Systems and methods for controlling artificial lift units

Abstract

A system and method for controlling multiple artificial lift units at multiple well sites. Processing equipment is installed at multiple well sites. Operating parameters of each of the artificial lift units are obtained using sensing equipment at the well sites and the operating parameters are transmitted in real time from the well sites to the processing equipment installed at the multiple well sites. A modeling function of the processing equipment analyzes trends in the operating parameters of the artificial lift units and an automated machine learning of the processing equipment predicts the condition of at least one of the artificial lift units based on the analyzed trends. The processing equipment determines at least one automated control for the determined condition of at least one of the artificial lift units and responds to the determined condition by implementing the at least one automated control at the at least one artificial lift unit.

Description

[0001] Cross - Reference to Related Applications

[0002] This application claims the benefit of U.S. Provisional Application No. 62 / 931,071, filed on November 5, 2019, the entire content of which is incorporated herein by reference. Background Art

[0003] Without assistance in lifting formation fluids to the Earth's surface, many hydrocarbon wells cannot produce at a commercially viable level. For this reason, various forms of artificial lift are used at the wellsite to produce from these types of wells.

[0004] For example, a reciprocating pump system such as a beam pump unit extracts fluid from the well and employs a downhole pump connected to a drive source at the surface. A rod string connects the surface driving force to the downhole pump in the well. In operation, the drive source cyclically raises and lowers the downhole pump, and with each stroke, the downhole pump lifts the well - produced fluid towards the surface.

[0005] In another example, a gas injection unit can be used. In yet another example, wells producing oil, gas, and water can be assisted in producing fluids with a hydraulic jet pump. This type of system typically includes a surface motive fluid system, a prime mover, a surface pump, and a downhole jet pump. Another type of lift, the PCP, has a surface pumping unit attached to a downhole pump via a rod system that rotates the rod to rotate the downhole pump to bring the fluid to the surface.

[0006] Artificial lift units at the wellsite should be properly monitored and controlled to meet given well conditions. Monitoring and control require a large amount of computation that interprets fluid density and viscosity, the presence of gas, and other conditions that may affect the downhole pressure that the artificial lift unit may encounter.

[0007] Typically, desktop software programs are used to set up and configure the operation of artificial lift units at the wellsite to provide optimization and performance analysis. To configure the unit initially, a user inputs information about a particular implementation into the program, which then calculates various results. This is typically done in an office environment. The results are then communicated to the operators at the site, who then configure the artificial lift unit so that the unit can begin normal operation. However, over time, the efficiency of the artificial lift unit decreases due to changes in well conditions, changes in the system, installation errors, etc.

[0008] Eventually, the artificial lift unit ceases to operate effectively and the well production declines. The unit may also need repair, may become damaged, may malfunction, etc. At some point, the field operator must provide updated information on the units, their operation, well production, etc. to the office operator so that the updated information can be re-entered into the desktop software program and updated configuration results can be calculated and sent back to the field. As expected, there can be significant delays in obtaining the correct information to and from the well site, running the software program, and then sending the results back to the well site to adjust the unit. Typically, there are communication failures. Additionally, in some cases, the software is only used during initial setup and the artificial lift unit may rarely be optimized, which can lead to malfunctions and production losses.

[0009] When production efficiency declines, the field operator needs to adjust or repair the artificial lift unit. In some cases, the unit may have to be shut down or set to maintenance mode to allow repair of the unit and its components. Components of the artificial lift unit may be removed from the wellbore and damaged components may need to be replaced with other components before full load production can be resumed. This typically involves waiting for replacement components to be transported to the location and service equipment to be transported to the location, which can result in significant downtime and production losses.

[0010] Currently, existing control systems for monitoring artificial lift units at the well site may only be able to give an indication of a problem once the problem has occurred. Even then, the existing control systems may only be able to communicate the problem at the well site through standard polling of the SCADA system. Data cannot be analyzed on-site and changes to the artificial lift unit cannot be made at the well site using well modeling control without manual intervention. Instead, once an alarm is issued, maintenance personnel must inspect the artificial lift unit. Then, the engineering team manually runs well site modeling to determine what changes need to be made.

[0011] Due to the limitations of the current control system, any automatic changes to the control at the well site are typically limited to daily updates as required. For more complex problems, manual analysis and intervention are performed from a central location. In some cases, data is transmitted at regular intervals regardless of whether the request is necessary. Without a robust history, data may also be lost during communication failures or during infrequent polling at the central location.

[0012] A control system is needed to assist in the real-time configuration, operation, and optimization of artificial lift units. To this end, the subject matter of the present disclosure aims to overcome or at least mitigate the effects of one or more of the problems set forth above.

[0013] The subject matter of the present disclosure aims to overcome or at least mitigate the effects of one or more of the problems set forth above. Summary of the Invention

[0014] According to the present disclosure, a method is directed to controlling multiple artificial lift units at multiple well sites. The artificial lift units have installed controllers, installed sensing devices, and installed communication systems. The method includes: interfacing a distributed processing device with the installed controllers and installed communication systems at the multiple well sites; connecting the distributed processing devices together in one or more networks; obtaining, at the distributed processing device, the operating parameters of each of the artificial lift units in real time from the installed sensing devices at the well sites; analyzing trends in the operating parameters of the artificial lift units using the modeling capabilities of the distributed processing device; predicting the condition of the artificial lift units using automated machine learning of the distributed processing device based on the analyzed trends; determining automated control for the determined condition of at least one of the artificial lift units using the processing device; and responding to the determined condition by configuring instructions to effect the automated control and transmitting the configured instructions from the distributed processing device to the installed controllers.

[0015] According to the present disclosure, a programmable control apparatus is directed to controlling multiple artificial lift units at multiple well sites. The artificial lift units have installed controllers, installed sensing devices, and installed communication systems. A programmable storage device has program instructions stored thereon for causing a distributed processing device to: interface the distributed processing device with the installed controllers and installed communication systems at the multiple well sites; connect the distributed processing devices together in one or more networks; obtain, at the distributed processing device, the operating parameters of each of the artificial lift units in real time from the installed sensing devices at the well sites; analyze trends in the operating parameters of the artificial lift units using the modeling capabilities of the distributed processing device; predict the condition of the artificial lift units using automated machine learning of the distributed processing device based on the analyzed trends; determine automated control for the determined condition of at least one of the artificial lift units using the processing device; configure instructions to effect the automated control; and transmit the configured instructions from the distributed processing device to the installed controllers to respond to the determined condition.

[0016] According to the present disclosure, a system is designed to control multiple artificial lift units at multiple well sites. The artificial lift units have installed controllers, installed sensing devices, and installed communication systems. The system includes: a communication device and a distributed processing device. The communication device has a network interface for communicating with one or more networks and a local interface for communicating with the installed communication system. The distributed processing device communicates with the communication device and is installed at multiple well sites for the artificial lift units. The distributed processing device is configured to: obtain in real time the operating parameters of each of the artificial lift units from the installed sensing devices at the well sites; analyze the trends of the operating parameters of the artificial lift units using the modeling function of the distributed processing device; predict the condition of the artificial lift units based on the analyzed trends using the automated machine learning of the distributed processing device; determine automated control for the determined condition of at least one artificial lift unit; configure instructions to implement the automated control; and transmit the configured instructions from the distributed processing device to the installed controller in response to the determined condition.

[0017] The subject matter of the present disclosure is intended to overcome or at least reduce the effects of one or more of the problems set forth above. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A control system for monitoring and controlling a number of artificial lift systems in accordance with the present disclosure is shown.

[0019] Figure 2 The control system of the present disclosure is shown in more detail.

[0020] Figure 3 A diagram showing the control application of the disclosed system is shown.

[0021] Figure 4 A control device used in the disclosed system is shown.

[0022] Figure 5 A configuration of a control device connected to a local controller compatible with the disclosed system is shown.

[0023] Figure 6 Another configuration of a control device connected to a local controller retrofitted to the disclosed system is shown.

[0024] Figure 7 A control device in a configuration communicating with the disclosed system is shown.

[0025] Figure 8 A part of the control system having some communication connections is shown.

[0026] Figure 9Shows an example of a reciprocating rod pump system.

[0027] Figure 10A Shows a perspective view of a pumping unit having a counterweight balancing assembly according to the present disclosure.

[0028] Figure 10B Shows for Figure 10A a schematic diagram of a controller and control device of a pumping unit.

[0029] Figure 11A Shows the integration of the control device with a reciprocating pump system having a configured controller.

[0030] Figure 11B Shows the integration of the control device with a reciprocating rod lift system having an existing controller.

[0031] Figure 12A Shows a completion configured according to the present disclosure for artificial lift using a hydraulic jet pump system.

[0032] Figure 12B Shows a bottom hole assembly having a downhole jet pump.

[0033] Figure 12C Shows some surface equipment of the jet pump system relative to the downhole jet pump.

[0034] Figure 13 Shows a schematic diagram of a jet pump controller of the present disclosure.

[0035] Figure 14 Shows a process for controlling a gas injection unit according to the present disclosure.

[0036] Figure 15 Shows a control device in a configuration for proxy communication for the disclosed system. Detailed Description

[0037] A. Control System

[0038] Referring to Figure 1, the control system 50 monitors and controls a number of artificial lift units 100 at different locations to improve the operation of each unit 100. As will be understood, the artificial lift units 100 installed at different well sites may have different capacities, operating requirements, maintenance schedules, lifetimes, etc. In fact, the control system 50 can monitor and control various types of artificial lift units 100, including hydraulic jet pumps (HJPs), gas lifts (GLs), plunger lifts (PLs), gas-assisted plunger lifts (GA-PLs), reciprocating rod pumps (RRPs), hydraulic piston pumps (HPPs), progressing cavity pumps (PCPs), electric submersible pumps (ESPs), etc. In addition, the artificial lift units 100 can be maintained by different technicians 30 and can be operated by different operators 32.

