DIGITAL FLOWMETER FOR WELLBORES IMPLEMENTING ELECTRICAL SUBMERSIBLE PUMPS

Description

BACKGROUND OF THE DISCLOSURE

Wellbores may be drilled into a surface location or seabed for a variety of exploratory or extraction purposes. For example, a wellbore may be drilled to access fluids, such as liquid and gaseous hydrocarbons, stored in subterranean formations and to extract the fluids from the formations. Wellbores used to produce or extract fluids may be formed in earthen formations using earth-boring tools such as drill bits for drilling wellbores and reamers for enlarging the diameters of wellbores.

Some wellbores may implement electrical submersible pumps (ESPs) for facilitating flowing production fluids to the surface of the wellbore. Understanding flowrates of production fluids from the wellbore can be critical to optimizing the production of the well and oilfield. Generally, flowrates are measured using multi-phase flowmeters that directly measure the flowrate of each constituent phase of the production fluid, or else flowrates are determined using tank volume measurements based on an observing time period. In either case, it can be difficult, complex, and disruptive to production to measure production flowrates for a wellbore. Further, limitation of resources, cost, logistics, and even restrictions in production lines (e.g., co-mingled flowlines) can be prohibitive to taking constant flowrate measurements from a practical standpoint. By utilizing real-time pressure data from an ESP implemented in a wellbore, an accurate measure of flowrate can be determined to facilitate characterizing and forecasting wellbore production.

SUMMARY

In some embodiments, a method of determining flowrate of a production fluid of a downhole system implementing an electrical submersible pump (ESP) includes receiving pressure data of the ESP including input pressure data and output pressure data, and detecting an event of the downhole system associated with a change to one or more downhole conditions based on identifying a change in a pressure differential between the input pressure data and the output pressure data. The method includes classifying the event based on a change in the input pressure data or a change in the output pressure data. The method further includes updating a hydraulic model of the downhole system based on the classification of the event and based on the pressure differential, and determining a flowrate of the production fluid downhole system with the updated hydraulic model. In some embodiments, the method is performed by a computer system. In some embodiments, the method is implemented as instructions stored on a computer-readable storage medium.

This summary is provided to introduce a selection of concepts that are further described in the detailed description. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter. Additional features and aspects of embodiments of the disclosure will be set forth herein, and in part will be obvious from the description, or may be learned by the practice of such embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and other features of the disclosure can be obtained, a more particular description will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. For better understanding, the like elements have been designated by like reference numbers throughout the various accompanying figures. While some of the drawings may be schematic or exaggerated representations of concepts, at least some of the drawings may be drawn to scale. Understanding that the drawings depict some example embodiments, the embodiments will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:

FIG. 1-1 is an example of a downhole system, according to at least one embodiment of the present disclosure;

FIG. 1-2 is an example of a production system for producing a downhole fluid, according to at least one embodiment of the present disclosure;

FIG. 2 illustrates an example of a hydraulic model 200 for determining flowrate, according to at least one embodiment of the present disclosure;

FIG. 3-1 illustrates an example environment in which a flowrate system is implemented, according to at least one embodiment of the present disclosure;

FIG. 3-2 illustrates an example implementation of a flowrate system as described herein, according to at least one embodiment of the present disclosure;

FIGS. 4-1 and 4-2 illustrate pressure data measurements with respect to a hydraulic model, according to at least one embodiment of the present disclosure;

FIG. 4-3 illustrates pressure data measurements with respect to a hydraulic model, according to at least one embodiment of the present disclosure;

FIG. 4-4 shows an IPR model and a reservoir pressure model, according to at least one embodiment of the present disclosure;

FIG. 4-5 illustrates pressure data measurements with respect to a hydraulic model 400, according to at least one embodiment of the present disclosure;

FIG. 4-6 shows an IPR model and a reservoir pressure model, according to at least one embodiment of the present disclosure;

FIGS. 4-7 and 4-8 illustrate pressure data measurements with respect to a hydraulic model, according to at least one embodiment of the present disclosure;

FIG. 5 illustrates a flow diagram or decision tree for a method for identifying events and performing simulated calibrations of a hydraulic model, according to at least one embodiment of the present disclosure;

FIG. 6 illustrates a flow diagram for a method or a series of acts for determining flowrate for a production fluid of a downhole system, according to at least one embodiment of the present disclosure; and

FIG. 7 illustrates certain components that may be included within a computing system.

DETAILED DESCRIPTION

This disclosure generally relates to systems and methods for determining flowrate for a production fluid. In oilfield operations, having an understanding of production fluid flowrates of a wellbore may be valuable for increasing and/or optimizing wells and field production. Commonly, flowrates from ESP wells are measured with multiphase flowmeters or using tank volume measurements taken over a measurement period. It is generally difficult to take such measurements often and/or continually for various reasons such as limitation of resources, cost, logistics, among other reasons.

The computer-implemented flowrate system described herein uses the operational parameters of a well, such as real-time input and output pressures for the ESP to provide an accurate estimate of the production fluid flowrate. The flowrate system maintains and updates a hydraulic model for determining the production fluid, and performs simulated calibrations of the hydraulic model by considering the interaction between the behavior of the ESP, represented by an ESP curve, and the net lifting needs of the wellbore as a function of the production rate, represented by a system curve. The flowrate system identifies the flowing conditions of the well to appropriately determine how the hydraulic model should be updated or calibrated in order that the hydraulic model remains true to the actual, changing downhole conditions.

As will be discussed in further detail below, the present disclosure includes a number of practical applications having features described herein that provide benefits and/or solve problems associated with determining flowrates for a production fluid. Some example benefits are discussed herein in connection with various features and functionalities provided by a flowrate system implemented on one or more computing devices. It will be appreciated that benefits explicitly discussed in connection with one or more embodiments described herein are provided by way of example and are not intended to be an exhaustive list of all possible benefits of the flowrate system.

For example, flowrates are generally determined based on measuring the flow of a production fluid with a flowmeter. Flowmeters, such as multi-phase flowmeters which are conventionally utilized in order to measure the specific flows of constituent phases of a production fluid, are typically not implemented for providing flowrate measurements for extended and/or continual periods. For instance, flowmeters may typically include precise instrumentation that can be difficult to maintain and/or calibrate in a continual application. Additionally, flowmeters may not be able to withstand the harsh environment of a downhole system for extended periods. Thus, it can be difficult to obtain a measure of flowrate on a consistent and continual basis. The flowrate system described herein, however, may be implemented to provide real-time and continuous flowrate measurements. For example, because the flowrate system determines flowrate based on downhole parameters, such as pressure data, that are typically collected in a downhole operation, and which can be reliably and consistently collected for extended periods, the flowrate system can provide a measure of the flowrate in a manner which may not be possible with flowrate measuring devices such as flowmeters.

In some cases, hydraulic models are implemented to calculate or estimate flowrates based on simulating the flow dynamics of the production fluid. While these models can provide accurate results, changes to downhole conditions can affect the accuracy of these models to actually represent and simulate the downhole system. As such, hydraulic models typically are periodically calibrated to account for downhole condition changes. Model calibration is typically performed based on physical measurements taken for the downhole system, such as flowrate measurements with a flowmeter. As mentioned, these measurements may only be taken periodically and at delayed intervals. As such, hydraulic models may suffer accuracy limitations for significant periods between model calibrations. The flowrate system described herein utilizes the operational data for the downhole system such as pressure data, frequency data, temperature data, etc., in order to identify when downhole changes occur and simulate a model calibration based on adjusting curves of the hydraulic model in accordance with a type of identified downhole event. Thus, the flowrate system may implement and update hydraulic models to provide accurate estimates of flowrate despite changes to the downhole conditions. For example, the flowrate system updating the hydraulic model in this way may accurately determine flowrate with up to 95% or up to 99% accuracy to an actual flowrate measurement with a flowmeter. Thus, the flowrate system not only provides flexibility advantages for providing continual flowrate measurements, but may also do so with a high level of accuracy.

Additional details will now be provided regarding systems described herein in relation to illustrative figures portraying example implementations. For example, FIG. 1 shows one example of a downhole system 100 for drilling an earth formation 101 to form a wellbore 102. The downhole system 100 includes a drill rig 103 used to turn a drilling tool assembly 104 which extends downward into the wellbore 102. The drilling tool assembly 104 may include a drill string 105, a bottomhole assembly (“BHA”) 106, and a bit 110 attached to the downhole end of the drill string 105.

The drill string 105 may include several joints of drill pipe 108 connected end-to-end through tool joints 109. The drill string 105 transmits drilling fluid through a central bore and transmits rotational power from the drill rig 103 to the BHA 106. In some embodiments, the drill string 105 further includes additional downhole drilling tools and/or components such as subs, pup joints, etc. The drill pipe 108 provides a hydraulic passage through which drilling fluid is pumped from the surface. The drilling fluid discharges through selected-size nozzles, jets, or other orifices in the bit 110 for the purposes of cooling the bit 110 and cutting structures thereon, and for lifting cuttings out of the wellbore 102 as it is being drilled.

The BHA 106 may include the bit 110, other downhole drilling tools, or other components. An example BHA 106 may include additional or other downhole drilling tools or components (e.g., coupled between the drill string 105 and the bit 110). Examples of additional BHA components include drill collars, stabilizers, measurement-while-drilling (“MWD”) tools, logging-while-drilling (“LWD”) tools, downhole motors, underreamers, section mills, hydraulic disconnects, jars, vibration or dampening tools, other components, or combinations of the foregoing.

