WO2008093054A2 - Systèmes et procédés pour surveiller un état et une performance de détecteur et d'actionneur - Google Patents

Systèmes et procédés pour surveiller un état et une performance de détecteur et d'actionneur Download PDF

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Publication number
WO2008093054A2
WO2008093054A2 PCT/GB2008/000260 GB2008000260W WO2008093054A2 WO 2008093054 A2 WO2008093054 A2 WO 2008093054A2 GB 2008000260 W GB2008000260 W GB 2008000260W WO 2008093054 A2 WO2008093054 A2 WO 2008093054A2
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WIPO (PCT)
Prior art keywords
signal
bounds
oilfield equipment
subsystem
subsystems
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Application number
PCT/GB2008/000260
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English (en)
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WO2008093054A3 (fr
Inventor
Jason D. Dykstra
Original Assignee
Hallibruton Energy Services, Inc.
Curtis, Philip Anthony
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.)
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Publication date
Priority claimed from US11/700,735 external-priority patent/US7574325B2/en
Priority claimed from US11/700,396 external-priority patent/US20080179056A1/en
Application filed by Hallibruton Energy Services, Inc., Curtis, Philip Anthony filed Critical Hallibruton Energy Services, Inc.
Publication of WO2008093054A2 publication Critical patent/WO2008093054A2/fr
Publication of WO2008093054A3 publication Critical patent/WO2008093054A3/fr

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    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B41/00—Equipment or details not covered by groups E21B15/00 - E21B40/00
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH DRILLING; MINING
    • E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B44/00—Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions

Definitions

  • the present application relates to monitoring complex systems such as automated equipment used in oilfields, and more particularly to monitoring sensor and actuator health and performance.
  • the invention relates to systems for monitoring sensor and actuator health and performance.
  • the invention also relates to methods to monitor system sensor and actuator health and performance
  • Modern oilfield rigs use automated equipment in many aspects of an operation.
  • a key element of such complex systems is the control and monitoring system.
  • These systems include sensors and other elements that signal a control unit in a feedback loop.
  • the control unit monitors the system, providing stability and ensuring the system operates within desired parameters.
  • Sensors are often placed at specific locations within a system to provide information necessary for the control unit to function. For example, on a drill rig, mud must be provided within specific parameters. Sensors monitor the flow rate of the mud, pressure, density, and other measurables, and this information is fed back to the control unit and/or to an operator who manually monitors the system for failures. Current systems normally rely on operators to take action when failure occurs.
  • the present innovations provide a system and method to monitor for failures in one or more subsystems (preferably physically coupled subsystems) in a larger system, and (in some embodiments) update the operator of failures or impending failures to improve process control. It also can include a system with process control knowledge to help operation of the equipment and reduce operator error.
  • the innovations include a plurality of subsystems (such as sensors or actuators, or combinations of parts) that can signal operation or state information. This information is used to determine if one or more subsystems are in or near failure mode.
  • subsystems such as sensors or actuators, or combinations of parts
  • a sensor of interest is selected, such as a flow rate sensor.
  • Other subsystems of the total system that are physically coupled to the flow rate sensor provide information that is transformed into data that is comparable to the output of the flow rate sensor. This information is compared, and discrepancies indicate that some sensor of the system may be failing or outside preferred operating conditions.
  • Operating conditions or bounds can be chosen or generated in a number of ways, including static, dynamic, or operationally dependent bounds. Bounds may be also be reevaluated in real time, in dependence, for example, on system dynamics.
  • subsystem signals are aggregated and transformed into comparable form so that discrepancies can be identified.
  • multiple physically coupled subsystems form a redundant check on one another so as to monitor each individual subsystem's health and performance.
  • actual subsystem (e.g., sensor or actuator) readings are compared to a model of the system dynamics, so actual subsystem operation can be compared to expected subsystem operation.
  • the controller can be designed to estimate sensor and actuator failures and 3date the operator through the interface.
  • the controller can also be designed with system intelligence which can be used to help the operator perform the job and reduce operator error.