[0039] The control system 50 provides an automated platform for monitoring and controlling many atypical, suboptimal, or harmful "conditions" that affect the unit 100. These conditions can include inefficiencies, low production, damage, alarms, warnings, imbalances, over-pumping, under-pumping, over-injection, under-injection, etc., as discussed in more detail herein. The control system 50 helps to handle all the differences between the type of unit 100, the technician 30, the operator 32, the conditions, etc. by integrating sensing, monitoring, and control of the artificial lift unit 100 into the automated platform of the system. To this end, the control system 50 includes control devices 60 integrated throughout the system 50.

[0040] Typically, some of the control devices 60 are installed on-site at the well site, while some of the control devices 60 are remotely installed at a central processing location or installed in an overall cloud computing platform. Each control device 60 on-site generally includes a power input, a processing unit, a memory, a communication port, and other electronic components in an environmental enclosure. Wired and wireless communications can be used. In this way, the control devices 60 on-site can be installed as stand-alone automated devices or as an addition to existing equipment.

[0041] Each control device 60 has a communication component 62 for transmitting information (signals, measurements, controls, user interface screens, charts, etc.) locally to a user and remotely through one or more communication networks 52, which can be wired, wireless, satellite, cellular, or other forms of networks. The communication of the control device 60 can communicate between the devices 60 and with the users 30, 32, controllers 70 and 72, portable control unit 80, and other components disclosed herein.

[0042] The transmitted information can be shared among the components of the control system 50. For example, the transmitted information can communicate directly with the technician 30 and the operator 32 or with other control devices 60 for access by the technician 30 and the operator 32. For example, a artificial lift unit 100 having a controller 70 installed therein can communicate directly with the technician 30 and the operator 32, can communicate with the control device 60, can communicate with the control device 60 of another pumping unit 100, and / or can communicate with the control device 60 designated for multiple units 100. As will be appreciated, these and any number of possible communication arrangements can be used.

[0043] The control device 60 provides real-time control for the artificial lift unit 100. For example, using real-time data, the control device 60 can control each stroke or injection cycle of the artificial lift unit 100. Automating the control through a preset algorithm can increase production, improve efficiency, and identify problems. Through monitoring and control, for example, the control system 50 can reduce over-pumping and under-pumping in the rod lift unit 100 and can reduce over-injection and under-injection in the gas lift unit 100.

[0044] As Figure 1 An example of a type of artificial lift unit 100A as shown has a control device 60 and a controller 70 to monitor the operation of the artificial lift unit 100A. Some of the operation controls provided by the controller 70 can include typical operation instructions, measurements, and other details related to the general operation of the artificial lift unit 100A. However, according to the present disclosure, the control device 60 further includes features that allow the control system 50 to monitor and control the artificial lift unit 100A for conditions, such that proactive, automated steps can be taken to optimize the artificial lift unit 100A, change the operation of the unit to at least temporarily address the condition, alert the technician 30 and the operator 32 of the condition, and perform other functions disclosed herein. The control device 60 can use its communication device 62 to transmit the monitored condition and can receive instructions remotely or locally to process the condition.

[0045] The sensors of the controller 70 can be permanently installed on the artificial lift unit 100. Sensor data is periodically collected by the control device 60 for long-term storage. The control device 60 can be used to automatically manage calculations and provide remote indication of the monitored conditions. The user (i.e., the technician 30 and the operator 32) can use a mobile device on-site or can use a remote device to connect to the control device 60. The user can download the data history and can perform other functions. The control device 60 can be directly connected to the network 52 (i.e., the cloud) for user access to upload the history to a web application, etc. The uploaded data can be further used for advanced data analysis.

[0046] As another example, asFigure 1 One artificial lift unit 100B as shown may be a reciprocating rod pump unit having a control device 60 and a controller 70 for monitoring the operation of the artificial lift unit 100B. The control device 60 may be part of the controller 70 of the artificial lift unit 100 or may interface with the controller 70 of the artificial lift unit 100.

[0047] In yet another example, an artificial lift unit 100C may have a configured controller 70 for monitoring the operation of the unit 100C. Although the unit 100C may have a controller configured for typical operation and automated control as disclosed herein, the unit 100C may not include a control device 60 that includes specific features that allow for the monitoring and control of the unit 100C for certain conditions, such that proactive steps can be taken to optimize the unit 100C, change its operation to at least temporarily address a condition, etc. Instead, the controller 70 may use its communication device 74 to transmit the monitored conditions and may receive instructions remotely or locally from the control device 60 on the network 52.

[0048] Yet another artificial lift unit 100D may have a controller 72 for its typical operation. However, the unit 100D may not include a control device 60 and the controller 72 may not be preconfigured for automated control. Alternatively, a control device 80 may be used on the unit 100D. The control unit 80 includes features for communicating with the control device 60 for monitoring and controlling for conditions, such that proactive steps can be taken to optimize the unit 100C, change its operation to at least temporarily address a condition, etc. The control unit 80 may use its communication device 82 to send information and receive instructions remotely or locally.

[0049] For the gas lift unit 100A shown herein, the control device 60 may provide high-frequency data recording and storage and instantaneous intelligent alerts via the MQTT protocol. The control device 60 may detect slugs, may send intelligent alerts, and may autonomously control the gas injection rate.

[0050] For the rod lift units 100B, 100D as shown herein Figure 1 the control device 60 may detect various conditions such as balance problems, markings, gearbox torque, high / low load, high rod stress, excessive friction, and downhole valve problems. The control device 60 minimizes the need for manual intervention by detecting load violations and receiving notifications on any device. The lift unit 100 may be shut down by the control device 60 based on detected events or alerts.

[0051] The control device 60 can provide high-frequency data recording and storage and can send instant intelligent alerts via the MQTT protocol. The control device 60 can autonomously control idle time, detect imbalance conditions, identify minimum / maximum loads and rod stresses, monitor load spans, identify real-time pump jams, calculate PIP calculations, and calculate downhole pump jams.

[0052] Although four types of artificial lift units 100A to 100D are shown, it will be understood that a given artificial lift unit 100 that is part of the disclosed system 50 can have other configurations of the prominent components disclosed herein, having more or less autonomy and manual capabilities.

[0053] During operation, one of the artificial lift units 100A to 100D may generate a specific monitoring condition that requires automated control. By way of example only, some monitoring conditions suitable for the automated control of a rod pumping unit include imbalance, marking, under-pumping, over-pumping, and other conditions disclosed herein. Some monitoring conditions suitable for the automated control of a gas lift unit include under-injection, over-injection, and other conditions disclosed herein.

[0054] Depending on the configuration of the units 100A to 100D, the monitored conditions can be transmitted remotely for processing or can be processed locally. For example, some of the artificial lift units 100A to 100B with the control device 60 can determine and process the conditions on their own. The monitored conditions can also be transmitted to the technician 30, the operator 32, other control devices 60, other units 100, etc. In some cases, the other units 100C to 100D can only determine and transmit the monitored conditions for processing by the control device 60 on the network 52. The automated control can be transmitted back to the unit 100C for implementation by a suitably configured controller 70.

[0055] Either way, the technician 30 and the operator 32 can be notified of the monitored conditions through the control system 50. Ideally, the artificial lift units 100A to 100D can be automatically controlled to correct the monitored conditions. On the reciprocating pump unit 100B, for example, over-pumping conditions or under-pumping conditions can be corrected through the automated control of the variable speed drive of the unit 100B. If the unit 100B includes a variable frequency drive for providing continuous variable speed control, such as a Weatherford variable frequency drive (VFD), the control device 60 can automatically access the speed mode suitable for ensuring the above operations.

[0056] If automated control cannot be performed for a particular situation, units 100A to 100D are preferably quickly repaired manually to correct the situation. On reciprocating pump unit 100B, for example, the counterweight of unit 100B may need to be repositioned to maintain balance. Typically, the operator 30 can be notified of the imbalance of unit 100B, but the technician 32 cannot repair unit 100B at this time, or cannot repair unit 100B until after an extended period of time. Automated control can be temporarily implemented at unit 100B as a remedial correction until unit 100B can be repaired manually. For example, the control device 60 can automatically set the pumping speed to ensure that the gearbox does not become overloaded and can minimize production losses due to the imbalance condition.

[0057] The control system 50 allows the handling of the conditions of artificial lift units 100A to 100D when any of a variety of situations occur. In one option, the control system 50 optimizes a given unit 100A to 100D by monitoring parameters, performing calculations, determining harmful conditions, and providing outputs for the automated control of units 100A to 100D. In another option, the control system 50 allows a given artificial lift unit 100A to 100D to continue operating in a sub-optimally operating condition by monitoring parameters, performing calculations, and providing outputs for modifying the operating conditions of units 100A to 100C to remain safe and minimize production losses until manual repair or modification can be performed.

[0058] It can be seen that the control system 50 combines analysis software with hardware at a well site having an artificial lift unit 100. Using the modeling function, the control system 50 can immediately notify personnel (such as operator 30, technician 32, etc.) of changes at the well site and can analyze data to provide alerts and automated control without manual intervention.