In general, the downhole system 100 may include other downhole drilling tools, components, and accessories such as special valves (e.g., kelly cocks, blowout preventers, and safety valves). Additional components included in the downhole system 100 may be considered a part of the drilling tool assembly 104, the drill string 105, or a part of the BHA 106, depending on their locations in the downhole system 100.

The bit 110 in the BHA 106 may be any type of bit suitable for degrading downhole materials. For instance, the bit 110 may be a drill bit suitable for drilling the earth formation 101. Example types of drill bits used for drilling earth formations are fixed-cutter or drag bits. In other embodiments, the bit 110 may be a mill used for removing metal, composite, elastomer, other materials downhole, or combinations thereof. For instance, the bit 110 may be used with a whipstock to mill into casing 107 lining the wellbore 102. The bit 110 may also be a junk mill used to mill away tools, plugs, cement, other materials within the wellbore 102, or combinations thereof. Swarf or other cuttings formed by use of a mill may be lifted to the surface or may be allowed to fall downhole. The bit 110 may include one or more cutting elements for degrading the earth formation 101.

The BHA 106 may further include a rotary steerable system (RSS). The RSS may include directional drilling tools that change a direction of the bit 110, and thereby the trajectory of the wellbore. At least a portion of the RSS may maintain a geostationary position relative to an absolute reference frame, such as one or more of gravity, magnetic north, or true north. Using measurements obtained with the geostationary position, the RSS may locate the bit 110, change the course of the bit 110, and direct the directional drilling tools on a projected trajectory. The RSS may steer the bit 110 in accordance with or based on a trajectory for the bit 110. For example, a trajectory may be determined for directing the bit 110 toward one or more subterranean targets such as an oil or gas reservoir.

The downhole system 100 may be implemented as shown and described as part of a drilling and/or wellbore forming configuration of the downhole system 100. In some cases, the downhole system 100 may be implemented as a completion and/or production configuration having a different configuration of downhole components. For instance, the production system 111 is representative of an alternate or later implementation of at least a portion of the downhole system 100 having a combination of downhole components for a production phase of the downhole system 100. In some cases, after the wellbore 102 has been formed, one or more production or completion components may be installed or implemented in the wellbore 102 for facilitating the production and removal of a production fluid 144 from a reservoir 142. For instance, in some cases an electrical submersible pump (ESP) 140 may be implemented in the wellbore 102 for providing supplemental pressure and/or flow to the production fluid 144, for example, above that which the reservoir 142 provides. In this way the ESP 140 may facilitate the production fluid 144 flowing to the surface.

FIG. 1-2 is an example of the production system 111 for producing the production fluid 144, according to at least one embodiment of the present disclosure. For example, one or more of the components of the production system 111 shown in FIG. 1-2 may be implemented in conjunction with, or in place of, one or more of the components of the downhole system 100 as shown in FIG. 1-1 after some or all of the wellbore 102 has been formed.

The production system 111 may include a collection of components for flowing and/or lifting the production fluid 144 from the reservoir 142, into the wellbore 102, and to the surface. For example, the production system 111 may include various surface equipment, such as wellhead equipment 160 for controlling and directing the flow of the production fluid 144 at the surface. The surface equipment may include electrical components such as a variable speed drive 161, set up transformer 162, etc. for providing electrical energy to one or more downhole components. The production system 111 may include various components implemented within the wellbore, such as a motor 163, protector 164, the ESP 140 having an intake, bolt on head 165, various sections of tubing 166. The production system 111 may include s sliding sleeve 167, a landing nipple 168, a packer 169, a vent valve 170, a tubing retrievable safety valve 171, and one or more transmission and/or communication cables 172. The production system 111 may be implemented with fewer and/or additional components to those shown and described here in order to facilitate the production of the production fluid 144.

In some embodiments, the ESP 140 may be instrumented and/or may be associated with one or more downhole sensors for providing measurements of one or more downhole parameters. For instance, one or more pressure sensors may indicate an input pressure to the ESP 140 associated with a flow of the production fluid 144 to the ESP (e.g., downhole of the ESP 140). The input pressure may often be associated with and/or provided via the subsurface reservoir 142, such as an inflow performance relationship (IPR). For example, a reservoir pressure may cause the production fluid 144 to flow from the reservoir 142 to the wellbore bottom hole at an input pressure. In some cases, one or more pressure sensors may indicate an output pressure from the ESP 140 associated with a flow of the production fluid 144 from the ESP 140, for example, uphole and to the surface. The output pressure may often be associated with a vertical lifting performance (VLP), or a pressure required to lift the production fluid 144 at a given flowrate to the surface. For instance, the ESP 140 may provide a pump effect, boost effect, or otherwise may make up a pressure differential between the input pressure (IPR) and the output pressure (VLP).

As shown in FIG. 1-1, the downhole system 100 may include or may be associated with a client device 112 with a flowrate system 120 implemented thereon (e.g., or with a client application implemented thereon for accessing the flowrate system 120 as described herein). The flowrate system 120 may facilitate determining a flowrate of the production fluid upward through the wellbore 102. For instance, the downhole system 100 may be in data communication with the ESP 140 and may receive sensor data for downhole pressures associated with the ESP. The flowrate system 120 may determine, estimate, or infer a flowrate of the downhole system based on the sensor data received from the ESP 140, as described herein.

In many cases, it may be important to determine an accurate measure of the flowrate of the production fluid 144 from the wellbore 102. For example, knowing the flowrate may facilitate determining a production rate of the various phases (e.g., oil, gas, water) of the production fluid 144 in order to determine an accurate forecast of hydrocarbon production from the wellbore 102. For instance, this may help to increase or optimize production from the downhole system 100. In other instances, accurately determining the flowrate may be valuable for reservoir management, well performance monitoring, safety and environmental protections, equipment and process design, and financial accounting associated with the downhole system 100.

Generally, production fluid flowrates are measured using a flowmeter, such as a multiphase flowmeter, for directly interacting with the production fluid to measure the flowrate. For example, multiphase flowmeters may be implemented at various locations in the downhole system and may provide an accurate measure of the flowrates of the production fluid, including the flowrates of the various constituent phases within the production fluid, such as oil, water, and gas phases. These flowmeters, while highly accurate, can be fairly complex, expensive, and disruptive to implement. As such, flowmeters may typically not be implemented permanently and/or constantly for providing continual and/or real-time flowrate measurements. For instance, multiphase flowmeters may not be suited to withstand the downhole environment for extended periods of time. In other examples, flowmeters may include precise instrumentation that may need periodic maintenance or calibration to maintain accuracy, which can be challenging in continuous operations.

Thus, implementing and maintaining flowmeters for continually measuring flowrate can be disruptive to wellbore production and present significant challenges. As such, flowrate measurements using flowmeters in this way may typically only be taken periodically and at delayed intervals, such as at intervals of weeks or months at a time.

In some cases, hydraulic models or fluid flow models are developed and implemented for modelling or simulating the fluid flow of the production fluid in order to calculate or infer flowrates, for example, indirectly, and in this way determine a continual and/or real time indication of flowrate. For example, FIG. 2 illustrates an example of a hydraulic model 200 for determining flowrate, according to at least one embodiment of the present disclosure. The hydraulic model 200 represents various properties and dynamics for the wellbore and/or downhole environment that are relevant to determining flowrate. For example, the hydraulic model 200 includes an IPR curve 202. The IPR curve 202 represents the relationship between a bottom-hole flowing pressure of the production fluid 144 and flowrate of the production fluid 144. For instance, the production fluid 144 may flow from the reservoir 142 to the wellbore 102 based on a reservoir pressure of the reservoir 142. At lower flowrates, the bottom-hole flowing pressure may be higher, and the bottom hole-flowing pressure may decrease as flowrate increases, reaching a maximum flowrate when the bottom-hole flowing pressure is zero.

The hydraulic model 200 includes a VLP curve 204. The VLP curve 204 represents the relationship between a pressure or head required to lift the production fluid 144 upward through the wellbore 102 to the surface, and the flowrate of the production fluid 144. For example, a lower pressure is needed to bring the production fluid 144 to the surface for lower flowrates, and the required pressure increases as flowrate increases. In many cases, the VLP curve 204 and IPR curve 202 may be separated and/or may not intersect (e.g. at some or all flowrates). This may represent the fact that, in many cases, the bottom-hole flowing pressure of the production fluid 144 as provided by the reservoir 142 may not be sufficient to lift the production fluid 144 entirely to the surface of the wellbore 102. Thus, in many instances, downhole pumps such the ESP 140 may be implemented in the wellbore to facilitate lifting or pumping the production fluid 144 to the surface. For instance, the ESP 140 may provide a pump effect or boost effect 206 to pressurize the production fluid 144 sufficient to flow the production fluid 144 to the surface. In other words, the ESP 140 may make up the pressure difference between the bottom-hole flowing pressure as indicated by the IPR curve 202, and the pressure needed to produce the production fluid 144 at the surface as indicated by the VLP curve 204. Accordingly, the IPR curve 202 may represent a pressure (for a given flowrate) of the production fluid 144 as observed downhole of the ESP 140, or an input pressure of the production fluid to the ESP 140. Similarly, the VLP curve 204 may represent a pressure (for a given flowrate) of the production fluid 144 as observed uphole of the ESP 140, or an output pressure of the production fluid 144 from the ESP 140.