  • an oilfield equipment monitoring system comprising: at least three oilfield equipment subsystems that are physically coupled to one another; a control system configured to receive signals from at least some of the oilfield equipment subsystems; and ! wherein the control system is configured to:
  • an oilfield equipment monitoring system comprising: at least three oilfield equipment subsystems that are physically coupled to one another; a control system configured to receive signals from at least some of the oilfield equipment subsystems; and wherein the control system is configured to check the respective readings of said multiple subsystems against each other to determine whether any subsystems have readings which are physically inconsistent with each other; and under at least some conditions, exclude the output of a respective subsystem which has been determined in said check of respective readings to be showing inconsistent output.
  • an oilfield equipment monitoring system comprising: at least three oilfield equipment subsystems that are physically coupled to one another; a control system configured to monitor one or more signals derived from the oilfield equipment subsystems; and wherein said signals from different oilfield equipment subsystems are compared to identify an oilfield equipment subsystem's signal that does not substantially agree with at least two other oilfield equipment subsystems' signals.
  • a method of monitoring an oilfield equipment system comprising the steps of: identifying a physical coupling among three or more oilfield equipment subsystems; monitoring a plurality of signals, each signal being associated with one of the three or more oilfield equipment subsystems; transforming one or more of the oilfield equipment subsystem signals into units associated with the type of physical coupling among the three or more oilfield equipment subsystems; comparing at least some of the signals; and indicating at least one oilfield equipment subsystem's signal that does not agree with at least two other oilfield equipment subsystems' signals.
  • a method of operating an oilfield equipment system comprising the steps of: controlling system operation using readings from multiple subsystems of the system; checking the respective readings of said multiple subsystems against each other to determine whether any subsystems have readings which are physically inconsistent with each other; and under at least some conditions, changing the controlling step to exclude the output of a respective subsystem which has been determined, in the checking step, to be showing inconsistent output.
  • a method for operating a system comprising the steps of: in a first procedure, monitoring a first sensor, and generating a first estimate of at least one parameter thereby; in a second procedure, monitoring a second sensor, and generating a second estimate of said parameter thereby; and comparing said first and second estimates to thereby selectively generate communications indicating undesired mismatch between said estimates.
  • a method of controlling a complex system comprising the steps of: monitoring signals associated with a plurality of nodes in the system; identifying a node from the plurality whose respective signal is outside an operation limit; and switching from a first mode of operation to a second mode of operation in dependence on which node of the plurality has been identified as having a signal outside the operational limit.
  • a method of monitoring an oilfield equipment system comprising the steps of: monitoring three or more signals at respective physical interfaces to at least one oilfield equipment subsystem, said signals being associated with physical states which are physically coupled but not identical; transforming one or more of said signals into a set of units associated with the type of physical coupling between the three or more, signals; and indicating any oilfield equipment subsystem signal which is physically inconsistent with others of said signals.
  • FIG. 1 shows one embodiment of the present innovations as implemented in an exemplary hydrocarbon well drilling rig site.
  • FIG. 2 shows an example of actuator slippage.
  • FIG. 3 shows a sand and liquid slurry system consistent with implementing an embodiment of the present innovations.
  • FIG. 4 shows a detail of the liquid supply side of the sand and liquid slurry system consistent with implementing an embodiment of the present innovations.
  • FIG. 5 shows a control diagram of a blender unit consistent with an embodiment of the present innovations.
  • FIG. 6 shows an example implementation of redundant sensor checking relative to dynamic links of a physical system, consistent with an embodiment of the present innovations.
  • FIG. 1 shows an example system in which embodiments of the present innovations can be implemented.
  • This example shows an oilfield drilling system 100, including a drill string 102, and downhole tool 104.
  • Drilling system 100 also includes pump system 106 which controls insertion of materials downhole, such as drilling mud for cooling and removal of debris, or other slurries (such as sand and water combinations) for various tasks.