[0059] The control system 50 automates well activities using software rather than hardware alone. Therefore, the control system 50 reduces maintenance costs through predictive analysis. When the well site is producing, for example, the control system 50 anticipates and detects problems early, so that the operator 30 can proactively plan maintenance, dispatch personnel, extend the equipment life, and reduce the failure frequency. When the control device 60 is installed at the well site or is available through network communication, the control system 50 uses predictive analysis and artificial intelligence to reduce maintenance costs, to extend the mean time between failures (MTBF), as well as to reduce downtime and minimize delayed production.

[0060] The disclosed control system 50 has been outlined. Figure 2More particularly, the control system 50 of the present disclosure is shown. As already described above, the control system 50 has system computing deployed at multiple locations in a network arrangement. The system computing can be deployed on new devices, in remote terminal units, in the controller 70, at a central location 54, at a facility, at a wellsite 56, or in the cloud 52. In particular, the control system 50 includes control devices 60a to 60d arranged throughout the network arrangement. Depending on its processing needs, the control devices 60a to 60e can be server systems to handle the monitoring and control of several artificial lift units 100, or can be computers to handle the monitoring and control of a specific unit 100.

[0061] For example, the control device 60a in the form of a server system, etc., can be available in the cloud computing platform 52 of the network. As such, the cloud platform 52 can be provided by a service platform such as Microsoft Azure, Google Cloud Platform (GCP), Amazon Web Services (AWS), HiveMQ, etc.

[0062] The control device 60b can be available at a central location 54 such as a service facility. The control device 60c can be directly available at the artificial lift unit 100b with a configured controller 70, and the control device 60d can communicate with the unit 100a. In addition, the control device 60e can be used for the unit 100 at a multi-wellsite 56 with a remote terminal unit 76 and a controller 72. As will be understood, such a remote terminal unit (RTU) is an electronic device with a microprocessor that can interface with components at the wellsite using a telemetry protocol, such as a SCADA (Supervisory Control and Data Acquisition) system, etc. However, different from traditional SCADA systems with limited data storage and scheduled data polling, the control devices 60 of the disclosed system 50 store high-frequency data at the wellsite and transmit the data in real time to the operator's back-end SCADA system 40 at the data center 40 and / or transmit the data in real time to the cloud-based platform 52.

[0063] The control device 60 can have different hardware configurations, including a first configuration for use in combination with an existing wellsite controller 72 and a second configuration with a configured controller 70 and software. Either way, the control system 50 is integrated with a pre-configured controller 70 or retrofitted to an existing field controller 72.

[0064] Unlike traditional SCADA systems with limited data storage and sporadic data extraction, the control system 50 can store unlimited data in the cloud platform 52 and push it to the operator 32 in real time. The control system 50 learns from this stable data stream without programming to optimize the parameters of the artificial lift unit 100 (e.g., to optimize the stroke and pump fill of a rod lift unit). The control system 50 can send alerts only when needed. Preferably, the control system 50 uses the MQTT protocol for high-bandwidth data transmission.

[0065] Communication in the control system 50 can be via wired communication, wireless communication, radio signals, cellular, satellite, Internet protocol, etc. The client data center 40 can be connected to the control system 50 via the cloud 52. The dedicated control device 60c on the artificial lift unit 100b can communicate with the cloud 52 for access by the client data center 40 and the central location 54. The dedicated control device 60c can also communicate with the central location 54 or the facility 54 via wired or wireless communication.

[0066] The control device 60b at the central location 54 can communicate with the cloud 52. For those units 100a lacking a control device 60, the controller 72 of the unit 100a can communicate with the control device 60b at the central location 54, communicate with the control device 60b within the communication range, etc. The multi-well site 56 can have a local control device 60e, which can communicate with the remote control device 60b at the central location 54. These and other arrangements for system computing and network communication can be used in the disclosed control system 50.

[0067] B. Control Devices and Control Applications

[0068] Figure 3 A diagram of the system application 200 of the disclosed system is shown. Depending on the installation, the system application 200 runs on system hardware 202, which includes one or more of a server, a control device, a remote terminal unit, a computer, a laptop, a mobile device, a controller, etc., as disclosed herein. As will be understood but not necessarily shown, the system hardware 202 includes a central processing unit, an input-output interface, a communication interface, a memory, and other necessary components.

[0069] System application 200 includes a real-time application 210 and a control application 220. The real-time application 210 is an existing application suitable for the monitoring and operation of artificial lift units, such as reciprocating rod lift (RRL) units, desolvation (DLQ) systems, plunger lift units, gas lift units, etc. The real-time application 210 has a layout of components, and the components include board-specific drivers, input-output interface layers, core applications, flash file systems, databases, and artificial lift modules. The real-time application 210 is connected to various input-output modules (e.g., MIM) for communicating with sensors and the like.

[0070] Here, one of the artificial lift modules includes a reciprocating pump controller (RPC) module, which has a pump manager, variable speed drive, fluid production, episode storage, and other functional elements. Another artificial lift module among the artificial lift modules includes a desolvation (DLQ) module with MWGL, ProControl, and other functional elements. Other artificial lift modules may include those for progressing cavity pumps (PCP), flow control technology (FCT), net oil computer (NOC), remote terminal unit (RTU), etc.

[0071] As disclosed herein, the features of the control application 220 may be suitably available on the cloud 52 or on the control device 60. The control application 220 includes a supervisory control and data acquisition (SCADA) module 230, an analysis-modeling module 240, a cloud docking 250, and an analysis module 260. Inter-process communication (IPC) is provided between applications 210 and 220.

[0072] The SCADA module 230 may be based on the CYGNET TM SCADA platform. CYGNET is a trademark of Weatherford Technology Holdings, LLC. The SCADA module 230 allows the control application 220 to communicate directly with the controller 70 of the artificial lift unit. The SCADA module 230 includes a polling function, a communication function (TCP / serial / ...), and a historical function for storing data. The SCADA module 230 is connected to the cloud service 52 via the cloud interface 250.

[0073] The analysis-modeling module 240 includes module services, directory services, security token services, well analysis and modeling interfaces, and databases. The well analysis and modeling interfaces provide modeling functions (e.g., algorithms for the analysis, adjustment, and flow assurance of artificial lift units). The analysis-modeling module 240 can detect and generate alarms based on the monitored conditions. Alarms for reciprocating rod lift may include alarms related to gearbox torque, rod stress, rod threading, production slugging, and downhole valve problems. Alarms for gas lift may include multi-point injection, shallow injection, etc.

[0074] The analysis module 260 performs a number of analysis functions, which include predicting well and equipment failures, collecting data, training models on the cloud (52), scoring when running on the cloud (52), etc. The analysis module 260 communicates with the analysis-modeling module 240 via a Representational State Transfer (REST) Application Programming Interface (API) 262. To perform the analysis, data passes through a Python Data Preparation Script 264, and the cleaned data is stored in a staging area 266. Java Jobs 267 are used to store the prepared data and the result data. The prepared data is input into the runtime code (scoring) 272 of the machine learning model 270, and results are returned. Example platforms for the machine learning model 270 include TENSORFLOW TM , which provides an end-to-end open-source platform for machine learning. (TENSORFLOW is a trademark of Google LLC.) Other machine learning platforms can be automated according to the present disclosure to predict the condition of artificial lift units based on analyzed trends. Orchestration 280 of the data pipeline for building batch jobs is provided to the analysis module 260 through a workflow management system, which can be based on the Luigi or Airflow workflow engine.

[0075] The predictive features of the control application 220 can be used to plan maintenance. Wellsite analysis with a direct controller interface using SCADA allows the control application 220 to update setpoints and control the controllers 70, 72 of the unit. By analyzing current data, the control application 220 can monitor and can immediately notify of intelligent alerts, status changes, etc. Physics-based models in the modeling function can be created on-site at the control application 220 to enhance / optimize autonomous control. By monitoring and analyzing current data at the wellsite controllers 70, 72, the control application 220 publishes a database according to the data characteristics. The notifications can be predictive, not just reactive.

[0076] The system application 200 on the control device 60 is equipped to run engineering models in real time. The engineering models in the modeling function are manually configured to provide a digital representation of the characteristics of the well, such as equipment, depth, deviation, reservoir characteristics, etc. The system application 200 automatically collects sensor data in real time and executes the engineering models to produce specified results. The system application 200 uses these results to determine and change the operating parameters of the well to achieve optimization.

[0077] For the rod lift unit 100, the system application 200 collects, analyzes, and automatically historicizes each card on-site. The system application 200 uses a modified Everitt-Jennings analysis and uses automatic pattern matching and recognition to detect anomalies in the dynamometer card. The system application 200 detects changing well conditions based on analysis results, card shape, and trend data, etc. Setpoints can be changed on the dynamometer card. The system application 200 can perform autonomous control, such as automatically adjusting idle time to maximize well efficiency. The system application 200 can perform downhole analysis on legacy, existing, or installed controllers 72, infer production values, and perform pump intake pressure (PIP) calculations.

[0078] The automatic monitoring of the rod lift unit 100 can involve high-frequency data logging and instant alert notifications via MQTT for controller alerts. Elements that can be monitored and controlled include idle time, minimum / maximum structural load, load span, marked bottom / top, gearbox load, imbalance condition, high rod stress, downhole pump valve problems, excessive friction, pump fill, pump intake pressure, pump shut-off stroke, load cell drift, position sensor stroke upper limit (TOS), inferred production error, etc. For those rod lift units with variable speed drives, elements for monitoring and controlling can also include gas intrusion control, minimum / maximum strokes per minute (SPM), incremental speed, and optimal pump fill setpoint.