The hydraulic model 200 may represent the relationship between the IPR curve 202 and VLP curve 204 as a system curve 208. For example, the system curve 208 may be defined by the difference between the VLP curve 204 and the IPR curve 202. In other words, the system curve 208 may represent the amount of additional pressure needed (e.g., to be provided by the ESP 140) to flow a given flowrate of the production fluid 144 to the surface of the wellbore 102.

In some cases, the hydraulic model 200 may include an ESP curve 210. The ESP curve 210 may be representative of the performance characteristics of the ESP 140. For example, the ESP curve 210 may represent a head of the ESP 140 with respect to the flowrate of the production fluid 144. For instance, the ESP curve 210 may represent an amount of pressure that the ESP 140 can provide to the production fluid 144, or a pressure differential that the ESP 140 may exhibit, for a given flowrate of the production fluid 144. The ESP curve 210 may be based on many different factors such as efficiency, power consumption, RPM, pump stages, etc., of the ESP 140. The ESP curve 210 and the system curve 208 may intersect (e.g., during normal and/or expected operating conditions of the downhole system) at the pressure and flowrate of the production fluid 144 flowing up the wellbore 102. For example, this intersection may represent the condition of the ESP 140 providing the required pressure, given the IPR and VLP pressures, to lift a given flowrate of the production fluid 144 to the surface.

In this way, the hydraulic model 200 may facilitate determining the flowrate of the production fluid 144, for example, based on the various curves of the hydraulic model 200. For example, given (e.g., measurable) input and output pressures of the ESP 140, the flowrate may be determined based on a location of the input and output pressures on the VLP curve 204 and IPR curve 202. In another example, the flowrate may be determined based on the difference between the input and output pressures as defined on the system curve 208. In another example, the flowrate may be determined based on the difference between the input and output pressures as indicated on the ESP curve 210. In another example, the flowrate may be determined based on identifying an intersection point between the ESP curve 210 and the system curve 208.

The hydraulic model 200 (e.g., specifically the various curves) may be generated based on various characteristics of the wellbore 102, downhole system 100, reservoir 142, etc. For instance, the hydraulic model 200 may be generated based on wellbore geometry, fluid properties, operational conditions, pressure losses and/or friction losses from the wellbore, reservoir location and/or geometry, reservoir properties, subsurface lithology, etc. The hydraulic model 200 may be a robust model that may account for many different properties, conditions, and/or characteristics of the downhole system 100. Additionally, the hydraulic model 200 may be generated based on measurements taken for the downhole system 100. For example, one or more sensor measurements for flowrate, pressure, ESP speed (RPM), or any other relevant measure may be taken in order to determine the curves and/or calibrate the hydraulic model 200.

In some cases, downhole conditions may change. For example, reservoir characteristics may change such that a bottom-hole flowing pressure no longer substantially fits to the IPR curve 202. In another example, wellbore characteristic may change such that an ESP output pressure no longer substantially lies on the VLP curve 204. Accordingly, in such situations, the hydraulic model 200 may no longer accurately reflect the actual flow dynamics of the production fluid 144. Any number of different events, circumstances, or behaviors may cause changes to the downhole conditions that may affect the accuracy of the hydraulic model 200 for determining flowrate. For example, described herein are several examples of situations in which conditions of the wellbore, reservoir, or other part of the downhole system may change.

Accordingly, in some cases, the hydraulic model 200 may typically be updated and/or calibrated, for example, by updating or calibrating one or more of the curves of the hydraulic model 200. For instance, as mentioned above, periodically one or more measurements, such as flow measurements, pressure measurements, etc. may be taken using instrumentation that can accurately measure these parameters. Based on these measurements, the hydraulic model 200 may be calibrated and/or one or more curves may be calibrated in order that the hydraulic model 200 is accurately updated to reflect the (e.g., changed) downhole conditions.

Such calibrations of the hydraulic model 200, however, may typically be sparce, and may only be performed periodically and/or at delayed intervals. For example, calibration measurements with flowmeters may only be performed at intervals of several weeks or several months. Accordingly, based on the delay in calibration of the hydraulic model 200, changes in downhole conditions may cause the hydraulic model 200 to inaccurately represent production fluid flow dynamics for extended periods. In this way, it may be difficult to accurately determine flowrates with hydraulic models after downhole conditions have changed and before the hydraulic models can next be updated or calibrated based on calibration measurements (e.g., flowrate measurements). Thus, the experience and intuition of drilling personnel and/or petroleum engineers may be relied on to estimate what the flowrate of the production fluid is, and what hydrocarbon production will be, in the presence of changing downhole conditions, which may be inconsistent and inaccurate.

One technique to handle changing downhole conditions is to rely more heavily on the ESP curve 210. For example, once identifying that the system curve 208 is no longer accurate to the input and/or output pressures, flowrates may be determined based on the ESP curve 210. However, as described herein, in some situations motor characteristics may change such that the ESP curve 210 does not give a reliable representation of the production fluid flow dynamics. Accordingly, flowrates determined in this way may not be accurate.

Another conventional technique involves monitoring the motor dynamics of the ESP 140, and inferring information about the flowrate from these dynamics. For example, if it is determined that the system curve 208 no longer accurately reflects the (e.g., changing) downhole dynamics, flowrates may be inferred based on observing the RPM and/or power consumption of the ESP 140. For instance, if the RPM and/or power consumption increases, it may be inferred that the result is an increase in flowrate (i.e., the ESP 140 is operating faster and/or at higher loads), and vice versa for RPM and/or power consumption decreases. Utilizing motor dynamics for inferring flowrates in this way, however, may be problematic. Namely, motor dynamics may not necessarily be an accurate proxy for flow dynamics. For instance, many factors may affect the motor RPM and/or power consumption of the ESP 140 that may not be directly related to the flow properties of the production fluid 144. As an illustrative example, an increase in electrical load drawn by the ESP 140 may not necessarily reflect a corresponding, or proportional, increase to the output pressure, flowrate, etc. To elaborate, a change in the composition (e.g., weight) of the production fluid 144 may cause the ESP 140 to operate faster and/or draw more current to maintain a given output pressure. The flowrate, however, may not necessarily increase, but may remain the same or even decrease. Thus, relying on changes in motor dynamics as indicating corresponding changes in flowrate may lead to inaccuracies. Accordingly, because ESP motor dynamics are somewhat removed from directly representing fluid flow dynamics of the production fluid 144, relying on motor dynamics to infer flowrate may not be an adequate approach to handling changes to downhole conditions causing a hydraulic model to be inaccurate before the model can be appropriately calibrated.

The flowrate system 120 described herein may overcome the limitations of these and other conventional techniques of determining production fluid flowrates. For example, the flowrate system 120 may identify changes to the downhole conditions, and may simulate one or more calibrations to a hydraulic model such that flowrates may be accurately determined from the hydraulic model. In this way, the hydraulic model may be relied on to provide an accurate measure of production fluid flowrate notwithstanding changes to the downhole environment. Additionally, the flowrate system 120 may update the model and may accurately determine flowrate independent of, or without relying on electrical data such as current draw of the ESP. In this way, the hydraulic model may be utilized to provide a continual and/or real-time indication of flowrate, including between extended periods of model calibration with direct flowrate measurements, for example, from a flowmeter.

FIG. 3-1 illustrates an example environment 300 in which a flowrate system 120 is implemented in accordance with one or more embodiments described herein. As shown in FIG. 3-1, the environment 300 includes a server device 114. The server device 114 may include one or more computing devices (e.g., including processing units, data storage, etc.) organized in an architecture with various network interfaces for connecting to and providing data management and distribution across one or more client systems. As shown in FIG. 3-1, the server device 114 may be connected to and may communicate with (either directly or indirectly) a client device 112 through a network 116. The network 116 may include one or multiple networks and may use one or more communication platforms and/or technologies suitable for transmitting data. The network 116 may refer to any data link that enables transport of electronic data between devices of the environment 300. The network 116 may refer to a hardwired network, a wireless network, or a combination of a hardwired network and a wireless network. In one or more embodiments, the network 116 includes the internet. The network 116 may be configured to facilitate communication between the various computing devices via well-site information transfer standard markup language (WITSML) or similar protocol, or any other protocol or form of communication.

The client device 112 may be representative of one or multiple client devices, and may refer to various types of computing devices. For example, the client device 112 may include a mobile device such as a mobile telephone, a smartphone, a personal digital assistant (PDA), a tablet, a laptop, or any other portable device. Additionally, or alternatively, the client device 112 may include one or more non-mobile devices such as a desktop computer, server device, surface or downhole processor or computer (e.g., associated with a sensor, system, or function of the downhole system), or other non-portable device. In one or more implementations, the client device 112 includes graphical user interfaces (GUI) thereon (e.g., a screen of a mobile device). In addition, or as an alternative, one or more of the client devices 112 may be communicatively coupled (e.g., wired or wirelessly) to a display device having a graphical user interface thereon for providing a display of system content. The server device 114 may similarly refer to various types of computing devices. Each of the devices of the environment 300 may include features and/or functionalities described below in connection with FIG. 7.