  • materials downhole such as drilling mud for cooling and removal of debris, or other slurries (such as sand and water combinations) for various tasks.
  • the drilling system 100 includes sensors such as flow meter 101 that monitor and characterize the performance of various subsystems. This information is used, often by an operator, but also by automated systems, to determine when performance is outside desired bounds or failure occurs or is about to occur.
  • Figure 1 also shows one embodiment of the present innovations as an oilfield equipment system 100 which can be comprised of a pump system 106, a rotary flow control valve with an actuator/position indicator assembly as 103, a flow meter 101, a drill string 102, a drill bit down hole at 104, and a plurality of signal operations, computations, and other actions that can be configured with a general purpose computer (not shown) that is monitoring system 100.
  • Pump 106 can pump a drilling fluid through control valve 103 and through flow meter 101, then down drill string 102 through bit 104 and then can re-circulate the fluid back to itself.
  • the pump, the valve, and the meter are physically coupled by the drilling fluid.
  • Pump 106 can send a pump speed signal to stage 106A for transformation of the speed signal to a volumetric fluid flow rate, in say, gallons per minute ("GPM").
  • Flow meter 101 can send a flow rate signal to stage 101A for transformation to a volumetric fluid flow rate in GPM.
  • Valve 103 position indicator can send a signal to stage 103 A for transformation of the "% OPEN" signal of the valve to a volumetric flow rate in GPM.
  • Stage 107 can compare the three transformed signals for agreement in stages 107 A, 107B, and 107C. If one signal is found to disagree with the other two signals, an output signal can be made to notify an operator that the particular component that is not in agreement needs maintenance or attention.
  • Figure 2 shows a top view of an example rotary-actuated valve 206 that is operated by an actuator attached to the valve shaft 208, which opens and closes the valve by rotating the valve shaft according to a signal.
  • an actuator attached to the valve shaft 208
  • the actuator was signaled to move the valve a first amount 202, while the actual valve movement 204 was less.
  • the difference in movement can represent a difference in the signaled angle of rotation.
  • a valve can be vertically actuated and the difference can represent the error in valve stroke.
  • reports of valve movement can depend on signaled movement 202 and not actual movement 204.
  • failure to obtain accurate information about actual subsystem performance can harm production and propagate to other parts of the system.
  • subsystems of a larger- system preferably physically coupled subsystems, or subsystems that can otherwise be characterized in terms of one another
  • subsystems that affect a sensor or actuator are compared in order to characterize a given sensor or actuator's current, actual level of performance in order to determine if the sensor or actuator is performing within accepted bounds.
  • Inputs and outputs that affect (or are affected by) the subsystem are, in preferred embodiments, transformed into comparable sensor or actuator states to monitor sensor or actuator performance.
  • some or all the sensors outputs can be transformed into the same units or data as one of the sensors, to determine if that sensor is sending accurate signals of the subsystem which it monitors.
  • the present innovations provide a way to redundantly check each individual sensor of the group of sensors.
  • This redundant checking can be performed in a number of ways, uch as by selecting a sensor of interest and transforming all other sensor data into data that is comparable to the sensor of interest, or by transforming all sensor data into a single form so their signals can be aggregated and compared, for example, by checking standard deviations between signals, spread, and other statistical analysis.
  • a sensor or actuator of interest can be viewed as being coupled
  • Transformation of the various signals is derived from physical system dynamics.
  • the transformed signals of multiple coupled subsystems effectively become redundant sensors.
  • subsystem performance, as determined by one or more of the redundant sensors is compared to predetermined or dynamic bounds to determine if the subsystem is performing properly, for example, or close to or in failure. These bounds can be static or operationally dependent, and/or reevaluated in real time. Other performance constraints can be created from the dynamic limits of the physical system.
  • the physical system operational envelop can be defined, for.
  • a state vector of first order derivatives ⁇ i.e., change over time which can be used to define acceptable operational ranges of the sensors.
  • Such a mechanism can be used to detect, for example, when a sensor registers severe change, which can indicate either a subsystem in failure, or sensor malfunction.