[0079] For the gas lift unit 100, the system application 200 can monitor and control multiple wells, perform well test verification, and adjust the automatic model to improve model accuracy. The application 200 can generate alerts based on nodal analysis and trend data to alert users of changing conditions. The inferred production can be calculated daily based on the adjusted well model and current operating conditions. The system application 200 can use the following well analysis tools based on well test data or daily operating conditions to identify lift opportunities. The system application 200 can perform autonomous control, such as automatically adjusting the injected gas to maximize production.

[0080] For the gas lift unit, elements for monitoring can include high-frequency data logging and availability, instant alert notifications via MQTT for controller alerts, and intelligent alerts for determining when slugging occurs in gas lift or natural flow wells. Autonomous control of the gas injection rate can be provided based on nodal analysis calculations (using actual rate data).

[0081] C. Control Device Connection

[0082] Figure 4Shown is a control device 60 used in the disclosed system 50, which is connected to other remote terminal units 72 having sensors 76 and is connected to a data center 40 via a cloud 62. The control device 60 includes a SCADA module 63 and a processor 61. The SCADA module 63 communicates with the remote terminal units 72 of the artificial lift unit having the sensors 76 connected thereto. The processor 61 communicates with the data center 40 via the cloud 52.

[0083] For its part, the data center 40 includes a SCADA cloud agent 42 that communicates with the cloud 52. The SCADA module 43 allows users of the system application 44 to communicate with the control device 60. Other data consumers 46 can receive information of the control device 60 via the SCADA 42 cloud agent.

[0084] Figure 5 Shown is a configuration of the control device 60 connected to an artificial unit controller 70, which is compatible with the disclosed system. The control device 60 has a control application 200, and the control application 200 has an analysis module 260, an analysis-modeling module 240, and a SCADA module 230 that can run on a Linux kernel or other platforms. Each of the modules 230, 240, and 260 can communicate with the cloud service 52 and can communicate with each other. The SCADA module 230 is used to communicate with the local controller 70, and the local controller 70 is compatible with the configured control device 60.

[0085] Figure 6 Shown is another configuration of the control device 60 connected to a local controller 72 that is retrofitted to the disclosed system, the local controller 72. As described above, the control device 60 has a control application 220, and the control application 220 has an analysis module 260, an analysis-modeling module 240, and a SCADA module 230 that can run on a Linux kernel or other platforms. Each of the modules 230, 240, and 260 can communicate with the cloud service 52 and can communicate with each other. The SCADA module 230 is used to communicate with the existing local controller 72. Here, the SCADA module 230 communicates with a real-time control application 210 of a unit running on a separate Linux kernel. The control device 60 includes communicating with an input / output module 73 of a local sensor 74 for an artificial lift unit.

[0086] D. Control Device

[0087] After understanding the software and some communications of the control device, Figure 7 Shown is the control device 60 in a configuration communicating with the disclosed system. The control device 60 includes a plurality of communication components, and the plurality of communication components include a serial port 62a, an Ethernet port 62b, and wireless modules 62d to 62e. The wireless module may include wireless or a WIFI module 62e and an internal wireless broadband communication or cellular module. (Bluetooth is a registered trademark of BLUETOOTH SIG, Inc.)

[0088] The serial port 62a can be connected to an existing serial radio device 73 at the well site. Another serial port 62a is connected to the remote terminal unit 72 of the manual unit at the well site.

[0089] For remote communication, the Ethernet port 62b can be connected to an external cellular radio or LTE modem 62c, and the external cellular radio or LTE modem 62c can communicate with a public Internet or a private internal network 52. As described herein, typical entities that can access the network 52 include data centers, commercial users, etc. Alternatively, the control device 60 can have an internal cellular module 62d and an antenna to communicate with the network 52.

[0090] Local users at the well site can use a portable device 80 (such as a laptop computer, a smart phone, etc.), which can be connected to the control device 60 via a local wireless connection 82e (to the wireless module 62e) or via a wired connection 82b (through a crossover Ethernet cable connected to the Ethernet port 62b). The portable device 80 can also be connected to the network 52 via a cellular connection 82a.

[0091] E. System Connections

[0092] Figure 8 A part of the control system 50 with some other communication connections is shown. As shown, the disclosed control system 50 features running in the cloud 52, which can be a public Internet or a private internal network. For example, analysis, analytics and modeling, and SCADA services can run on the cloud 52. The administrator terminal 34, the end-user terminal 36, the terminals 80 of the operator 30 and the field technician 32, and the well-site control device 60 have various applications and communicate with each other and with the services on the cloud 52 using multiple communication protocols, Transmission Control Protocol / Internet Protocol (TCP / IP), Machine-to-Machine (M2M) / "Internet of Things" connection protocol (MQTT), Hypertext Transfer Protocol Secure (HTTPS), RUDP, Virtual Desktop Infrastructure (VDI), Bluetooth, Serial / IP, etc.

[0093] For example, the system administrator terminal 34 uses a device management application and communicates with services on the cloud 52 via TCP / IP, HTTPS, RUDP, or VDI. The end-user terminal 36 uses an end-user application and communicates with services on the cloud 52 via HTTPS, RUDP, or VDI. The operator 30 and the field technician 32 use a portable terminal 80 with a mobile application to communicate with services on the cloud 52 via TCP / IP and communicate with the wellsite control device 60 via a wired or wireless connection. The control device 60 has a browser interface for on-site configuration and information.

[0094] The wellsite control device 60 communicates with services on the cloud 52 using TCP / IP or MQTT. The wellsite control device 60 can communicate with components of the artificial lift unit 100 via a serial / IP connection, or can be connected to the artificial lift unit 100 via a serial / IP connection to a cellular or radio connection. Preferably, the control system 50 uses MQTT to publish instant notifications instead of relying solely on SCADA polling.

[0095] Many available applications of the system 50 include links, RTU applications, communication proxy applications, SCADA, optimization applications, artificial intelligence applications, etc.

[0096] Application connections can be implemented in various ways. In the case of online use, the operator 30, technician 32, or other users can be physically located through the control device 60 via a cellular modem or a customer radio network with an Internet connection. The user can use a wireless communication connection to the control device 60 for configuration or status.

[0097] In the offline case, the operator 30, technician 32, or other users can be physically located through the control device 60, but neither the user nor the control device 60 has an Internet connection. The user can still use a local wireless communication (e.g., Bluetooth) to connect to the control device 60.

[0098] In the case of proxy use, the operator 30, technician 32, or other users can be physically located through the control device 60. However, the device 60 does not have an Internet connection, but the users have an Internet connection on their phone or tablet and can connect and configure the device 60. In the case of remote use, the operator 30, technician 32, or other users are not physically located through the control device 60, but the device 60 has an Internet connection.

[0099] F. Reciprocating Rod Lift Unit

[0100] As described herein, the artificial lift unit 100 can be a reciprocating rod lift unit. For example, Figure 9Shown is a reciprocating rod lift unit 100 for producing fluid from a well. The downhole pump 14 has a barrel 16, and the barrel 16 has a standing valve 24 at the bottom. The standing valve 24 allows fluid to enter from the wellbore but does not allow fluid to leave. Inside the pump barrel 16, a plunger 20 has a traveling valve 22 at the top. The traveling valve 22 allows fluid to move from below the plunger 20 to the production pipe 18 above, but does not allow fluid to return from the pipe 18 to the pump barrel 16 below the plunger 20. A drive source (e.g., a pumping unit or a pumping unit 112) at the surface is connected to the plunger 20 through a rod string 12 and cyclically moves the plunger 20 up and down during the upstroke and downstroke.

[0101] During the upstroke, the traveling valve 22 closes, and any fluid above the plunger 20 in the production pipe 18 is lifted toward the surface. At the same time, the standing valve 24 opens and allows fluid to enter the pump barrel 16 from the wellbore.

[0102] At the upper limit of the stroke, the standing valve 24 closes and holds the fluid that has entered the pump barrel 16. In addition, during the entire upstroke, the weight of the fluid in the production pipe 18 is supported by the traveling valve 22 in the plunger 20 and thus also by the rod string 12, which causes the rod string 12 to stretch. During the downstroke, the traveling valve opens, which causes the load on the rod string 12 to rapidly decrease. The movement of the plunger 20 from the transition point to the lower limit of the stroke is called the "fluid stroke" and is a measure of the amount of fluid lifted by the pump 14 in each stroke.

[0103] Since there are no sensors to measure the conditions at the downhole pump 14, which may be thousands of feet underground, surface measurements of the position and load of the rod string 12 at the pumping unit 112 are used together with numerical methods to calculate the position of the pump plunger 20 and the load acting on the plunger 20. These surface measurements are typically made at the top of the polished rod 15, which is part of the rod string 12 passing through the stuffing box 13 at the wellhead. A pump controller 150 is used to monitor and control the pump system 10.

[0104] To effectively control the reciprocating rod lift unit 100 and avoid costly maintenance, the rod pump controller 150 can collect system data and adjust the operating parameters of the unit 100 accordingly. Typically, the rod pump controller 150 collects system data such as load and rod string displacement by measuring these characteristics at the surface.