As shown in FIG. 3-1, the environment 300 may include a flowrate system 120 implemented on the server device 114. While shown on the server device 114, the flowrate system 120 may be implemented wholly or in part on the client device 112, across the server device 114 and the client device 112, or on or across one or more additional devices, such that different portions or components of the flowrate system 120 are implemented on different computing devices in the environment 300. The client device 112 may include a client application 118. The client application 118 may include an application or interface for interacting with and/or receiving the features of the flowrate system 120 as described herein. In some embodiments, one or more of the functionalities or features of the flowrate system 120 may be carried out or performed on or by the client application 118. In this way, the environment 300 may be a cloud computing environment, and the flowrate system 120 may be implemented across one or more devices of the cloud computing environment in order to leverage the processing capabilities, memory capabilities, connectivity, speed, etc., that such cloud computing environments offer in order to facilitate the features and functionalities described herein.

FIG. 3-2 illustrates an example implementation of the flowrate system 120 as described herein, according to at least one embodiment of the present disclosure. The flowrate system 120 may include a data manager 122, an event manager 124, and a flowrate manager 126 implementing a hydraulic model 128. The flowrate system 120 may also include a data storage 130 having pressure data 132 and flowrate data 134 stored thereon. While one or more embodiments described herein describe features and functionalities performed by specific components 122-128 of the flowrate system 120, it will be appreciated that specific features described in connection with one component of the flowrate system 120 may, in some examples, be performed by one or more of the other components of the flowrate system 120.

By way of example, one or more of the data receiving, gathering, or storing features of the data manager 122 may be delegated to other components of the flowrate system 120. As another example, while events may be identified and classified by the event manager 124, in some instances, some or all of these features may be performed by the flowrate manager 126 (or other component of the flowrate system 120). Indeed, it will be appreciated that some or all of the specific components may be combined into other components and specific functions may be performed by one or across multiple components 122-128 of the flowrate system 120.

Additionally, while FIG. 1, for example, depicts the flowrate system 120 implemented on a client device 112 of the downhole system, it should be understood that some or all of the features and functionalities of the flowrate system 120 may be implemented on or across multiple client devices 112 and/or server devices 114. For example, data may be input and/or received by the data manager 122 on a (e.g., local) client device, and the hydraulic model 128 may be updated and/or implemented (e.g., by the flowrate manager 126) on one or more of a remote, server, or cloud device. Indeed, it will be appreciated that some or all of the specific components 122-128 may be implemented on or across multiple client devices 112 and/or server devices 114, including individual functions of a specific component being performed across multiple devices.

As mentioned above, the flowrate system 120 includes a data manager 122. The data manager 122 may receive a variety of types of data associated with the downhole system and may store the data to the data storage 130. The data manager 122 may receive the data from a variety of sources, such as from sensors, surveying tools, downhole tools, other (e.g., client) devices, libraries, databases, user input, etc.

In some embodiments, the data manager 122 receives pressure data 132. For instance, the data manager 122 may receive the pressure data 132 from one or more pressure sensors included or otherwise associated with the ESP. The pressure data 132 may include input pressure data and output pressure data. The input pressure data may indicate a pressure of the production fluid flowing into the ESP. For instance, the input pressure of the input pressure data may be associated with an IPR of the downhole system. The output pressure data 132 may indicate a pressure of the production fluid flowing out of the ESP. For example, the output pressure of the output pressure data may be associated with a VLP of the downhole system. The pressure data 132 may include any information associated with the pressure of the production fluid, for example, in addition to the pressure measurements.

In some embodiments, the data manager 122 receives temperature data. For instance, the data manager 122 may receive the pressure data 132 for one or more temperature sensors positioned at one or more locations of the downhole system. in some cases, the temperature data indicates a temperature of the production fluid at one or more locations. In some embodiments, the temperature data indicates a temperature of one or more surface components of the downhole system, such as a wellhead temperature. The temperature data may include any other temperature measurements for any other component or location of the downhole system.

In some embodiments, the data manager 122 receives fluid composition data. The fluid composition data may indicate a composition of a production fluid flowing within or from the wellbore. For example, the fluid composition data may indicate a makeup of two or more constituent phases of the production fluid. For instance, the fluid composition data may indicate a percentage or ratio of gas and oil in the production fluid, such as by indicating a gas-oil-ratio (GOR) of the production fluid. In some embodiments, the fluid composition data may indicate a percentage or ratio of water in the production fluid, such as by a water cut of the production fluid. The fluid composition data may be determined, for example, by sampling or testing the production fluid. For instance, a sample of the production fluid may be tested on-or off-site (e.g., in a lab) in order to determine a fluid compensation of the production fluid, and may be transmitted to the flowrate system 120 via the data manager 122.

In some embodiments, the data manager 122 receives user input. The data manager 122 may receive the user input, for example, via any of the client devices 112 and/or server devices 114. Any of the data described herein may be input or augmented via the user input. For example, in some instances, some or all of the fluid composition data is received by the data manager 122 as user input. The user input may be received in association with one or more functions or features of the flowrate system 120, such as part of detecting or classifying events, or any other feature described herein.

As mentioned above, the flowrate system 120 includes an event manager 124. The event manager 124 may facilitate identifying events corresponding to changes in the downhole conditions of the reservoir, wellbore, ESP, etc. For example, the event manager may monitor the pressure data and may identify events based on identifying changes in a pressure differential between the input pressure and the output pressure of the pressure data. For example, a change in the pressure differential may indicate that some corresponding change in the downhole system has taken place. For instance, a change in the pressure differential may indicate that the pump is providing more or less boost effect or lifting pressure to the production fluid, which may be caused by any of a number of changes in downhole conditions. Accordingly, the event manager may identify the event in order to signify changes in the downhole conditions and in order to facilitate appropriately simulating a calibration of a hydraulic model.

In some embodiments, the event manager 124 classifies the identified events. The event manager 124 may classify the events based on observed changes to the input and/or output pressures, and with respect to a (e.g., current or last simulated calibration of a) hydraulic model. For instance, the event manager 124 may determine whether or not the changes in the pressure data align, fit, or are otherwise accurately represented by the hydraulic model. For example, the event manager may identify that for a given input and output pressure, the input pressure is not accurately represented by the VLP curve. In another example, the event manager may identify that for a given input and output pressure, the output pressure is not accurately represented by the IPR curve. In another example, the event manager 124 may identify that for a given input and output pressure, a pressure differential is not accurately represented by the ESP curve. In this way, the event manager 124 may identify events based on observable changes to the pressure differential, and may classify the events based on the changes to the input and/or output pressures that resulted in that change in pressure differential. Based on this event type, the flowrate manager 126 may simulating a calibration of the hydraulic model as described herein.

FIGS. 4-1 and 4-2 illustrate pressure data measurements with respect to a hydraulic model 400, according to at least one embodiment of the present disclosure.

In some embodiments, the event manager 124 identifies an event of a normal event type (or first event type). The normal event type may correspond with a normal operation of the downhole system. For example, the normal event type may correspond to an event that may not indicate changes to downhole conditions associated with the reservoir, wellbore, etc. but may indicate a change to the functioning and/or operation of the ESP.

The event manager 124 may identify an event of the normal event type based on identifying a change in the pressure differential 406 between an input pressure 412 and an output pressure 414. For example, at a first time t₁, the event manager 124 may observe the input pressure 412 and output pressure 414. The event manager 124 may identify that the input pressure 412 and output pressure 414 align with, or are represented by, the hydraulic model 400 based on the input pressure 412 falling on an IPR curve 402 and based on the output pressure 414 falling on a VLP curve 404. At a time t₂, the event manager 124 may identify that the pressure differential 406 has changed, and may identify the change in pressure differential as an event. For example, the event manager 124 may identify that the pressure differential increased at time t₂ (FIG. 4-1). Similarly, the event manager 124 may observe a change in an opposite direction, such as a decrease in the pressure differential at time t₂ (FIG. 4-2).

The event manager 124 may classify the identified event as the normal event type based on the individual measures of the input pressure 412 and the output pressure 414. For example, the event manager 124 may identify that both the input pressure 412 and the output pressure 414 have changed. In particular, the event manager may identify that the input pressure 412 and the output pressure 414 changed inversely. For instance, the event manager 124 may identify that the input pressure 412 decreased from time t₁ to time t₂, and that the output pressure 414 increased from time t₁ to time t₂ (FIG. 4-1). Similarly, the event manager 124 may identify that the input pressure 412 increased from time t₁ to time t₂, and that the output pressure 414 decreased from time t₁ to time t₂ (FIG. 4-2). Based on this observation, the event manager 124 may classify the event as the normal event type (e.g., first event type). For example, the input pressure 412 at time t₂ may align with the IPR curve 402 and the output pressure 414 at time t₂ may fall on the VLP curve 404 based on the inverse change in the input pressure 412 and the output pressure 414. Accordingly, the event manager 124 may classify the event as the normal event type based on the pressure data indicating that the system curve 408 is true or accurate to the reservoir, wellbore, etc. of the downhole system, or that the downhole system is behaving in a normal mode.

In some embodiments, the normal event type may be associated with a change in the operation and/or efficiency of the ESP (e.g., rather than a change in the behavior of the wellbore, reservoir, etc.). For instance, in some cases, gasses may flow into and/or may be released from the ESP which may cause changes to the ESP efficiency. In other cases, gas annulus venting may cause changes to the pump behavior. Any number of other factors or causes may affect the behavior of the ESP, such as opening or closing of casing valves, elevated and/or changes in temperature, scaling and corrosion, wear and tear, etc. In this way, the event manager 124 may determine that the downhole conditions affecting production fluid flow have changed and that the changes are specifically associated with changes to the ESP. For instance, an increase in the pressure differential 406 in connection with a normal event may indicate an increase in the efficiency of the ESP. A decrease in the pressure differential 406 in connection with a normal event may indicate a decrease in the efficiency of the ESP.