  • Operational bounds or envelopes can also be dynamically reset, for example, relative to physical system dynamics.
  • Further embodiments of the present innovations include interfaces wherein results of one or more of the redundant sensors are reported to an operator, preferably coupled with information to help the operator or give assistance in detecting, for example, when corrective action needs to be taken and reduce operator error.
  • sensor information is used in feedback loops to aid in controlling systems to provide stability and to ensure that a system operates within acceptable limits or bounds.
  • data from a plurality of sensors are used by a control unit in a feedback and control system
  • the present innovations allow for more robust control in several ways. For example, in ne example embodiment, if a plurality of sensors are used to inform a control unit, and if one of those sensors goes out of operational bounds, that sensor's signal, can be removed from input to the control unit.
  • the control algorithm used in the control system can be modified to operate without the data from the sensor that was removed.
  • a sensor can experience temporary periods when its signal is outside of operational bounds, indicating bad sensor data, for example.
  • the sensor can be temporarily removed from input to the control unit, and later, when it has resumed operation that is within operational bounds, its signal can be reintroduced to the control unit.
  • a sand and liquid blending system 300 that includes a sand supply 302, a liquid supply 304, a blender 306, and a pump system 308.
  • a sand and liquid blending system 300 that includes a sand supply 302, a liquid supply 304, a blender 306, and a pump system 308.
  • various parts of the system are physically coupled.
  • FIG. 4 shows a detailed view of the liquid supply subsystem 400 of the system shown generally in Figure 3.
  • Liquid supply tank 304 sends liquid to blender 306 which outputs to a pump system 308.
  • Output from liquid supply tank 304 is monitored by a flow sensor 402 and is controlled by a valve 404. Downstream of blender 306, another flow sensor 406 monitors output to the pumping system 308.
  • valve 404 can be used to express rate as a function of the valve flow constant, the valve-open angle and drive signal applied to the valve 404.
  • the blender 306 and flow sensor 406 can, together, provide rate as a function of the height, the change in height over time, the area, density, and output flow of the blender.
  • rate can be expressed at the pumping system 308 in terms of the efficiency, output curve, and RPMs of the pumping system.
  • these multiple functions that result in flow rate determinations effectively form a system or plurality of redundant sensor measurements for flow rate measurements (in this example).
  • these values are compared to the sensor 402 to determine if the sensor 402 is operating correctly. For example, if the subsystems that also indirectly measure the flow rate yield a relatively consistent flow rate, and if sensor 402 differs significantly from this rate, then the accuracy of sensor 402 is called into question.
  • all five of these subsystems can be aggregated and statistically analyzed, for example, by measuring their standard deyiation, and/or, .identifying, any individual subsystem that differs from the other readings beyond a predetermined threshold or envelope. Other statistical manipulation or analysis of these data is also possible.
  • the various data of the subsystems can be dynamically transformed into an interested subsystem's performance.
  • the disclosed sensor checking and dynamic characterization system can be used in other ways as well. For example, in one embodiment, if a sensor is found to operate outside of predetermined (or dynamic, or operationally dependent) bounds, that sensor can be removed. In other embodiments, the sensor can be temporarily removed, and reintroduced when its operation returns within desired limits. Changes in the sensor operation over time, as detected by the present innovations, can also exceed limits as described above. In other embodiments, a sensor or subsystem might go out of operational bounds and be removed from input to the control algorithm that maintains stability in the system. In some embodiments, the sensor's input is simply emoved, and may or may not be reintroduced when the sensor is once again found to be operating within desired limits.
  • the sensor's input is removed (temporarily or permanently) and, additionally, the control algorithm is modified to account for the reduced input information.
  • some cement mixing systems can be designed to switch from being controlled using density information (i.e., information from density sensors/calculations) to being controlled using volume information i.e., information from volume sensors/calculations).
  • density information i.e., information from density sensors/calculations
  • volume information i.e., information from volume sensors/calculations
  • the innovative system can switch to density mode and use the changed input in its control algorithm.