[0105] The current pumping unit, such as the beam pumping unit 112, is balanced to reduce energy consumption. The balancing subsystem uses weights 134 attached at predetermined points along the crank arm 126 to counteract a portion of the rod load in the well. The positions of these weights 134 are typically calculated as part of an initial setup and are based on a number of factors, many of which include but are not limited to the physical characteristics (length, weight, etc.) of the rod string 12, the fluid load, the size of the pumping unit 112, the type of gearbox 132, the type of motor 130, and the like. The calculations involved in setting the positions of the weights have been known to those skilled in the art of conventional pumping units for many years.

[0106] However, during normal pumping operations, the rod load can change. This results in a condition known as "unbalance," and it is desirable to correct this condition. Otherwise, energy usage increases, and the operation of the reciprocating rod lift unit 100 is not optimal, which can reduce the working life of some components.

[0107] Now referring to Figure 10A , the reciprocating rod lift unit 100 according to the present disclosure is shown in further detail and includes a frame 102, a walking beam 110 disposed on the frame 102, a crank assembly 120 connected to the walking beam 110, and an actuator 130 connected to the crank assembly 120. The polished rod 118 for the reciprocating rod system is connected to the head 112 of the walking beam 110 using a cable 114 and a polished rod hanger 116.

[0108] The frame 102 is mounted on a pumping unit base and may include one or more front columns 104 and one or more rear columns 106 that are joined together to form an A-frame to support the walking beam 110, and the walking beam 110 is pivotally supported by a bearing assembly 108.

[0109] The crank assembly 120 includes a connecting rod arm 122 that is coupled to one end 110a of the walking beam 110 through a tail or balancer bearing assembly 124. As shown, the unit 100 may have two connecting rod arms 122 that are joined by a balance beam 125, and the balance beam 125 is connected to the walking beam 110 through a bearing assembly 124. Each connecting rod arm 122 is pivotally connected to a crank arm 126 through a crank pin assembly 128, which is also referred to as a piston pin.

[0110] The actuator 130 mainly includes an electric motor that rotates the crank arm 126. Typically, a gearbox 132 is connected to the motor 130 and reduces the rotation of the motor to a crankshaft 133 that is connected to the crank arm 126. For balancing as discussed herein, one or more counterweights 134 may be attached to the crank arm 126.

[0111] As the actuator 130 rotates the crank assembly 120, the walking beam 110 rocks on the pivot 108 of the frame, and thus the polished rod 118 reciprocates the rod string system and the downhole pump in the well. During operation, for example, the motor 130 and the gearbox 132 rotate the crank arm 126, which causes the end 110a of the walking beam 110 to move up and down via the connecting link arm 122. The up and down movement of the end 110a causes the walking beam 110 to pivot about the bearing assembly 108, which results in the downstroke and upstroke of the horsehead 112.

[0112] During the upstroke, the motor 130 and the gearbox 132 overcome the weight and load on the horsehead 112 with the help of the counterweight 134 and pull the polished rod string 118 upward from the wellbore, which reciprocates the rod string and the downhole pump in the well to lift the fluid. During the downstroke, the motor 130 rotates the crank arm 126 with the help of the weight and load on the horsehead 112 to raise the counterweight 134.

[0113] The counterweight 134 is selected based on the weight and load of the reciprocating rod string system (i.e., the force required to lift the reciprocating rod and the fluid above the downhole pump in the wellbore). In one embodiment, the counterweight 134 can be selected such that one or more components of the pumping unit 100 have substantially symmetric accelerations and / or velocities during the upstroke and the downstroke. The component can be any moving component of the pumping unit 100, such as the connecting link arm 122, the piston pin assembly 128, the crank arm 126, the balance beam 125, the walking beam 110, the horsehead 112, etc.

[0114] According to the present disclosure, the reciprocating rod string lifting unit 100 includes a management assembly 140 for balancing / adjusting the unit 100. As described above, the management assembly 140 can be part of the unit 100 or incorporated into the unit 100, can include local components and remote components, and can have other configurations as described herein.

[0115] The management assembly 140 includes mechanically adjustable components on the pumping unit 100 for adjusting the position of the counterweight 134 on the crank arm 132 and / or changing the position of the piston pin that connects the connecting link arm 122 to the crank arm 126, which changes the balance of the unit 100. Details related to such mechanically adjustable components can be found in the co-pending U.S. application Ser. No. 15 / 345,288, entitled “Apparatus and Methods for Counterbalancing a Pumping Unit,” filed on Nov. 7, 2016, and the entire content of this U.S. application is incorporated herein by reference.

[0116] As shown herein, the management assembly 140 also includes a sensor interface 150 and a controller 160 for monitoring and controlling the reciprocating rod string lifting unit 100. As forFigures 1 to 2 For the system 50, the controller 160 can be a configured controller (70) of the artificial lifting unit 100.

[0117] The sensor interface 150 has one or more sensors 152 attached to one or more moving parts of the reciprocating rod type lifting unit 100. The sensors 152 measure one or more parameters related to the imbalance between the load from the polished rod string 118 and the counterweight 134. The one or more parameters can include at least one of the speed and acceleration of the moving part, and can include the orientation of the counterweight 134.

[0118] Although the sensors 152 are shown attached at one location on the reciprocating rod type lifting unit 100 in Figure 10A , it should be understood that various types of sensors, such as sensors for orientation, speed, acceleration, etc., can be attached at different locations on the unit 100. Generally, the sensors 152 of the sensor interface 150 can be attached to any one of a plurality of components on the unit 100, and the sensors 152 can be arranged on several components. For example, the sensors 152 can be attached to the link arm 122 to measure at least one of the speed and acceleration of the link arm 122, and can measure the orientation of the counterweight 134. The sensors 152 can be attached to the link arm 122 near the piston pin assembly 128, so that the controller 160 can measure the speed and / or acceleration of the counterweight 134. Alternatively, the sensors 152 can be attached to the walking beam 110 or the horsehead 112 to measure the acceleration and / or speed of the walking beam 110 or the horsehead 112. These and other configurations are possible.

[0119] During operation, the sensor interface 150 can send the measurement results to the controller 160 via wired, wireless, satellite, cellular or other forms of communication. As such, the controller 160 includes a computer program for analyzing the measurement results from the sensor interface 150 and providing various forms of output. In particular, the controller 160 can determine the imbalance of the counterweight 134 based on the measurement results from the sensor interface 150, and can provide a balance solution, such as providing an adjustment to balance the reciprocating rod type lifting unit 100.

[0120] With the understanding of the pumping unit 100, the discussion turns to Figure 10B , Figure 10B which schematically illustrates the elements of the monitoring component 140 according to one embodiment of the present disclosure. Similarly, the monitoring component 140 includes a sensor interface 150 and a controller 160.

[0121] The sensor 152 may include an orientation sensor 154 for measuring an orientation, such as the orientation of the counterweight (134). In one embodiment, the orientation sensor 154 may be a magnetometer that helps to describe the orientation of the element to which it is attached in the Earth's magnetic field. Additionally, it may provide information about the arrangement or position of the counterweight (134) relative to the element to which the sensor 154 is attached.

[0122] The sensor 152 may include a speed sensor 156, which may be a gyroscope, such as a 3-axis gyroscope, but the speed sensor 156 may be any suitable sensor for measuring speed. The sensor 152 may include an acceleration sensor 158, which may be an accelerometer, such as a 3-axis accelerometer, but the acceleration sensor 158 may be any sensor suitable for measuring acceleration.

[0123] Although Figure 10B both the speed sensor 156 and the acceleration sensor 158 are shown, the sensor interface 150 may include only one of the speed sensor 156 and the acceleration sensor 158, and it may also be configured to sense speed or acceleration on only one axis.

[0124] The sensor interface 150 may also include a control board 151 connected to the sensor 152. The control board 151 may include input / output ports for connecting to the sensor 152. The control board 151 may establish wired or wireless communication with the controller 160.

[0125] The sensor interface 150 may be permanently mounted on the reciprocating rod lift unit 100 or may be a portable component that is mounted and removed as needed on a given unit. In one embodiment, the sensor interface 150 may include a sealed housing that encloses the sensor 152 and the control board 151. The sensor interface 150 may also include a structure that allows the sensor interface 150 to be securely attached to the moving parts of the pumping unit 100.

[0126] Just as the sensor interface 150 can be permanent or portable, the controller 160 can also be permanent or portable. For example, the controller 160 can be a computer or a mobile device, such as a smart phone or a tablet computer. The controller 160 can be incorporated as a permanent element into the overall control system of the reciprocating rod lifting unit (100), or the controller 160 can be a portable or remote component that docks with the reciprocating rod lifting unit (100). The controller 160 can include one or more interfaces 162, such as a user interface, a display, a communication device, etc., and can include a computer program or application for analyzing the measurements from the sensor interface 150, detecting the balance condition in the reciprocating rod lifting unit (100) such as any imbalance and / or providing a solution for the balance / adjustment unit (100).

[0127] In providing a solution for balancing / adjusting the reciprocating rod lifting unit (100), the controller 160 can provide an adjustment to the mechanically adjustable component 142 of the component 140. For example, the controller 160 can include a program for displaying a graphical representation of the movement of the pumping unit (100), and can indicate an adjustment of the counterweight (134) to achieve balance. In most cases, the adjustment of the counterweight (134) may involve moving the heavy object on the crank arm (126) to a new position, but may involve adding or removing heavy objects. In most cases, these adjustments must be done manually by a technician. In the case where the pumping unit (100) has this ability, the adjustment of the counterweight (134) or other balance parameters can be done automatically using a movable heavy object, etc. In providing a solution for balancing / adjusting the reciprocating rod lifting unit (100), the controller 160 can provide an adjustment to the motor 130 of the pumping unit (100). For example, in the co-pending U.S. application 15 / 643,769 filed on July 7, 2017 Figures 4 to 1 1 discloses the details of these solutions, and the entire content of this U.S. application is incorporated herein by reference.

