a deviation of the health index from the defined operating range occurs.
  • the processing device 190 will not generate such an alert or alarm where the deviation is caused by a critical event, reducing the number of false alarms that an operator or user must assess and address.
  • a deviation of the health index may result in a remedial action (e.g., adjusting operation of the ESP 110) may be automatically taken.
  • the processing device 190 will not cause such remedial action to be carried out where the deviation is caused by a critical event, reducing the amount of unnecessary ESP 110 downtime or time in which ESP 1 10 operation is altered.
  • the detection of a deviation of the health index from the defined operating range leading to an alarm or alert may be presented to a user such as a surveillance center employee or a well site operator through a display device (not shown) coupled to the processing device 190, through a user device (not shown) coupled to the network 101, or other similar manners.
  • a user such as a surveillance center employee or a well site operator
  • the processing device 190 may also be referred to as executing a pump monitoring engine to carry out various functionality of that engine described herein.
  • processing and event detection may be carried out at the well site, at a remote surveillance center, and in any number of various centralized and distributed arrangements, such as through cloud computing and over a cloud.
  • the network 101 comprises a cellular network and the user device is a mobile phone, a smartphone, or the like.
  • the detection of a deviation of the health index from the defined operating range not attributable to a critical event may be transmitted to one or more users physically remote from the ESP system 100 over the cellular network 101.
  • the transmission or alert may be a warning of varying severity that a fault, failure, or degradation in ESP 1 10 performance is expected.
  • certain embodiments of the present disclosure may include taking a remedial or other corrective action in response to detection of an event that may lead to a decrease in ESP 1 10 performance or to an outright failure of the ESP 1 10.
  • the action taken may be automated in some instances, such that detection of a particular type of event, or deviation of the health index, automatically results in the action being carried out.
  • Actions taken may include altering ESP 1 10 operating parameters (e.g., operating frequency) or surface process parameters (e.g., choke or control valves) to prolong ESP 1 10 operational life, stopping the ESP 1 10 temporarily, and providing a warning to a local operator, control room, or a regional surveillance center.
  • FIG. 2 demonstrates an exemplary lifespan of an ESP 1 10, which begins with its installation at 200 and ends with its failure at 220.
  • one or more critical events 210a, 210b, 210c may occur.
  • These critical events can include, but are not limited to, reservoir changes (such as gas, sand, etc.), human operational changes, or completion changes (downhole or surface restrictions).
  • These events are unexpected in the majority of cases, but nevertheless affect the diagnostics of the failure prediction algorithm, namely the calculation of the health index, and may generate alarms relating to an impending failure of the pump in conventional pump health monitoring systems.
  • a low flow event such as insufficient lift or dead head which may trigger rise in heat impacting the underlying model used by the prediction algorithm.
  • systems and methods of the present disclosure combine an automated event detection algorithm with a failure prediction algorithm to identify and report anomalies caused by such critical events.
  • those anomalous deviations of the calculated health index are discarded or flagged, thus causing an alarm not to be raised, which, if raised, may be misleading since a critical event— rather than actual degradation of pump health— led to the deviation.
  • sensor data 330 is obtained from one or more of a downhole gauge 310 and surface data 320, which may include data indicative of wellhead temperature, wellhead pressure, electrical measurements, and the like.
  • the sensor data 330 is directed to failure prediction algorithm or model 340 and to an automated event detection algorithm 350.
  • the failure prediction algorithm 340 may analyze the received sensor data 330 to calculate a health index, which may be compared with one or more health indicators and/or threshold parameters 370 (e.g., a defined operating range, a health index outside of which indicates a likely failure of the ESP 1 10).
  • an alert 380 may be presented to a user.
  • Automated event detection 350 may analyze and/or compare received sensor data 330 to identify the occurrence of critical events 360.
  • an alert 380 may be presented to a user.
  • critical events 360 may include (but are not limited to): insufficient lift, dead head (surface or downhole), pump off, gas interference, and sand.
  • alerts 380 may be presented to the user in response to the output of both the failure prediction algorithm 340 and the automated event detection algorithm 350
  • systems and methods of the present disclosure may leverage both algorithms 340, 350 to improve the accuracy of alarms or alerts reported to the user, to reduce false or misleading alarms, and/or to reduce implementation of inappropriate remedial measures.
  • FIG. 4 shows an alternate example system 400.
  • the system 400 is generally similar to that shown in FIG. 3.
  • the failure prediction algorithm 340 is shown in further detail.
  • the failure prediction algorithm 340 includes both a physics-based modeling 410 of ESP 1 10 and a model based on historical data analysis 420 (e.g., machine learning). Examples of the present disclosure may leverage either or both types of failure prediction modeling 410, 420 to improve the overall failure prediction algorithm 340 and the accuracy of the calculated health index of the ESP 1 10.
  • a pump monitoring engine 430 e.g., executed by processing device 190 receives the outputs 470a, 470b, 470c of the failure prediction modeling 410, 420 as well as the event detection output 360.
  • FIG. 5 shows an example output 500 of the pump monitoring engine 430, which demonstrates the identification of critical events corresponding with deviations of the health index.
  • an alert or alarm based on the deviation of the health index is caused to not be raised, since the deviation is caused by an anomalous occurrence of the critical event, and not an actual degradation of ESP 1 10 health over time.
  • the example output 500 includes a health index 502 that corresponds to the output of the failure detection algorithm 340 and a defined operating range boundary 506.
  • the output 500 also includes critical events 504 represented by vertical dashed lines.
  • Anomalous deviations of the health index 502 above the threshold 506 are encircled, for example 508 and 508b.
  • some critical events e.g., 504a
  • other critical events e.g., 504b
  • the anomalous deviations may be flagged or discarded, for example as false alarms, since those deviations correspond to detected critical events 504, rather than an actual trend in the health index 502 above the threshold 506 resulting from a general decline in pump health over time.
  • FIG. 6 provides a system schematic of a motor monitoring system 600 in accordance with an embodiment.
  • the system 600 includes a processing resource 602 coupled to a non- transitory storage device 604.
  • the processing resource 602 may be a single processor, a multicore processor, a single computer (desktop computer, notebook computer, tablet computer, etc.) multiple computing devices coupled together in a network, or any other type of computing device.
  • the non-transitory storage device 604 includes volatile storage such as random access memory (RAM), non-volatile storage such as a magnetic storage (e.g., hard disk drive), an optical storage device (e.g., compact disc), or solid state storage (e.g., flash storage).
  • RAM random access memory
  • non-volatile storage such as a magnetic storage (e.g., hard disk drive), an optical storage device (e.g., compact disc), or solid state storage (e.g., flash storage).
  • the non- transitory storage device 604 may be a single device or collection of multiple devices, and be either stand-alone storage devices or storage devices contained within the processing resource 602. [0044]
  • the non-transitory storage device 604 contains pump assessment software 606 that, when executed by the processing resource 602, causes the processing resource to perform some or all of the functionality described herein.
  • the processing resource 602 may calculate or generate a health index of the ESP 1 10. As explained above, the health index may be calculated based on a failure prediction algorithm developed from a historical analysis of pump sensor data using machine learning or other adaptive learning techniques, based on a physics-based model of the pump, or a combination thereof.
  • the processing resource 602 also identifies a defined operating range in which a health index value indicates that the ESP 1 10 is in a normal or healthy range of operation.
  • the processing resource 602 also takes identified critical event occurrences into account in generating alerts 605 to a user based on a health index value that deviates from the defined operating range. If a critical event occurs proximate in time to a deviation of the health index from the defined operating range, the processing resource 602 may flag or discard the deviation, or otherwise inform a user that the deviation of the health index is not attributable to a decline in pump health, but rather is explained by the occurrence of a critical event.
  • alerts or alarms 605 also can be generated or caused to be generated by the processing resource 602 as described above.
  • the processing resource 602 alternatively or additionally may generate a feedback signal 603 to be provided to the VSD 170, for example, to change the operation of the motor 1 15 (e.g., reduce the speed of the motor, turn the motor off, etc.).
  • one or more I/O devices may be included to display alerts, generate alarms, receive operator input, and the like, to permit a user to receive the benefits enabled by embodiments of the present disclosure.
  • components of the motor monitor processing system 100 including the one or more I/O devices, may be coupled to a network for communication and connectivity purposes, and to allow sharing of data such as alarms or alerts with other computing systems coupled to the network.
  • the network may be or include the Internet, an intranet, a cellular network, a satellite network, etc.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Mining & Mineral Resources (AREA)
  • Geology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Geochemistry & Mineralogy (AREA)
  • Environmental & Geological Engineering (AREA)
  • Fluid Mechanics (AREA)
  • General Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Geophysics (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Mathematical Physics (AREA)
  • Control Of Positive-Displacement Pumps (AREA)
  • Structures Of Non-Positive Displacement Pumps (AREA)