  • an operator would be informed and may have to take necessary actions, such as controlling some levels manually.
  • FIG. 5 shows a further detail of the blending system 306 shown in Figure 3, showing the control loops that maintain stability in the respective systems.
  • a density sensor 502, a height sensor 504, a water sensor 506, and a sand sensor 508 are shown in context of a control system diagram.
  • Each control loop includes a control unit or algorithm, represented by PID (proportional, derivative, integral) controller (shown variously as units 502A-508A) that is associated with elements in the forward path, between the error signal and the control signal. (Other types of control models can of course be implemented, and the present example is illustrative only.)
  • the depicted system includes signals that represent the error between the dynamic models (502B- 508B) and the outputs of their respective sensors.
  • Each sensor measures some property that is also being dynamically modeled.
  • the input to the dynamic models from the PIDs are the amounts needed to correct the dynamic models so they match their respective sensor readings.
  • Each control loop also has a ynamic model (502B-508B) of the system or subsystem on which the control unit imposes stability.
  • the other inputs and outputs can be dynamically transformed into an interested system's performance.
  • the mass rate error signal can be dynamically transformed (in the same way that readings were transformed into liquid flow rates, above) to achieve an expected sand rate 502C.
  • the volumetric rate error signal can be transformed into an expected sand rate 504C.
  • the sand screw dynamic model gives a measure of the sand rate by taking into account the drive signal, the speed of the screw, and other known dynamics.
  • this system contains an adaptive parametric control (APC) to map nonlinearities.
  • APC adaptive parametric control
  • the APC is used in examining actuator performance and looking for problems.
  • these innovative concepts include, in a first embodiment, modeling of the dynamics of a system as expected in normal operation; modeling the dynamics of the system in real time; and comparing the two models to determine if a failure has occurred.
  • the present innovations include embodiments that use a learning algorithm to determine a parameter in a model of the dynamics; and using that parameter to detect system failure, such as by monitoring that parameter (or systems from which that parameter can be derived) during operation.
  • a model of failure behavior is generated.
  • the model of system failure is compared to the system as the system is running. This comparison can provide additional information, about both the failure model and the system dynamics.
  • the dynamics of valve slop (or mismatch between a valve ontrol signal and actual valve performance) may be well known.
  • the model of valve slop can be compared to the system dynamics while the system is running. For example, the deadband of the valve and the valve coefficient (or an aspect of the control signal) can be mapped so as to increase the accuracy of the valve slop model. This will provide information about the wear that is occurring and the flow characteristics through the valve.
  • the dynamics of the system are mapped while the system is running, but without a model of how the system fails or misbehaves.
  • the mapped dynamics are compared to a threshold value, such as one or more dynamic performance specifications, to see if the mapped system dynamics are within bounds.
  • a threshold value such as one or more dynamic performance specifications
  • the number of sensors and observable states would determine how many properties could be mapped to the dynamic model or thresholds.
  • a learning algorithm (such as a neural network) determines normal operating behavior. The model created by the learning algorithm can be compared to sensor data to determine how well the system is tracking "normal" behavior, and to thereby detect failures.
  • a sensor analysis program 510 such as a computer program product on a computer readable medium that analyzes the readings, as described above.
  • the sensor readings can be monitored for behavior so as to indicate (for example, by a signal to an operator or by automated alarm or controls) when a given sensor is operating outside predetermined bounds (whether dynamic or static).
  • Figure 6 shows sensor checking relative to dynamic limits to the physical system.
  • the known operational envelop shown as lower bound (LB) and upper bound (UB) are used to check the sensor and actuator performance relative to the current operating position and derivative of that position. The current will determine the allowable sensor envelope.
  • the rate of change of the tub level sensor should output a signal value that is close to what would be expected for that rate of change of volume.
  • Figure 6 includes a plurality of levels of checking.
  • the water rate includes three separate levels of performance checks.