[0128] As described above, a artificial lift unit, such as a reciprocating rod pump unit 100, may or may not have a pre-configured controller, such as that in the controller 160. For example, Figure 11A shows the integration of the control device 60 with the reciprocating rod lifting unit 100 having a compatible, pre-configured controller 160. Here, the controller 160 is a rod pump optimization controller. Examples of such controllers include those for rod pump optimization available from Weatherford International Controller. (WELLPILOT is a registered trademark of Weatherford Technology Holdings, LLC.) The controller 160 is connected via the input / output module of the sensor interface 150 to the various sensors 152 of the unit 100. The load cell and the inclinometer communicate with the controller 160. The control device 60 communicates directly with the controller 160, which is preconfigured for integration.

[0129] Figure 11B Shows the integration of the control device 60 with the reciprocating rod lift unit 100 lacking a compatible, preconfigured controller. Alternatively, the unit 100 includes an existing controller 72, which is a rod pump controller. Examples of such controllers include as described herein The unit 100 includes various sensors 152, inclinometers, load cells, etc. These communicate with the input / output module 75 of the unit controller 72, and the unit controller 72 commutates with the control device 60. For de-liquefaction, the unit 100 includes a de-liquefaction (DLQ) system 90. Examples of such systems include De-liquefaction system. The system 90 includes a sensor 92 that communicates wirelessly with the control device 60. The docking (MIM) 94 connects the sensor 94 to the wireless communication 96. The multi-variable transmitter communication interface module (MVT) 98 for other units (100) can communicate with the wireless communication 96. Although not shown, a gas lift controller can be attached to the MIM 94 and the MVT 98 and then communicate. The wireless communication 96 of the DLQ system 90 in turn communicates with the control device 60.

[0130] Jet pump unit

[0131] In addition to the reciprocating rod lift unit disclosed above, the control system 50 of the present disclosure can be used with other artificial lift units such as gas lift units, gas injection units, etc. For example, Figure 12A Shows a completion 10 having another form of artificial lift unit 300 according to the present disclosure. The completion 10 includes a casing 12 that extends into the well to one or more downhole production zones 17 in the formation. As will be understood, the casing 12 typically includes a liner 15 that has perforations, screens 18, isolation packers 19, inflow control devices, sliding sleeves, etc. at the production zone 17 for allowing formation fluids to enter the annulus 14 for final production at the surface.

[0132] The pipe 20 extends from the surface into the well and defines a through - hole 22 that communicates with the bottom hole assembly 24. As schematically shown herein, the bottom hole assembly 24 includes a packer 16 that seals the annulus 14 in the casing 12 / liner 15 as the case may be. The bottom hole assembly 24 further includes a production port 26 that communicates the through - hole 22 with the annulus 14.

[0133] As is known, a typical well can start its life with a high productivity generated by the natural flow of the produced fluids from the well. However, as the formation depletes, the productivity decreases, and thus artificial lift is required. Accordingly, the completion 10 herein is configured with a hydraulic jet pump unit 300 suitable for artificially lifting the produced fluids from the well. The lifting equipment for the unit 300 includes a downhole jet pump 350 installed in the bottom hole assembly 24 and includes a surface power fluid unit 360. A regulating unit 370 at the surface can condition the received fluid and can separate oil from gas and water. Finally, the lift unit 300 includes a jet pump controller 400, which can be used for several wells or can serve a single well individually.

[0134] With a general understanding of the completion 10 and the hydraulic jet pump unit 300, Figure 12B A portion of the bottom hole assembly 24 of a completion with an example of a downhole jet pump 350 according to the present disclosure is shown in more detail. Also, as shown, the completion 10 includes a casing 12 (or liner 15) for the well. A bottom hole packer 16 seals the annulus 14 of the casing 12 (or liner 15) with a pipe 20 disposed in the casing 12. Additionally, the pipe 20 includes a through - hole 22 that has one or more production ports 26 that communicate with an upper annulus 14a. Generally, the bottom hole assembly 24 on the pipe 20 can include a plurality of interconnected housings, components, pipe fittings, etc. connected together, which are not necessarily depicted herein for simplicity.

[0135] As previously mentioned, the production equipment is configured for hydraulic lift using the downhole jet pump 350. The downhole jet pump 350 has been run into position within the bottom hole assembly 24. For example, the assembly 24 can include one or more internal elements (e.g., seals or seats) 28a - 28b disposed relative to one or more ports 26. These elements 28a - 28b can be hole seals in the form of polished holes for engaging seals of the downhole jet pump 350 inserted therein. In some implementations, the elements 28a - 28b can include seal rings, joints, latch profiles, seats, etc. for engaging the downhole jet pump 350 removably inserted into the through - hole 32 of the device. As an example, a profile such as an X - lock profile can be provided in the through - hole 22 to lock the disclosed jet pump 350 in place.

[0136] The lifting device may also include a fixed valve 357 disposed at the inlet of the downhole jet pump 350. The fixed valve 357 may be part of (or mounted on) the downhole jet pump 350 and may operate therewith. Alternatively, the fixed valve 357 may be a separate component operating independently.

[0137] The downhole jet pump 350 includes a nozzle 352, an inlet 354, a throat 355, a diffuser 356, and an outlet 358. As described herein, the components of the downhole jet pump 350 are preferably configured to suit production requirements and downhole conditions. For example, different configurations and materials may be used for the nozzle 352, the throat 355, and the diffuser 356.

[0138] During a hydraulic lifting operation, a power fluid unit (360) including a power fluid storage device, a surface pump, a prime mover, a flow control member, etc. pressurizes the power fluid PF and injects the pressurized power fluid PF into the through-hole 22 of the pipe 20. The power fluid PF travels downward along the pipe 20. At the jet pump 350, the power fluid PF enters the inlet nozzle 352. At the same time, the downhole-segregated production P in the lower annulus 14b can flow upward through the through-hole 22, through the fixed valve 355, and into the inlet 354 of the downhole jet pump 350. As such, the fixed valve 355 prevents the production fluid P from escaping from the downhole hydraulic jet pump 350 in the absence of a sufficient fluid level.

[0139] The nozzle 352 utilizes the Venturi effect to reduce the fluid pressure of the power fluid PF. This sucks the production fluid P into the throat 355 of the pump, where the power fluid FP and the production fluid P combine. The mixed fluid MF is then transferred to the pump diffuser 356, where the pressure increases at the pump outlet 358, so that the mixed fluid MF can leave the port 26 and can rise to the surface in the annulus 14a.

[0140] In a previous arrangement, the jet pump 350 operates using the power fluid PF transmitted downward from the surface along the through-hole 22, such that the mixed fluid MF can travel upward along the annulus 14a. Reverse operation may also be used. In particular, the jet pump 350 may be installed in the through-hole 22, and the power fluid PF may be transmitted downward from the surface along the annulus 14a, where the power fluid PF may then enter the jet pump 350 through the ports 26, 358. As previously described, the production P rising upward from the downhole along the through-hole 32 also enters the jet pump 350 and the two fluids mix therein. Finally, the mixed fluid MF then travels upward through the through-hole 22 of the pipe to the surface.

[0141] Figure 12BSome components of the jet pump unit 300 are shown in more detail. The power fluid unit 360 on the skid at the surface can serve a single well (as shown here) or can be used for several wells. The power-fluid unit 360 has a prime mover 368 and a surface pump 362 and is used to inject power fluid into the wellhead 11 to operate the downhole jet pump 350 of the bottomhole assembly 24 disposed in the borehole 22 of the pipe 20.

[0142] The power fluid unit 360 can pressurize the produced reservoir fluid to operate the downhole jet pump 350. For example, the surface pump 362 can include a multiplex pump ranging from 60 to 625 HP, and the prime mover 368 can include an electric motor or a multi-cylinder driver controlled by a variable speed drive 369.

[0143] The regulating unit 370 on the skid at the surface includes a container 372 for receiving the produced fluid from the well and the discharged power fluid. The regulating unit 370 cleans and conditions the received fluid and can separate oil from gas and water. Finally, the lifting unit 300 includes a jet pump controller 400, which can serve a single well (as shown) or can be used for several wells.

[0144] Figure 12C A schematic diagram of the jet pump controller 400 of the present disclosure is shown. The controller 400 includes a processing unit 402, a memory 404, software 406, a drive interface 408a, a sensor interface 408b, and an input / output interface 408c. The processing unit 400 and the memory 404 can use any acceptable device suitable for on-site use at a well site having artificial lift equipment according to the present disclosure. For example, the processing unit 402 can include a suitable processor, digital electronic circuits, computer hardware, computer firmware, computer software, and any combination thereof. The memory 404 can include any suitable storage device for computer program instructions and data, such as EPROM, EEPROM, flash memory devices, magnetic disks, magneto-optical disks, ASICs (application specific integrated circuits), etc.

[0145] The software 406 operating on the controller 400 monitors the inputs from a plurality of sensors 420, performs analysis, and controls the prime mover using the variable speed drive 368 for driving the hydraulic jet pump unit (300). The software 406 includes algorithms in a modeling function for calculating the parameters of the hydraulic jet pump unit (300). These algorithms can be similar to the algorithms available from the Jet Pump Evaluation and Modeling Software (JEMS) software available from Weatherford International. The controller 400 is also connected or integrated with the control device 60 according to the present disclosure, which serves the purposes disclosed herein.