As mentioned, the flowrate system 120 includes a flowrate manager 126. The flowrate manager 126 may determine a flowrate of the production fluid based on implementing a hydraulic model, such as the hydraulic model 400. For instance, the flowrate manager 126 may simulate the downhole system, and more specifically the fluid and/or flow dynamics of the production fluid, based on the hydraulic model 400, and may accordingly determine a flowrate of the production fluid. For example, for a given input pressure 412 and output pressure 414, the flowrate manager 126 may determine a flowrate for the production fluid based on one or more of the curves of the hydraulic model 400.

In some embodiments, the flowrate manager 126 may implement the hydraulic model 400 and/or may simulate the flow dynamics according to an identified event and event type. For example, based on an identified event classification, the flowrate manager 126 may reference a specific curve of the hydraulic model 400 in order to accurately determine the flowrate. As an example, based on the event manager 124 detecting an event of the normal event type, the flowrate manager 126 may reference or implement the system curve 408 in order to determine the flowrate. For example, as described above, the event type being of the normal mode may correspond with any changes to the downhole conditions being associated with the ESP, rather than being associated with changes of the reservoir or the wellbore. Accordingly, the flowrate manager 126 may determine that the system curve 408 accurately reflects the flow dynamics and may reliably implement the system curve 408 in order to determine the flowrate. For instance, based on the pressure differential between the input pressure 412 and the output pressure 414, the system curve 408 may indicate a flowrate of the production fluid. The flowrate manager 126 may determine this flowrate to be the flowrate of the production fluid, and may store this flowrate to the data storage as the flowrate data 134. In this way the flowrate manager 126 may determine and implement a specific curve of the hydraulic model 400 based on an identified event and event type in order to determine an accurate flowrate for the production fluid.

In some embodiments, the flowrate manager 126 may update the hydraulic model 400 by simulating a calibration of the hydraulic model 400. For instance, the flowrate manager 126 may simulate a calibration of one or more of the curves of the model in order to ensure that the hydraulic model 400 may be implemented (e.g., at a later time interval) to accurately determine the flowrate of the production fluid. For example, as just mentioned, based on a normal event, the flowrate manager 126 may determine that the system curve 408 accurately reflects the downhole conditions for the wellbore and reservoir, but that one or more changes with respect to the operation of the ESP have occurred such that the ESP curve 410 may no longer be accurate. As described herein, in some cases (e.g., later) events of other types may correspond with implementing the ESP curve 410 (e.g., rather than the system curve 408) to determine flowrates and/or to simulate calibration of the hydraulic model 400. However, as just mentioned, the ESP curve 410 may be determined to be inaccurate (in this example). Accordingly, the flowrate manager 126 may simulate a calibration of the ESP curve 410 in order that the ESP curve accurately reflects the changes of the ESP and in order that the ESP curve 410 may be reliably and accurately implemented (e.g., at a future time interval).

In some embodiments, the flowrate manager 126 may calibrate the ESP curve 410 based on the system curve 408. For instance, as described in this example with respect to FIG. 4-1, the flowrate may accurately be determined based on the system curve 408. Additionally, as mentioned above, the ESP curve 410 and the system curve 408 may intersect at the indicated pressure and flowrate of the downhole system, reflecting the fact that the ESP operates to provide the boost effect (pressure differential) as needed to lift the given flowrate of the production fluid to the surface. Accordingly, the flowrate manager 126 may simulate a calibration of the ESP curve 410 based on adjusting the ESP curve 410 to intersect with the system curve 408 at the pressure and flowrate of the production fluid as determined by the flowrate manager 126. For example, the flowrate manager may determine an updated ESP curve 410-1 to reflect the changes to the ESP as identified at time t₂. Similarly, with respect to FIG. 4-2, the flowrate manager 126 may determine an updated ESP curve 410-2 to reflect the identified changes to the ESP. In this way, the flowrate manager 126 may update the hydraulic model 400 by simulating a calibration of the ESP curve 410 in order that the hydraulic model 400 may continue to accurately represent the production fluid flow dynamics despite changes to the downhole environment.

FIGS. 4-3 and 4-5 illustrate pressure data measurements with respect to the hydraulic model 400, according to at least one embodiment of the present disclosure.

In some embodiments, the event manager 124 may identify an event of an abnormal IPR type. For example, the event manager 124 may identify the event based on identifying a change in the pressure differential 406 (e.g., an increase or decrease in the pump boost effect) and may classify the event as the abnormal IPR type based on identifying a change in only the input pressure 412. For example, between the time t₁ and t₂, the event manager 124 may observe the pressure differential 406 increasing, and may observe the increase to be based on the output pressure 414 remaining substantially constant and the input pressure 412 decreasing, as shown in FIG. 4-3. In a similar manner, the event manager 124 may observe the pressure differential 406 decreasing, and may observe the decrease to be based on the output pressure 414 remaining substantially constant and the input pressure 412 increasing, as shown in FIG. 4-5. Accordingly, the event manager 124 may identify and classify an abnormal IPR event, indicating one or more changes affecting the input pressure.

An abnormal IPR event may be associated with one or more changes to the reservoir. For example, in some cases the reservoir experiences sharp or quick increases or decreases in reservoir pressure. For example, such sharp changes in reservoir pressure may be exhibited over hours or days. The sharp changes may be due to a pressure transient response of the reservoir as the reservoir pressure equalizes. For example, the reservoir may lose pressure at or near the wellbore based on the wellbore drawing the production fluid from the wellbore, and this decrease in pressure may transmit through the reservoir as a pressure transient response of the reservoir as the reservoir equalizes to this loss of pressure. A similar effect may occur when the reservoir is stimulated, such as by injecting water into the reservoir to increase the reservoir pressure. Such a pressure increase at the stimulation sight may travel across the reservoir as pressure transients as the reservoir pressure equalizes, which may be experienced at the wellbore. Accordingly, the input pressure may exhibit sharp increases or decreases in pressure based on these or similar changes to the reservoir pressure.

In some cases, the reservoir experiences soft or slow increases or decreases in reservoir pressure. For example, over time, as the production fluid is extracted from the reservoir, the reservoir pressure naturally and slowly decreases. Accordingly, the bottom-hole flowing pressure with which the production fluid flows into the wellbore, as indicated by the input pressure, may gradually decline over time. Similarly, in cases where water in injected into the reservoir to stimulate the reservoir and increase the pressure, the input pressure may exhibit soft, slow increases in pressure over time as the reservoir pressure increases.

Based on the identified and classified abnormal IPR event, the flowrate manager 126 may implement the hydraulic model 400 and/or may simulate the flow dynamics according to the abnormal IPR event. For example, as just mentioned, an abnormal IPR event may indicate one or more downhole changes that are associated with the reservoir, rather than the wellbore or ESP. Accordingly, the flowrate manager 126 may determine that the ESP curve 410 (e.g., as most recently updated through simulated calibration) remains accurate to the downhole system, but that the system curve 408 may no longer be reliable for determining flowrate. For example, based on the change in the input pressure 412 resulting in the input pressure 412 no longer aligning with the IPR curve 402, as indicated by the abnormal IPR event, the flowrate manager 126 may determine that the IPR curve 402 is no longer accurate, which affects the accuracy of the system curve 408. The flowrate manager 126 may determine that the VLP curve 404 is still reliable based on the output pressure 414 remaining unchanged and aligning with the VLP curve 404.

Accordingly, the flowrate manager 126 may reference or implement the ESP curve 410 in order to determine flowrate. For example, based on the pressure differential 406, the ESP curve 410 may indicate a flowrate of the production fluid, which the flowrate manager 126 may determine is the flowrate for the production fluid and may store this flowrate to the data storage as the flowrate data 134. In this way, the flowrate manager 126 may determine and implement the ESP curve 410 of the hydraulic model 400 based on identifying an abnormal IPR event.

In some embodiments, the flowrate manager 126 may update the hydraulic model 400 by simulating a calibration of the system curve 408 based on the ESP curve 410. For instance, FIG. 4-4 shows an IPR model 450 and a reservoir pressure model 452 which may be utilized by the flowrate manager 126 in cases where the input pressure 412 is observed to decrease, in order to determine the updated IPR curve 402-3 and updated system curve 408-3. FIG. 4-5 shows an IPR model 454 and a reservoir pressure model 456 which may be utilized by the flowrate manager 126 in cases wherein the input pressure 412 is observed to increase, in order to determine the updated IPR curve 402-5 and the updated system curve 408-5. The IPR models 450, 454 and reservoir pressure models 452, 456 may be generated or received from a simulation of the reservoir, through survey data, log data, etc. The IPR models 450, 454 show, in log scale, how the IPR curve 402 may change over time and, at a distance r from the reservoir, under transient flow conditions as well as steady state (e.g., including pseudo-steady state) flow conditions. Similarly, the reservoir pressure models 452, 456 represents how the pressure of the reservoir is affected over time under both transient flow conditions and steady state flow conditions.