  • the water rate is directly measured, for example, by a flow meter or other means of checking movement of the water. Lower bounds and upper bounds are set for the water rate, and if the water rate exceeds these bounds, a signal indicating unacceptable behavior or performance can be sent.
  • a second condition for bounding the water rate is based on the commands sent to the actuator that controls the water rate. Known changes- in...,. * . the actuator correspond to known changes in the water rate. If a given command is sent, and yet the water rate does not respond as expected (within bounds), then a signal indicating this behavior can be sent.
  • the change in the water rate can be used to set bounds on the water rate.
  • the dynamic behavior of the water rate can, for example, have known bounds outside which unacceptable behavior is indicated. For example, if it is known that the change in water rate should not exceed d(water rate)/dt, and if checks on the water rate indicate that the dynamic behavior of the water rate exceeds preset bounds, then a signal indicating such condition can be sent. All these bounds or indications of the water rate can be used, for example, as checks on the water rate.
  • the water rate, or the water actuator command, or the dynamic changes in the water rate may be inferred from data from other (coupled) systems.
  • the data from the coupled systems is preferably transformed into one of the three example measures for acceptable water rate behavior, and compared to the predetermined bounds.
  • the present innovations include, in at least one embodiment, a multi-layered solution in which all the sensors and actuators are combined with system intelligence to determine failure, or likelihood of failure. (For example, bounds can indicate failure, or conditions that are known or suspected to lead to failure.) This provides an improved view of system health and performance, and also permits signaling to operators so that failures are prevented or caught more quickly, reducing operator error.
  • At least three oilfield equipment subsystems that are physically coupled to one another, a control system configured to receive signals from at least some of the oilfield equipment subsystems, and wherein the control system is configured to: transform one or more of the oilfield equipment subsystem signals into units associated with the type of physical coupling among the three or more oilfield equipment subsystems, compare at least some of the signals and indicate at least one oilfield equipment subsystem's signal that does not agree with at least two other oilfield equipment., subsystems' signals.
  • An oilfield equipment monitoring system comprising at least three oilfield equipment subsystems that are physically coupled to one another, a control system configured to receive signals from at least some of the oilfield equipment subsystems, and wherein the control system is configured to check the respective readings of said multiple subsystems against each other to determine whether any subsystems have readings which are physically inconsistent with each other; and under at least some conditions, exclude the output of a respective subsystem which has been determined in said check of respective readings to be showing inconsistent output.
  • an oilfield equipment monitoring system comprising at least three oilfield equipment subsystems that are physically coupled to one another, a control system is configured to monitor one or more signals derived from the oilfield equipment subsystems and wherein signals from different oilfield equipment subsystems are compared to identify an oilfield equipment subsystem's signal that does not substantially agree with at least two other oilfield equipment subsystems' signals.
  • a method of monitoring an oilfield equipment system comprising the steps of identifying a physical coupling among three or more oilfield equipment subsystems, monitoring a plurality of signals, each signal being associated with one of the three or more oilfield equipment subsystems, transforming one or more of the oilfield equipment subsystem signals into units associated with the type of physical coupling among the three or more oilfield equipment subsystems, comparing at least some of the signals, and indicating at least one oilfield equipment subsystem's signal that does not agree with at least two other oilfield equipment subsystems' signals.
  • a method of operating an oilfield equipment system comprising the steps of controlling system operation using readings from multiple subsystems of the system, checking the respective readings of said multiple subsystems against each other, to determine!:!: whether any subsystems have readings which are physically inconsistent with each other, and under at least some conditions, changing the controlling step to exclude the output of a respective subsystem which has been determined, in the checking step, to be showing inconsistent output.
  • a method for operating a system comprising the steps of in a first procedure, monitoring a first sensor, and generating a first estimate of at least one parameter thereby; in a second procedure, monitoring a second sensor, and generating a second estimate of said parameter thereby; and comparing said first and second estimates to thereby selectively generate communications indicating undesired mismatch between said estimates.