[0146] The drive interface 408a is connected to a variable speed drive 369 of a prime mover (i.e., a motor) of a surface pump for operating the unit (300). If desired, the drive interface 408a can also be connected to a controllable flow device 367 to control the discharge pressure in the discharge line of the surface unit (360).

[0147] The sensor interface 408b is connected via a junction box 365 to various sensors 420, such as pressure sensors, vibration sensors, flow meters, level sensors, and temperature sensors. As discussed in more detail below, these sensors 420 are configured and arranged on the hydraulic jet pump unit (300) depending on the type of surface pump used.

[0148] According to one aspect and Figure 12C as shown, the unit 300 can also include a cavitation sensor 420', such as a microphone, accelerometer, vibration sensor, or gyroscope, associated with the wellhead 11 and / or the downhole jet pump 350. The cavitation sensor 420' can be configured to detect vibrations or other cavitation indicators, as taught in co-pending U.S. application Ser. No. 15 / 252,412, filed Aug. 31, 2016, which is hereby incorporated by reference.

[0149] The input / output interface 408c can be connected to a display 410, an input device 412, and a communication interface 414. The display 410 on the controller 400 can be a touch screen for the input device 412. The communication interface 414 can allow downloading of inputs / uploading of outputs via a memory device, wireless communication, etc.

[0150] At the controller 400, a field operator can manually input initial configuration data into the controller 400 via the display 410 and the input device 412. Alternatively, the initial configuration data can be input via the communication interface 414, such as by downloading from a storage device or from a satellite or wireless communication. The initial configuration data typically includes configuration information and computational analysis, such as the configuration information and computational analysis available in Weatherford's JEMS program. A number of models have been constructed in the art based on theoretical and empirical analysis of jet pumps, and the computations of the controller 400 can be based on any suitable model.

[0151] After the appropriate sizing of the initial configuration, nozzle, and throat from the input, as well as the configuration of the operating parameters of the power fluid unit (360), the controller 400 uses sensor inputs and calculations in real time to predict inefficiencies (e.g., predicting bottomhole pressure and optimizing the output of the surface power unit 360) such that the jet pump 350 continues to operate effectively over time, even when the operating conditions of the unit 300 change. The analysis and solutions typically provide information such as head pressure, bottomhole pressure, intake pressure, power fluid flow rate, produced fluid flow rate, hydraulic horsepower to be used, etc. Since knowledge of cavitation when operating the jet pump 350 is important, the controller 400 also calculates and displays the cavitation limit of the unit (300) based on real-time information.

[0152] In this way, the controller 400 together with the disclosed control device 60 can optimize the operating life of the jet pump 350 by preventing the jet pump 350 from entering cavitation. The controller 400 can also track the decline trend of the well and predict when the jet pump 350 will enter cavitation. Thus, generally speaking, the controller 40 can track trends and predict the decline of the well at the well site of at least one artificial lift unit, which results in harmful operation of at least one artificial lift unit. These and several other functions can be handled by the controller 400, as discussed below. Although not discussed in detail here, it should be understood that the controller 400 can also be configured to operate and control the regulation of the power fluid by adjusting the unit 370.

[0153] The control system 50 having the control device 60 uses, for example, the techniques discussed in the pending U.S. application Ser. No. 16 / 363,592, filed Mar. 25, 2019 Figures 3 to 7 to monitor and control the hydraulic jet pump unit (300), the entire content of which is incorporated herein by reference.

[0154] In addition to the examples disclosed above, the control system 50 of the present disclosure can be used with a gas injection unit. For example, Figure 14 an automated control process (500) of the control system (50) is shown in controlling the gas injection rate of the gas injection unit by automated control from the control device (60) of the present disclosure.

[0155] In process (500), as long as the analysis is not the first time (502), the actual and inferred injection rates (T - today) (504) and the actual injection depth (T) (506) can be obtained. Decision (508) determines whether the actual injection depth (T) is not equal to the optimized injection depth (Y - yesterday). If so, process (500) determines that the actual injection depth is not equal to the optimized injection depth and triggers an alarm (509). Further analysis (524) is discussed further below. This further analysis can be compared with the initial analysis provided by process (500), or when there are differences in the injection rates.

[0156] If at decision (508), process (500) determines that the actual injection depth (T) does equal the optimized injection depth (Y), then process (500) moves to the decision (510) of whether the actual injection rate (T) is not empty. If the actual injection rate (T) is empty (no at the decision), then a decision (518) is made that the daily average gas injection rate QGI(T) is not equal to the optimized gas injection rate QGI(Y), which is discussed below.

[0157] If the actual injection rate (T) is not empty (yes at the decision), then process (500) calculates the difference (512) between the actual injection rate (T) and the inferred injection rate (T). If the difference is greater than the user - configurable maximum value (514), then the well needs adjustment and an alarm (516) is triggered. If the difference is not greater than the user - configurable maximum value, then a decision (518) is made that the daily average gas injection rate QGI)(T) is not equal to the optimized gas injection rate QGI(Y). If so, the optimized gas injection rate cannot be set and an alarm (520) is triggered. If the daily average gas injection rate QGI(T) equals the optimized gas injection rate QGI(Y), then a decision (522) is made as to whether the daily average tubing head pressure THP(T) equals the daily average tubing head pressure THP(Y). If so, process (500) exists. If not, then process (500) generates a performance curve for the daily average tubing head pressure THP(524) and finds the optimal gas injection rate QGI(526). For example, process (500) can use a quadratic fit to find the gas injection rate QGI that maximizes production.

[0158] In process (500), a decision (528) is made that the optimal gas injection rate QGI is greater than the allowed maximum gas injection rate. If so, the gas injection rate is set to the maximum gas injection rate QGI and an alarm (530) is triggered. The maximum gas injection rate QGI can be set by the user in the toolbox of the control application of the present invention.

[0159] Otherwise, if the optimal gas injection rate QGI is not greater than the allowable maximum gas injection rate, set the gas injection rate (532) of the gas injection unit, and the optimized gas injection rate, together with the rate and depth, is stored in the daily average table (534) stored for the gas lift unit.

[0160] Figure 15 The control device 60 is shown in a configuration for proxying communications for the disclosed system. As previously discussed and shown again, the control device 60 has a first communication interface 62a with an installed or existing communication system 73. For example, the first communication interface 62a can be a serial / RS232 port connected to an installed or existing serial radio system 73 at the well site. The control device 60 also has a second communication interface 62a' with installed or existing devices 70, 72 at the well site. For example, the second communication interface 62a' can be a serial / RS232 port connected to an installed or existing local controller or remote terminal unit 70, 72 at the well site.

[0161] The control device 60 includes a communication agent 610 that interfaces between the existing communication system 73 and the data collection engine 600 of the control device 60. The data collection engine 600 collects data and communications from other data sources and communication systems, such as the other network configurations disclosed herein. The data collection engine 600 includes the elements discussed above, such as the Figure 3 SCADA module 230, polling 232, etc. with respect to. These other data sources and communication systems may be capable of having a faster data rate and bandwidth than the existing / installed communication system 73. The communication agent 610 proxies the communication data to the local controller / remote terminal unit 70, 72 to ensure that only a single entity communicates with the local controller / remote terminal unit 70, 72 at a given point in time. Priority is given to the existing / installed communication channels of the system 73 and the interface 62a.

[0162] As disclosed herein, one of the benefits of the control device 60 is that it can retrofit an existing wellsite with legacy, existing, or installed hardware without substantial changes to its current communication infrastructure. To achieve this, the communication agent 610 enables the control device 60 to act as an agent or proxy for the existing communication. The agent 610 manages communication from multiple sources by internally switching and prioritizing requests originating from the legacy polling infrastructure. This switching and prioritization requires analyzing data from the requesters. When the protocols used by the legacy system and the internal polling system are known, the agent 610 performs protocol-level packet analysis to route the traffic to the correct destination. This routing occurs when a response is received from the existing RTUs / controllers 70, 72, a request is received from the existing polling / serial communication channels 73, 62a, or the internal polling infrastructure 600 of the control device requests data from the RTUs / controllers 70, 72. As will be appreciated, logical requests to the RTUs / controllers 70, 72 can span multiple data packets.

[0163] The agent for the service allows the usually slower original polling infrastructure to poll the RTUs / controllers 70, 72 at the same rate without interruption. At the same time, the data collection engine 600 of the control device 60 can poll the RTUs / controllers 70, 72 at high speed during times when the legacy polling infrastructure is not communicating with the RTUs / controllers 70, 72.

[0164] Figure 16 Shown is Figure 15 the proxy process 650 handled by the communication agent 610 of the control device 60. At the start of the repeated processing during operation, the agent 610 monitors whether the control device 60 is communicating with the local controllers 70, 72 (decision 652). If the control device 60 is communicating with the local controller 70 (Yes - decision 652), then the agent 610 processes the input / output data of the control device 60 (block 654). When the agent 610 processes the data, the agent 610 monitors whether the existing / installed communication system 73 is communicating with the controller 70 (decision 656). If not (No - decision 656), then the agent 610 can send the communication of the control device to the controller 70 (block 660) and process the input / output data from the control device 60 to the controller 70 (block 662).

[0165] When the agent 610 monitors (decision 656), it can determine that the existing / installed communication system 73 is communicating with the controller 70 (Yes - decision 656). In this case, the agent 610 waits for the communication to complete (block 658), and then processes the input / output data from the control device 60 to the controller 70 (blocks 660, 662).