The flowrate manager 126 may accordingly determine an updated IPR curve 402-3 and an updated system curve 408-3 (in accordance with the example case of FIG. 4-3), or an updated IPR curve 402-5 and an updated system curve 408-3 (in accordance with the example case of FIG. 4-5) in order to simulate a calibration of these curves and/or of the hydraulic model 400. In updating the IPR curve 402 and system curve 408, the flowrate manager 126 may reference the ESP curve 410. For instance, the flowrate manager 126 may update the IPR curve 402 and system curve 408 such that the updated system curve 408-3 or 408-5 intersects the ESP curve 410 at the pressure and flowrate of the production fluid as determined by the flowrate manager 126 using the ESP curve 410. For instance, the IPR curve 402 and system curve 408 may be adjusted through a numerical convergence process. Accordingly, the hydraulic model 400 may be updated to reflect the fact that the ESP provides the boost effect (e.g., pressure differential) as needed by the system to lift the flowrate of the production fluid to the surface. In this way, the flowrate manager 126 may update the hydraulic model 400 by simulating a calibration of the IPR curve 402 and system curve 408 in order that the hydraulic model 400 may continue to accurately represent the production fluid flow dynamics despite changes to the downhole environment.

FIGS. 4-7 and 4-8 illustrate pressure data measurements with respect to the hydraulic model 400, according to at least one embodiment of the present disclosure.

In some embodiments, the event manager 124 may identify an event of an abnormal VLP type. For example, the event manager 124 may identify the event based on identifying a change in the pressure differential 406 (e.g., an increase or decrease in the pump boost effect) and may classify the event as the abnormal VLP type based on identifying a change in only the output pressure 414. For example, between the time t₁ and t₂, the event manager 124 may observe the pressure differential 406 increasing, and may observe the increase to be based on the input pressure 412 remaining substantially constant and the output pressure 414 increasing, as shown in FIG. 4-7. In a similar manner, the event manager 124 may observe the pressure differential 406 decreasing, and may observe the decrease to be based on the input pressure 412 remaining substantially constant and the output pressure 414 decreasing, as shown in FIG. 4-8. Accordingly, the event manager 124 may identify and classify an abnormal VLP event, indicating one or more changes affecting the output pressure.

An abnormal VLP event may be associated with one or more changes to a flow path of the production fluid uphole of the ESP. For example, changes in the wellbore, uphole components, surface equipment, etc., can affect the flow of the production fluid from the ESP upward through the wellbore. For instance, the wellbore, wellhead, or other component of the flow path may become restricted, such as from scaling, restricting or closing of a valve, etc., causing an increase in the output pressure required to lift the production fluid to the surface. Similarly, a restriction may become cleared causing the output pressure to decrease. In another example, a weight of the production fluid may change, such as a change in the water cut or other composition of the production fluid, which may cause an increase or decrease in output pressure.

Based on the identified and classified abnormal VLP event, the flowrate manager 126 may implement the hydraulic model 400 and/or may simulate the flow dynamics according to the abnormal VLP event. For example, as just mentioned, an abnormal VLP event may indicate one or more downhole changes that are associated with the wellbore, wellhead, etc., rather than the reservoir or ESP. Accordingly, the flowrate manager 126 may determine that the ESP curve 410 (e.g., as most recently updated through simulated calibration) remains accurate to the downhole system, but that the system curve 408 may no longer be reliable for determining flowrate. For example, based on the change in the output pressure 414 resulting in the output pressure 414 no longer aligning with the VLP curve 404, as indicated by the abnormal VLP event, the flowrate manager 126 may determine that the VLP curve 404 is no longer accurate, which affects the accuracy of the system curve 408. The flowrate manager 126 may determine that the IPR curve 402 is still reliable based on the input pressure 412 remaining unchanged and aligning with the IPR curve 402.

Accordingly, the flowrate manager 126 may reference or implement the ESP curve 410 in order to determine flowrate. For example, based on the pressure differential 406, the ESP curve 410 may indicate a flowrate of the production fluid, which the flowrate manager 126 may determine is the flowrate for the production fluid and may store this flowrate to the data storage as the flowrate data 134. In this way, the flowrate manager 126 may determine and implement the ESP curve 410 of the hydraulic model 400 based on identifying an abnormal VLP event.

In some embodiments, the flowrate manager 126 may update the hydraulic model 400 by simulating a calibration of the system curve 408 and by generating an updated system curve 408-7 (FIG. 4-7) or 408-8 (FIG. 4-8). For instance, the flowrate manager 126 may simulate a calibration of the VLP curve 404 and may generate an updated VLP curve 404-7 (FIG. 4-7) or 404-8 (FIG. 4-8). The flowrate manager 126 may update the VLP curve 404 based on adjusting the VLP curve 404 to alight or fit the (e.g., changed) output pressure 414 as observed at time t₂. In this way the VLP curve 404 may be updated such that it reflects the actual conditions affecting the flow of the production fluid as it flows upward through the wellbore and to the surface.

In some embodiments, the flowrate manager 126 may update the hydraulic model 400 based on the ESP curve 410. For instance, as mentioned, the flowrate may accurately be determined based on the ESP curve 410. Additionally, as mentioned above, the ESP curve 410 and the system curve 408 may intersect at the indicated pressure and flowrate of the downhole system, reflecting the fact that the ESP operates to provide the needed boost effect (pressure differential) needed to lift the given flowrate of the production fluid to the surface. Accordingly, the flowrate manager 126 may simulate a calibration of the system curve 408 based on adjusting the system curve 408 (e.g., and/or the VLP curve 404) to intersect with the ESP curve 410 at the pressure and flowrate of the production fluid as determined by the flowrate manager 126. In this way, the flowrate manager 126 may update the hydraulic model 400 by simulating a calibration of the VLP curve 404 and system curve 408 in order that the hydraulic model 400 may continue to accurately represent the production fluid flow dynamics despite changes to the downhole environment.

In this way, the flowrate manager 126 may make one or more updates to the hydraulic model 400 by simulating calibrations of the hydraulic model 400 in order to reflect identifiable and observable changes to the downhole conditions. The flowrate system 120 may accordingly implement the hydraulic model 400 to accurately determine flowrates of the production fluid notwithstanding changes to flow conditions, and despite long periods between model calibrations (e.g., with flowmeter and other measurements). Additionally, the flowrates determined by the flowrate system 120 may be determined continually and/or in real time or near real time. For example, the data manager 122 may receive the pressure data in real time or near real time, and the flowrate system 120 may identify and classify events, perform simulated calibrations to update the hydraulic model, and determine flowrates in a substantially real time manner. In this way, the flowrate system 120 may provide a continual indication of the flowrate of the production fluid in order to facilitate operating the wellbore in an efficient and effective manner.

In some embodiments, the flowrate manager 126 may validate or verify the simulated calibrations to ensure that the flowrates determined by the hydraulic model are accurate (e.g., after one or more updates). In some embodiments, the flowrate manager 126 may validate the current state of the hydraulic model based on the temperature data. For example, the temperature data may indicate a temperature of the wellhead equipment or other surface components. The flowrate manager 126 may confirm that an update to the hydraulic model is accurate based on correlating a determined flowrate to a change in the temperature data. For example, the flowrate manager 126 may simulate a calibration of the hydraulic model, which may result in the flowrate manager 126 determining that the flowrate of the production fluid has increased. The flowrate manager 126 may verify that this determined increase is in effect based on confirming that the temperature of one or more components has increased. For example, the production fluid may typically exhibit an elevated temperature. A higher flow of the production fluid may result in the surface and/or wellhead components increasing in temperature. Thus, the flowrate manager 126 may confirm that an update to the model resulting in an increase in the determined flowrate is observed in the real world. The flowrate manager may similarly validate a model update associated with a decrease in determined flowrate based on confirming a decrease in the temperature data.

In some embodiments, the flowrate manager 126 may identify flowrate(s) for one or more constituent phases of the production fluid. For example, the flowrate manager 126 may determine the flowrate of the production fluid as described herein, and additionally, based on the fluid composition data (e.g., GOR and/or water cut) for the production fluid, the flowrate manager 126 may determine an individual flowrate or production rate for one or more of an oil phase, a gas phase, or a water phase of the production fluid. For example, the flowrate manager 126 may apply the GOR and/or water cut to the determined flowrate of the production fluid to determine the individual production rates of the individual phases of the production fluid. In this way, the flowrate manager 126 may facilitate determining a hydrocarbon production rate, for example, for the oil phase and/or the gas phase in order to accurately forecast how much oil and/or gas the wellbore may produce.

FIG. 5 illustrates a flow diagram or decision tree for a method 500 for identifying events and performing simulated calibrations of a hydraulic model as described herein, according to at least one embodiment of the present disclosure.

The method 500 may begin with monitoring the pressure data at 502. At 504, the method 500 determines if the pressure differential of the pressure data has changed. If the pressure differential has not changed, one or more flowrates are determined for one or more time intervals with the hydraulic model at 503 until a change to the pressure differential is determined at 504.

Based on the pressure differential increasing, the method 500 proceeds to determine at 506 whether the output pressure changed. If the output pressure did not change, then the method 500 proceeds to 510, where an abnormal IPR event is determined and a simulated calibration of the IPR curve is performed. For instance, if the pressure differential increased and the output pressure did not change, then the input pressure decreased, indicating a change to the flow dynamics affecting the input pressure.

At 506, if the output pressure increased, the method 500 proceeds to determine if the input pressure changed at 512. If the input pressure decreased, then the method 500 proceeds to 516, wherein a normal event is determined, and a simulated calibration of the ESP curve is performed. For example, if the pressure differential increased based on the output pressure increasing and the input pressure decreasing, then pressure data is consistent with the system curve (e.g., IPR and VLP curves), indicating a change to the ESP performance.