  • a method of controlling a complex system comprising the steps of monitoring signals associated with a plurality of nodes in the system, identifying a node from the plurality whose respective signal is outside an operation limit, and switching from a irst mode of operation to a second mode of operation in dependence on which node of the plurality has been identified as having a signal outside the operational limit.
  • a method of monitoring an oilfield equipment system comprising the steps of monitoring three or more signals at respective physical interfaces to at least one oilfield equipment subsystem, said signals being associated with physical states which are physically coupled but not identical, transforming one or more of said signals into a set of units associated with the type of physical coupling between the three or more signals, and indicating any oilfield equipment subsystem signal which is physically inconsistent with others of said signals.
  • the disclosed innovations can be applied in a number of areas outside the oil industry, though the preferred context is the oil industry.
  • any detection and signaling apparatus that receives information about a system and that can in any way convey that information could be implemented into the present innovations.
  • the parameters that are monitored can also vary widely, including density, flow, volume, various derivatives, mass transfer, temperature, pressure, and any other characterizable parameter.
  • the present innovations are described in the context of a sand and liquid slurry, this is only an example context. Other contexts would also benefit from the present innovations, where preferably physically coupled subsystems can be characterized in a common way. In another example, the present innovations are only one part of a multi-level filtering system, that can include other checks on system behavior.
  • the systems being monitored are characterized as being
  • Coupled Any transfer of information, matter and/or energy between two systems is included in the definition of “coupled” as that term is used in this application. Further, any two systems that can be characterized in terms of one another, are also considered to be “coupled” within the context of this application.
  • the current innovations are characterized in the context of oilfield equipment.
  • Such equipment includes a variety of oilfield supply systems, downhole tools, above-ground equipment, such as valves, screws, pumps, agitators, and other tools associated with oilfield operations.
  • the signals associated with the oilfield equipment subsystems are described as being transformed into "units" associated with the physical coupling that exists among the subsystems.
  • These units are understood to include not only physical units (such as mass, volume, rates, or other- physical quantities or one or more derivatives or quantities thereof), but also "unitless” mathematical quantities or expressions which are consistent with or associated with the physical coupling (i.e., are derivable from the type of physical coupling) in any way.
  • the units or expressions into which signals are transformed for comparison could include normalized quantities where "physical" units have been divided out of the expression. These units can also be monotonic expressions of one another, or another quantity.
  • signals associated with the various subsystems can refer to, for example, a sensor reading, a control signal sent to a subsystem, a meter or other device that is affected by the physical coupling of the subsystem that can be monitored, or any other quantity associated with that subsystem that can be monitored in some way, and which can be expressed in terms hat are comparable to at least one other subsystem that is physically coupled with the first subsystem.

Abstract

L'invention concerne des systèmes et des procédés pour évaluer un état et une performance d'actionneurs et de détecteurs dans un système d'équipement de traitement. Dans un exemple, le système d'équipement comprend des sous-systèmes (de préférence, des sous-systèmes couplés physiquement), dont au moins certains sont caractérisables par des signaux transmis. Certains de ces signaux sont transmis sous une forme comparable et comparée, de façon à identifier des signaux qui sont à l'extérieur de liaisons fonctionnelles.
PCT/GB2008/000260 2007-01-31 2008-01-24 Systèmes et procédés pour surveiller un état et une performance de détecteur et d'actionneur WO2008093054A2 (fr)

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US11/700,396 2007-01-31
US11/700,735 2007-01-31
US11/700,735 US7574325B2 (en) 2007-01-31 2007-01-31 Methods to monitor system sensor and actuator health and performance
US11/700,396 US20080179056A1 (en) 2007-01-31 2007-01-31 Systems for monitoring sensor and actuator health and performance

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WO2017086949A1 (fr) * 2015-11-18 2017-05-26 Halliburton Energy Services, Inc. Traitement de données optiques d'outil à deux capteurs via une standardisation par capteur maître
WO2017116875A1 (fr) * 2015-12-31 2017-07-06 General Electric Company Système et procédé pour l'identification d'une défaillance temporaire de capteur et le redressement après cette dernière

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