Abstract

L'invention concerne des procédés et des systèmes permettant de surveiller une pompe. Ces procédés consistent à obtenir des données relatives à la performance de la pompe, à déterminer un indice de santé de la pompe sur la base au moins en partie des données provenant du dispositif de surveillance de pompe, et lorsque l'indice de santé s'écarte d'une plage de fonctionnement définie, à déterminer si un événement critique s'est produit à proximité au moment de l'écart. Des systèmes peuvent employer un ou plusieurs processeurs configurés pour exécuter des étapes similaires.
PCT/US2016/022764 2015-03-25 2016-03-17 Système et procédé permettant de surveiller une pompe électrique submersible WO2016153895A1 (fr)

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US62/138,207 2015-03-25

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WO2019014087A1 (fr) * 2017-07-10 2019-01-17 Schlumberger Technology Corporation Diagnostic automatique de systèmes d'appareil de forage
US10385857B2 (en) 2014-12-09 2019-08-20 Schlumberger Technology Corporation Electric submersible pump event detection
WO2019199433A1 (fr) * 2018-04-12 2019-10-17 Saudi Arabian Oil Company Prédiction de défaillances dans des pompes immergées électriques à l'aide d'une reconnaissance de motifs
WO2020123420A1 (fr) * 2018-12-11 2020-06-18 General Electric Company Procédés et systèmes pour la maintenance automatisée basée sur des conditions de systèmes mécaniques
WO2020131725A1 (fr) * 2018-12-16 2020-06-25 Sensia Llc Système de pompe
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