At 512, if the input pressure did not change, the method 500 proceeds to 518, wherein an abnormal VLP event is determined, and a simulated calibration of the VLP curve is performed. For instance, the pressure differential increasing based on the output pressure increasing and the input pressure remaining constant indicates a change to the flow dynamics affecting the output pressure.

At 504, if the pressure differential decreases, the method 500 proceeds to determine at 508 whether the output pressure changed. If the output pressure did not change, then the method 500 proceeds to 510, where an abnormal IPR event is determined and a simulated calibration of the IPR curve is performed. For instance, if the pressure differential decreased and the output pressure did not change, then the input pressure increased, indicating a change to the flow dynamics affecting the input pressure.

At 508, if the output pressure decreased, the method 500 proceeds to determine if the input pressure changed at 514. If the input pressure increased, then the method 500 proceeds to 516, wherein a normal event is determined, and a simulated calibration of the ESP curve is performed. For example, if the pressure differential decreased based on the output pressure decreasing and the input pressure increasing, then pressure data is consistent with the system curve (e.g., IPR and VLP curves), indicating a change to the ESP performance.

At 514, if the input pressure did not change, the method 500 proceeds to 518, wherein an abnormal VLP event is determined, and a simulated calibration of the VLP curve is performed. For instance, the pressure differential decreasing based on the output pressure decreasing and the input pressure remaining constant indicates a change to the flow dynamics affecting the output pressure.

After determining an event and event type and accordingly simulating a calibration of a model curve at any of 510, 516, or 518, the method 500 proceeds to 520, wherein the hydraulic model is updated and a flowrate is determined based on the updated model. The method 500 then proceeds back to 502 to continue monitoring the pressure data. In this way, the hydraulic model may be implemented to determine accurate production fluid flowrates, and the hydraulic model may be updated as needed to reflect identified changes to the downhole system. The hydraulic model may be updated any number of times by performing any number of simulated calibrations of model curves and in any order based on any number of changes to the downhole system.

FIG. 6 illustrates a flow diagram for a method 600 or a series of acts for determining flowrate for a production fluid of a downhole system as described herein, according to at least one embodiment of the present disclosure. While FIG. 6 illustrates acts according to one embodiment, alternative embodiments may add to, omit, reorder, or modify any of the acts of FIG. 6. In some embodiments the acts of FIG. 6 are performed by a computer system. In some embodiments, the acts of FIG. 6 are implemented as instructions contained on a computer-readable storage medium.

In some embodiments, the method includes an act 610 of receiving pressure data of an ESP including input pressure data and output pressure data.

In some embodiments, the method includes an act 620 of detecting an event of the downhole system associated with a change to one or more downhole conditions based on identifying a change in a pressure differential between the input pressure data and the output pressure data.

In some embodiments, the method includes an act 630 of classifying the event based on a change in the input pressure data or a change in the output pressure data.

In some embodiments, the method includes an act 640 of updating a hydraulic model of the downhole system based on the classification of the event and based on the pressure differential.

In some embodiments, the method includes an act 650 of determining a flowrate of the production fluid downhole system with the updated hydraulic model.

In some embodiments, updating the hydraulic model includes simulating a calibration of a model curve of the hydraulic model based on the pressure data.

In some embodiments, updating the hydraulic model includes selecting a model curve of a set of model curves of the hydraulic model, and simulating a calibration of the selected model curve based on the classification of the event.

In some embodiments, the set of model curves includes an ESP curve of the ESP and a system curve of the downhole system.

In some embodiments, the system curve is defined by a vertical lifting pressure (VLP) curve and an inflow performance relationship (IPR) curve.

In some embodiments, the VLP curve is associated with the output pressure data and the IPR curve is associated with the input pressure data.

In some embodiments, updating the hydraulic model includes selecting a first model curve of the set of model curves to update, and simulating a calibration of the first model curve based on a second model curve of the set of model curves and based on the pressure data.

In some embodiments, the method 500 further includes measuring the input pressure data and the output pressure data with one or more downhole pressure sensors of the ESP.

In some embodiments, classifying the event includes classifying the event as a first event type based on determining changes to both the input pressure data and the output pressure data, and determining that the changes are inversely related.

In some embodiments, the first event type is associated with a change in efficiency of the ESP causing the change in the pressure differential.

In some embodiments, the hydraulic model includes simulating a calibration of an ESP curve of the hydraulic model based on a system curve of the hydraulic model and based on the pressure differential.

In some embodiments, classifying the event includes classifying the event as a second event type based on determining: a change in the input pressure and the output pressure remaining substantially constant, or a change in the output pressure and the input pressure remaining substantially constant.

In some embodiments, the second event type is associated with a steady-state inflow of the production fluid from a reservoir of the downhole system to a wellbore of the downhole system decreasing based on reservoir pressure depletion.

In some embodiments, the second event type is associated with an inflow of the production fluid from a reservoir of the downhole system to a wellbore of the downhole system changing based on a transient pressure response of a reservoir pressure of the reservoir.

In some embodiments, the second event type is associated with an outflow of the production fluid from the ESP upward through a wellbore of the downhole system changing.

In some embodiments, the outflow of the production fluid changes based on a change in one or more of a restriction within the wellbore, a restriction at a surface of the wellbore, a water cut of the production fluid, or a weight of a hydrostatic column of the production fluid in the wellbore.

In some embodiments, updating the hydraulic model includes simulating a calibration of a system curve of the hydraulic model based on an ESP curve of the hydraulic model and based on the pressure differential.

In some embodiments, the hydraulic model is updated, and the flowrate is determined, independent of electrical data associated with an electrical load of the ESP.

Turning now to FIG. 7, this figure illustrates certain components that may be included within a computer system 700. One or more computer systems 700 may be used to implement the various devices, components, and systems described herein.

The computer system 700 includes a processor 701. The processor 701 may be a general-purpose single-or multi-chip microprocessor (e.g., an Advanced RISC (Reduced Instruction Set Computer) Machine (ARM)), a special purpose microprocessor (e.g., a digital signal processor (DSP)), a microcontroller, a programmable gate array, etc. The processor 701 may be referred to as a central processing unit (CPU). Although just a single processor 701 is shown in the computer system 700 of FIG. 7, in an alternative configuration, a combination of processors (e.g., an ARM and DSP) could be used.

The computer system 700 also includes memory 703 in electronic communication with the processor 701. The memory 703 may include computer-readable storage media and can be any available media that can be accessed by a general purpose or special purpose computer system. Computer-readable media that store computer-executable instructions are non-transitory computer-readable media (device). Computer-readable media that carry computer-executable instructions are transmission media. Thus, by way of example and not limitations, embodiment of the present disclosure can comprise at least two distinctly different kinds of computer-readable media: non-transitory computer-readable media (devices) and transmission media.

Both non-transitory computer-readable media (devices) and transmission media may be used temporarily to store or carry software instructions in the form of computer readable program code that allows performance of embodiments of the present disclosure. Non-transitory computer-readable media may further be used to persistently or permanently store such software instructions. Examples of non-transitory computer-readable storage media include physical memory (e.g., RAM, ROM, EPROM, EEPROM, etc.), optical disk storage (e.g., CD, DVD, HDDVD, Blu-ray, etc.), storage devices (e.g., magnetic disk storage, tape storage, diskette, etc.), flash or other solid-state storage or memory, or any other non-transmission medium which can be used to store program code in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer, whether such program code is stored or in software, hardware, firmware, or combinations thereof.

Instructions 705 and data 707 may be stored in the memory 703. The instructions 705 may be executable by the processor 701 to implement some or all of the functionality disclosed herein. Executing the instructions 705 may involve the use of the data 707 that is stored in the memory 703. Any of the various examples of modules and components described herein may be implemented, partially or wholly, as instructions 705 stored in memory 703 and executed by the processor 701. Any of the various examples of data described herein may be among the data 707 that is stored in memory 703 and used during execution of the instructions 705 by the processor 701.

A computer system 700 may also include one or more communication interfaces 709 for communicating with other electronic devices. The communication interface(s) 709 may be based on wired communication technology, wireless communication technology, or both. Some examples of communication interfaces 709 include a Universal Serial Bus (USB), an Ethernet adapter, a wireless adapter that operates in accordance with an Institute of Electrical and Electronics Engineers (IEEE) 802.11 wireless communication protocol, a Bluetooth® wireless communication adapter, and an infrared (IR) communication port.

The communication interfaces 709 may connect the computer system 700 to a network. A “network” or “communications network” may generally be defined as one or more data links that enable the transport of electronic data between computer systems and/or modules, engines, or other electronic devices, or combinations thereof. When information is transferred or provided over a communication network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computing device, the computing device properly views the connection as a transmission medium. Transmission media can include a communication network and/or data links, carrier waves, wireless signals, and the like, which can be used to carry desired program or template code means or instructions in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer.

A computer system 700 may also include one or more input devices 711 and one or more output devices 713. Some examples of input devices 711 include a keyboard, mouse, microphone, remote control device, button, joystick, trackball, touchpad, and lightpen. Some examples of output devices 713 include a speaker and a printer. One specific type of output device that is typically included in a computer system 700 is a display device 715. Display devices 715 used with embodiments disclosed herein may utilize any suitable image projection technology, such as liquid crystal display (LCD), light-emitting diode (LED), gas plasma, electroluminescence, or the like. A display controller 717 may also be provided, for converting data 707 stored in the memory 703 into one or more of text, graphics, or moving images (as appropriate) shown on the display device 715.

