US20240068324A1

US20240068324A1 - Controlling production efficiency of intelligent oil fields

Info

Publication number: US20240068324A1
Application number: US17/823,434
Authority: US
Inventors: Abduljabbar S. AL- MOHSEN; Hussain M. AL-GHAMDI; Mohammed A. AL-HURAIFI
Original assignee: Saudi Arabian Oil Co
Current assignee: Saudi Arabian Oil Co
Priority date: 2022-08-30
Filing date: 2022-08-30
Publication date: 2024-02-29

Abstract

The present disclosure generally relates to optimizing the efficiency of one or more intelligent oil fields by controlling one or more variable choke valves of hydrocarbon wells. For example, one or more embodiments described herein can relate to a method that includes monitoring production data that characterizes operation of a well extracting production fluid from a hydrocarbon reservoir. The method can also comprise generating a steady-state multi-phase flow model based on the production data. Further, the method can comprise controlling a variable choke valve of the well to adjust a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy data regarding the hydrocarbon reservoir.

Description

FIELD OF THE DISCLOSURE

The present disclosure relates generally to controlling the production efficiency of one or more intelligent oil fields (“i-fields”) and, more particularly, to controlling choke valve openings of one or more wellheads to comply with the reservoir production strategy for a given i-field.

BACKGROUND OF THE DISCLOSURE

I-fields are oil fields comprising one or more hydrocarbon wells, with each well equipped with multiple sensors to monitor production efficiency. The wells can include a wellbore drilled into the earth to access a subsurface formation, which can be a reservoir of hydrocarbons. For instance, the wellbore can be utilized to inject substances into the reservoir and/or extract hydrocarbons (e.g., oil and/or gas) from the reservoir.
During a production stage, the wells can each include a wellhead (e.g., a production tree), comprising a plurality of valves, such as motorized choke valves, for regulating the flowrate and/or pressure of various fluids traversing the wellbore (e.g., for regulating production flowrate of extracted hydrocarbons). Additionally, multiple wellheads can be positioned within an i-field to manage the production of hydrocarbons. Further, the wellheads can be connected to one or more downstream facilities to process the raw hydrocarbons extracted from the well. Traditionally, wellheads are manually operated and/or adjusted in accordance with a defined production strategy. Also, the wellheads are typically operated in isolation of each other, based on the specific characteristics of each respective well.

SUMMARY OF THE DISCLOSURE

Various details of the present disclosure are hereinafter summarized to provide a basic understanding. This summary is not an extensive overview of the disclosure and is neither intended to identify certain elements of the disclosure, nor to delineate the scope thereof. Rather, the primary purpose of this summary is to present some concepts of the disclosure in a simplified form prior to the more detailed description that is presented hereinafter.
According to an embodiment consistent with the present disclosure, a method is provided. The method can comprise monitoring production data that characterizes operation of a well extracting production fluid from a hydrocarbon reservoir. The method can also comprise generating a steady-state multi-phase flow model based on the production data. Further, the method can comprise controlling a variable choke valve of the well to modulate a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy data regarding the hydrocarbon reservoir.
In another embodiment, a system is provided. The system can comprise a memory to store computer executable instructions. The system can also comprise one or more processors, operatively coupled to the memory, that execute the machine executable instructions to implement a status checker configured to monitor production data that characterizes operation of a well extracting production fluid from a hydrocarbon reservoir. The one or more processors can also execute the computer executable instructions to implement a multi-phase flow simulator configured to generate a steady-state multi-phase flow model based on the production data. Additionally, the one or more processors can execute the computer executable instructions to implement a choke valve controller configured to control a variable choke valve of the well to modulate a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy data regarding the hydrocarbon reservoir.
In a further embodiment, a computer program product for controlling an intelligent oil field is provided. The computer program product can comprise a computer readable storage medium having computer executable instructions embodied therewith. The computer executable instructions can be executable by one or more processors to cause the one or more processors to monitor production data that characterizes operation of a well extracting production fluid from a hydrocarbon reservoir. The computer executable instructions can also cause the one or more processors to generate a steady-state multi-phase flow model based on the production data. Additionally, the computer executable instructions can cause the one or more processors to control a variable choke valve of the well to modulate a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy data regarding the hydrocarbon reservoir.
Any combinations of the various embodiments and implementations disclosed herein can be used in a further embodiment, consistent with the disclosure. These and other aspects and features can be appreciated from the following description of certain embodiments presented herein in accordance with the disclosure and the accompanying drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a non-limiting example system that can control the production efficiency of an i-field by adjusting variable choke valves of under-performing hydrocarbon wells in accordance with one or more embodiments described herein.

FIG. 2 is a block diagram of a non-limiting example i-field that can be controlled by one or more systems via adjustments to the variable choke valves of one or more wells to modulate the flowrate of production fluids based on a reservoir production strategy in accordance with one or more embodiments described herein.

FIG. 3 illustrates a flow diagram of a non-limiting example method that can be implemented by one or more systems to control the production efficiency of an i-field by adjusting variable choke valves of under-performing hydrocarbon wells in accordance with one or more embodiments described herein.