[0166] When the agent 610 monitors, it can determine that the control device 60 is not communicating with the local controllers 70, 72 (No - decision 652). At this time, the agent 610 processes the input / output data of the communication system 73 (block 670). When the agent 610 processes the data, the agent 610 monitors whether the existing / installed communication system 73 is communicating with the controller 70 (decision 672). If the data is for some other entity (No - decision 672), the agent 610 discards the data from its buffer to allow other elements of the control device 60 to handle the routing and processing of the data. If the data is addressed to the controller 70 (Yes - decision 672), the agent 610 monitors whether the control device is communicating with the controller 70 (decision 674). If not, the agent 60 sends the communication to the controller 70 (block 660) and processes the input / output data to the controller 70 (block 662).

[0167] If the control device 60 is communicating with the controller 70 (Yes - decision 674), the agent 610 waits for the communication to complete (block 658), and then processes the input / output data to the controller 70 (blocks 660, 662).

[0168] The foregoing description of the preferred and other embodiments is not intended to limit or circumscribe the scope or applicability of the inventive concept conceived by the applicant. Benefiting from the present disclosure, it will be understood that the above features according to any embodiment or aspect of the disclosed subject matter can be used, either alone or in combination with any other described features, in any other embodiment or aspect of the disclosed subject matter.

[0169] In exchange for disclosing the inventive concept contained herein, the applicant desires all the patent rights provided by the appended claims. Accordingly, the appended claims are intended to cover all modifications and variations so that they fall fully within the scope of the appended claims or their equivalents.

Claims

1. A method of controlling multiple artificial lift units at multiple well sites, the artificial lift units having jet pumps operated by surface power units, the artificial lift units having installed controllers, installed sensing devices, and installed communication systems, the method comprising: docking a distributed processing device with the installed controllers and installed communication systems at the multiple well sites; connecting the distributed processing devices together in one or more networks; obtaining, at the distributed processing device, in real time the operating parameters of each of the artificial lift units from the installed sensing devices at the well sites; analyzing trends in the operating parameters of the artificial lift units by tracking production declines of the jet pumps of the artificial lift units at the well sites using the modeling capabilities of the distributed processing device; predicting the condition of the artificial lift units based on the analyzed trends by predicting cavitation of the jet pumps using automated machine learning of the distributed processing device based on the tracked declines; determining automated control for a determined condition of at least one artificial lift unit by determining an output of the surface power unit of the jet pump configured to mitigate the predicted cavitation of the jet pump using the processing device; and responding to the determined condition by configuring instructions to effect the automated control and transmitting the configured instructions from the distributed processing device to the installed controllers.

2. The method according to claim 1, wherein docking the distributed processing device includes installing a plurality of control devices in the one or more networks, each of the control devices having at least one first interface for network communication with the one or more networks and having at least one second interface for local communication with at least one of the installed communication systems.

3. The method according to claim 2, the artificial lift units including two or more types of artificial lift units, each of the two or more types of artificial lift units having an installed controller of a given type, wherein docking the distributed processing device includes: docking a given one of the control devices with one or more of the two or more types of artificial lift units; or docking a given one of the control devices with a given type of artificial lift unit of the two or more types of artificial lift units.

4. The method according to claim 1, wherein obtaining, at the distributed processing device, in real time the operating parameters of each of the artificial lift units from the sensing devices at the well sites includes: transmitting the operating parameters of each of the artificial lift units using a combination of the one or more networks and the installed communication systems.

5. The method according to claim 1, further comprising proxying communication to and from the installed controllers between the processing device and the installed communication systems using the distributed processing device.

6. The method according to claim 5, wherein Proxying the communication includes: making the first communication for the installed communication system take precedence over the second communication for the one or more networks.

7. The method according to claim 1, wherein analyzing the trend of the operating parameters of the artificial lift unit using the modeling function of the processing device includes one of the following: analyzing using a physics-based model based on the information of the well site and the artificial lift unit, analyzing using a model created on-site at the well site, and analyzing an engineering model configured as a digital representation of the well site and the artificial lift unit.

8. The method according to claim 1, wherein analyzing the trend of the operating parameters of the artificial lift unit using the modeling function of the processing device includes: establishing a data pipeline for batch jobs by using a workflow management engine.

9. The method according to claim 1, wherein predicting the condition of at least one artificial lift unit in the artificial lift unit based on the analyzed trend using the automated machine learning of the processing device includes: predicting at least one of the equipment failure of the at least one artificial lift unit and the failure of the well at the well site of the at least one artificial lift unit; predicting the inefficiency of the at least one artificial lift unit; and predicting the decline of the well at the well site of the at least one artificial lift unit that causes harmful operation of the at least one artificial lift unit.

10. The method according to claim 1, wherein determining at least one automated control for the determined condition of at least one artificial lift unit using the processing device includes: determining at least one temporary automated control configured to offset the determined condition as a remedial correction at least until a manual correction is performed.

11. The method according to claim 1 further includes implementing the automated control at the artificial lift unit based on the configured instructions sent from the distributed processing device to the installed controller.

12. A method for controlling multiple artificial lift units at multiple well sites, the artificial lift units having reciprocating rod lift units, the artificial lift units having installed controllers, installed sensing devices, and installed communication systems, the method includes: docking a distributed processing device with the installed controllers and installed communication systems at the multiple well sites; connecting the distributed processing devices together in one or more networks; obtaining in real time at the distributed processing device the operating parameters of each of the artificial lift units from the installed sensing devices at the well sites; using the modeling function of the distributed processing device to analyze the trend of the operating parameters of the artificial lift units by monitoring the balance of the reciprocating rod lift units of the artificial lift units; wherein predicting the condition of the artificial lift unit based on the analyzed trend using the automated machine learning of the distributed processing device by predicting the imbalance condition of the reciprocating rod lift unit based on the monitored balance. Using the processing device, automated control is determined for a determined condition of at least one artificial lift unit by determining an adjustment to the rod lift unit to counteract the imbalance condition. And The determined condition is addressed by configuring instructions to implement the automated control and transmitting the configured instructions from the distributed processing device to the installed controller.

13. The method according to claim 12, wherein, Implementing at least one automated control at the at least one artificial lift unit includes one of the following: automatically adjusting a motor, automatically adjusting a movable counterweight, and dispatching a mobile terminal to the well site.

14. The method according to claim 12, wherein, Analyzing trends of operating parameters of the artificial lift unit using the modeling function of the processing device includes one of the following: analyzing using a physics-based model based on information of the well site and the artificial lift unit, analyzing using a model created on-site at the well site, and analyzing an engineering model configured as a digital representation of the well site and the artificial lift unit.

15. The method according to claim 12, wherein, Analyzing trends of operating parameters of the artificial lift unit using the modeling function of the processing device includes: establishing a data pipeline for batch jobs by using a workflow management engine.

16. The method according to claim 12, wherein, Predicting the condition of at least one artificial lift unit in the artificial lift unit using the automated machine learning of the processing device based on the analyzed trends includes: predicting equipment failure of the at least one artificial lift unit, the condition of at least one of failures of wells at the well site of the at least one artificial lift unit; predicting inefficiency of the at least one artificial lift unit; and predicting a decline of the well at the well site of the at least one artificial lift unit that causes harmful operation of the at least one artificial lift unit.

17. The method according to claim 12, wherein, Determining at least one automated control for a determined condition of at least one artificial lift unit using the processing device includes: determining a temporary automated control configured to counteract the determined condition in the at least one automated control as at least a remedial correction until a manual correction is performed.

18. The method according to claim 12, further comprising implementing the automated control at the artificial lift unit based on the configured instructions sent from the distributed processing device to the installed controller.

19. The method according to claim 12, wherein, Docking the distributed processing device includes installing a plurality of control devices in the one or more networks, each of the control devices having at least one first interface for network communication with the one or more networks and having at least one second interface for local communication with at least one of the installed communication systems.

20. The method according to claim 19, wherein the artificial lift unit comprises two or more types of artificial lift units, and each of the two or more types of artificial lift units has an installed controller of a given type. Wherein, Docking the distributed processing device includes: docking a given one of the control devices with one or more of the two or more types of artificial lift units; or docking a given one of the control devices with the artificial lift units of a given type among the two or more types of artificial lift units.

21. The method according to claim 12. Wherein, Obtaining in real time at the distributed processing device the operating parameters of each of the artificial lift units from the sensing devices at the well site includes: transmitting the operating parameters of each of the artificial lift units using a combination of the one or more networks and the installed communication system.

22. The method according to claim 12, further comprising proxying communications to and from the installed controllers between the processing device and the installed communication system using the distributed processing device.

23. The method according to claim 22. Wherein, Proxying the communications includes: prioritizing a first communication for the installed communication system over a second communication for the one or more networks.

24. A programmable storage device storing program instructions for multiple artificial lift units at multiple well sites, the artificial lift units having installed controllers, installed sensing devices, and installed communication systems, the program instructions for causing a distributed processing device to perform the method according to claim 1 or 12.

25. A system for controlling multiple artificial lift units at multiple well sites, the artificial lift units having installed controllers, installed sensing devices, and installed communication systems, the system comprises: A communication device having a network interface for communicating with one or more networks and a local interface for communicating with the installed communication system; And A distributed processing device communicating with the communication device, the distributed processing device being installed at the multiple well sites for the artificial lift units, the distributed processing device being configured to perform the method according to claim 1 or 12.

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