The various components of the computer system 700 may be coupled together by one or more buses, which may include one or more of a power bus, a control signal bus, a status signal bus, a data bus, other similar components, or combinations thereof. For the sake of clarity, the various buses are illustrated in FIG. 7 as a bus system 719.

The techniques described herein may be implemented in hardware, software, firmware, or any combination thereof, unless specifically described as being implemented in a specific manner. Any features described as modules, components, or the like may also be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques may be realized at least in part by a non-transitory processor-readable storage medium comprising instructions that, when executed by at least one processor, perform one or more of the methods described herein. The instructions may be organized into routines, programs, objects, components, data structures, etc., which may perform particular tasks and/or implement particular data types, and which may be combined or distributed as desired in various embodiments.

Further, upon reaching various computer system components, program code in the form of computer-executable instructions or data structures can be transferred automatically or manually from transmission media to non-transitory computer-readable storage media (or vice versa). For example, computer executable instructions or data structures received over a network or data link can be buffered in memory (e.g., RAM) within a network interface module (NIC), and then eventually transferred to computer system RAM and/or to less volatile non-transitory computer-readable storage media at a computer system. Thus, it should be understood that non-transitory computer-readable storage media can be included in computer system components that also (or even primarily) utilize transmission media.

INDUSTRIAL APPLICABILITY

The following description from ¶¶ [0135]-[0154] includes various embodiments that, where feasible, may be combined in any permutation. For example, the embodiment of ¶ [0135] may be combined with any or all embodiments of the following paragraphs. Embodiments that describe acts of a method may be combined with embodiments that describe, for example, systems and/or devices. Any permutation of the following paragraphs is considered to be hereby disclosed for the purposes of providing “unambiguously derivable support” for any claim amendment based on the following paragraphs. Furthermore, the following paragraphs provide support such that any combination of the following paragraphs would not create an “intermediate generalization.”

In some embodiments, a method of determining flowrate of a production fluid of a downhole system implementing an electrical submersible pump (ESP) includes receiving pressure data of the ESP including input pressure data and output pressure data, detecting an event of the downhole system associated with a change to one or more downhole conditions based on identifying a change in a pressure differential between the input pressure data and the output pressure data, classifying the event based on a change in the input pressure data or a change in the output pressure data, updating a hydraulic model of the downhole system based on the classification of the event and based on the pressure differential, and determining a flowrate of the production fluid downhole system with the updated hydraulic model.

In some embodiments, updating the hydraulic model includes simulating a calibration of a model curve of the hydraulic model based on the pressure data.

In some embodiments, updating the hydraulic model includes selecting a model curve of a set of model curves of the hydraulic model, and simulating a calibration of the selected model curve based on the classification of the event.

In some embodiments, the set of model curves includes an ESP curve of the ESP and a system curve of the downhole system.

In some embodiments, the system curve is defined by a vertical lifting pressure (VLP) curve and an inflow performance relationship (IPR) curve.

In some embodiments, the VLP curve is associated with the output pressure data and the IPR curve is associated with the input pressure data.

In some embodiments, updating the hydraulic model includes selecting a first model curve of the set of model curves to update, and simulating a calibration of the first model curve based on a second model curve of the set of model curves and based on the pressure data.

In some embodiments, the method further includes measuring the input pressure data and the output pressure data with one or more downhole pressure sensors of the ESP.

In some embodiments, classifying the event includes classifying the event as a first event type based on determining changes to both the input pressure data and the output pressure data, and determining that the changes are inversely related.

In some embodiments, the first event type is associated with a change in efficiency of the ESP causing the change in the pressure differential.

In some embodiments, updating the hydraulic model includes simulating a calibration of an ESP curve of the hydraulic model based on a system curve of the hydraulic model and based on the pressure differential.

In some embodiments, classifying the event includes classifying the event as a second event type based on determining a change in the input pressure and the output pressure remaining substantially constant, or a change in the output pressure and the input pressure remaining substantially constant.

In some embodiments, the second event type is associated with a steady-state inflow of the production fluid from a reservoir of the downhole system to a wellbore of the downhole system decreasing based on reservoir pressure depletion.

In some embodiments, the second event type is associated with an inflow of the production fluid from a reservoir of the downhole system to a wellbore of the downhole system changing based on a transient pressure response of a reservoir pressure of the reservoir.

In some embodiments, the second event type is associated with an outflow of the production fluid from the ESP upward through a wellbore of the downhole system changing.

In some embodiments, the outflow of the production fluid changes based on a change in one or more of a restriction within the wellbore, a restriction at a surface of the wellbore, a water cut of the production fluid, or a weight of a hydrostatic column of the production fluid in the wellbore.

In some embodiments, updating the hydraulic model includes simulating a calibration of a system curve of the hydraulic model based on an ESP curve of the hydraulic model and based on the pressure differential.

In some embodiments, the hydraulic model is updated, and the flowrate determined, independent of electrical data associated with an electrical load of the ESP.

In some embodiments, a system, includes at least one processor, memory in electronic communication with the at least one processor, and instructions stored in the memory, the instructions being executable by the at least one processor to receive pressure data of an electrical submersible pump (ESP) of a downhole system, including input pressure data and output pressure data, detect an event of the downhole system based on identifying a change in a pressure differential between an input pressure of the input pressure data and an output pressure of the output pressure data, classify the event based on a change in the input pressure of the input pressure data or a change in the output pressure of the output pressure data, update a hydraulic model of the downhole system based on the classification of the event and based on the pressure differential, and determine a flowrate of the downhole system with the updated hydraulic model.

In some embodiments, a computer-readable storage medium including instruction that, when executed by at least one processor, cause the processor to, receive pressure data of an electrical submersible pump (ESP) of a downhole system, including input pressure data and output pressure data, detect an event of the downhole system based on identifying a change in a pressure differential between an input pressure of the input pressure data and an output pressure of the output pressure data, classify the event based on a change in the input pressure of the input pressure data or a change in the output pressure of the output pressure data, update a hydraulic model of the downhole system based on the classification of the event and based on the pressure differential, and determine a flowrate of the downhole system with the updated hydraulic model.

The embodiments of the flowrate system have been primarily described with reference to wellbore drilling operations; the flowrate system described herein may be used in applications other than the drilling of a wellbore. In other embodiments, the flowrate system according to the present disclosure may be used outside a wellbore or other downhole environment used for the exploration or production of natural resources. For instance, the flowrate system of the present disclosure may be used in a borehole used for placement of utility lines. Accordingly, the terms “wellbore,” “borehole” and the like should not be interpreted to limit tools, systems, assemblies, or methods of the present disclosure to any particular industry, field, or environment.

One or more specific embodiments of the present disclosure are described herein. These described embodiments are examples of the presently disclosed techniques. Additionally, in an effort to provide a concise description of these embodiments, not all features of an actual embodiment may be described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous embodiment-specific decisions will be made to achieve the developers'specific goals, such as compliance with system-related and business-related constraints, which may vary from one embodiment to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.

Additionally, it should be understood that references to “one embodiment” or “an embodiment” of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. For example, any element described in relation to an embodiment herein may be combinable with any element of any other embodiment described herein. Numbers, percentages, ratios, or other values stated herein are intended to include that value, and also other values that are “about” or “approximately” the stated value, as would be appreciated by one of ordinary skill in the art encompassed by embodiments of the present disclosure. A stated value should therefore be interpreted broadly enough to encompass values that are at least close enough to the stated value to perform a desired function or achieve a desired result. The stated values include at least the variation to be expected in a suitable manufacturing or production process, and may include values that are within 5%, within 1%, within 0.1%, or within 0.01% of a stated value.

A person having ordinary skill in the art should realize in view of the present disclosure that equivalent constructions do not depart from the spirit and scope of the present disclosure, and that various changes, substitutions, and alterations may be made to embodiments disclosed herein without departing from the spirit and scope of the present disclosure. Equivalent constructions, including functional “means-plus-function” clauses are intended to cover the structures described herein as performing the recited function, including both structural equivalents that operate in the same manner, and equivalent structures that provide the same function. It is the express intention of the applicant not to invoke means-plus-function or other functional claiming for any claim except for those in which the words ‘means for’ appear together with an associated function. Each addition, deletion, and modification to the embodiments that falls within the meaning and scope of the claims is to be embraced by the claims.

The terms “approximately,” “about,” and “substantially” as used herein represent an amount close to the stated amount that is within standard manufacturing or process tolerances, or which still performs a desired function or achieves a desired result. For example, the terms “approximately,” “about,” and “substantially” may refer to an amount that is within less than 5% of, within less than 1% of, within less than 0.1% of, and within less than 0.01% of a stated amount. Further, it should be understood that any directions or reference frames in the preceding description are merely relative directions or movements. For example, any references to “up” and “down” or “above” or “below” are merely descriptive of the relative position or movement of the related elements. Additionally, as used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.

The present disclosure may be embodied in other specific forms without departing from its spirit or characteristics. The described embodiments are to be considered as illustrative and not restrictive. The scope of the disclosure is, therefore, indicated by the appended claims rather than by the foregoing description. Changes that come within the meaning and range of equivalency of the claims are to be embraced within their scope.