FIG. 4 illustrates a flow diagram of a non-limiting example method that can incrementally adjust the settings of one or more variable choke valves of wells in an i-field to comply with a target production rate in accordance with one or more embodiments described herein.

FIG. 5 illustrates a block diagram of non-limiting example computer environment that can be implemented within one or more systems described herein.

DETAILED DESCRIPTION

Embodiments of the present disclosure will now be described in detail with reference to the accompanying Figures. Like elements in the various figures may be denoted by like reference numerals for consistency. Further, in the following detailed description of embodiments of the present disclosure, numerous specific details are set forth in order to provide a more thorough understanding of the claimed subject matter. However, it will be apparent to one of ordinary skill in the art that the embodiments disclosed herein may be practiced without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the description. Additionally, it will be apparent to one of ordinary skill in the art that the scale of the elements presented in the accompanying Figures may vary without departing from the scope of the present disclosure.
As used herein, the term “coupled” or “coupled to” or “connected” or “connected to” or “attached” or “attached to” may indicate establishing either a direct or indirect connection, and is not limited to either unless expressly referenced as such. Wherever possible, like or identical reference numerals are used in the figures to identify common or the same elements. The figures are not necessarily to scale and certain features and certain views of the figures may be shown exaggerated in scale for purposes of clarification.
Embodiments in accordance with the present disclosure generally relate to controlling the production efficiency of an oil field (e.g., of an i-field) by operating the choke valves of one or more wellheads to comply with a reservoir production strategy. For example, one or more embodiments described herein can employ a control scheme that compares the monthly production target of each well with one or more observed production parameters to determine whether a well is compliant with the reservoir production strategy. Non-compliant wells can be improved by adjusting the wellhead's choke valve to a setting that results in production parameters equivalent to, or closer to, the target production defined by the reservoir production strategy. Additionally, various embodiments described herein can employ one or more steady-state multi-phase flow simulators to: determine whether the underperforming well is capable of meeting the target production; and/or estimate one or more choke valve adjustments. Thereby, one or more embodiments described herein can optimize the production efficiency of an i-field via automated adjustments to variable choke values of one or more wellheads based on: measured well performance parameters (e.g., production data), a reservoir production strategy (e.g., which can define target production values per well), and/or one or more steady-state multi-phase flow models. Further, the embodiments described herein can continuously monitor the i-field and utilize the steady-state multi-phase flow models to identify and/or troubleshoot non-compliant wells (e.g., including the generation of alerts and/or notifications regarding the non-compliant wells).
Moreover, various embodiments described herein can constitute one or more technical improvements over conventional reservoir management schemes by optimizing field operation from a network perspective rather than a mere rule-based approach from the individual well perspective. For instance, various embodiments described herein can autonomously control the production (e.g., flow rate) of individual wells based on the reservoir production strategy for the oil field as a whole. Additionally, one or more embodiments described herein can have a practical application by employing steady-state multi-phase flow simulators to evaluate the capacities of the wells and improve operations of non-compliant wells (e.g., wells operating outside of an optimal production rate range). For example, one or more embodiments described herein can control a variable choke valve of a given well based on one or more steady-state multi-phase flow models characterizing the fluid dynamics associated with the well's configuration and/or environment.
FIG. 1 illustrates a diagram of a non-limiting example i-field 100 that can be controlled by a system 101 in accordance with one or more embodiments described herein. As shown in FIG. 1 , the example i-field 100 can comprise a plurality of wells 102 a-102 h (collectively, 102). Although FIG. 1 depicts the example i-field 100 comprising eight example wells 102, the architecture of the system 101 is not so limited. For example, embodiments in which the i-field 100 controlled by the system 101 comprises fewer or more than eight wells 102 are also envisaged. In one or more embodiments, the wells 102 can access a common hydrocarbon reservoir. Alternatively, the wells 102 can access multiple hydrocarbon reservoirs. Additionally, the wells 102 can be coupled to a distribution network comprising, for example, a plurality of pipelines 104 to carry production fluids from the wells to one or more processing plants, such as a gas oil separation plant (“GOSP”) 106. For example, the wells 102 can deliver fluids to one or more GOSP 106, which can separate the fluids into constituent vapor and/or liquid components. For example, the one or more GOSPs 106 can separate production gas from one or more liquids containing a production fluid. Further, the one or more GOSPs 106 can separate production fluid from the one or more liquid components (e.g., can separate oil from water within the fluids). In one or more embodiments, one or more remote terminal units 108 can be positioned in the one or more GOSPs 106 (e.g., as shown in FIG. 1 ); however, the architecture of the system 101 is not so limited. For example, embodiments in which the one or more remote terminal units 108 are positioned in alternative processing facilities (not shown) are also envisaged.
In various embodiments, each of the example wells 102 can comprise a well sensor system 110 (e.g., well sensor systems 110 a-h) and a variable choke valve 112 (e.g., variable choke valves 112 a-h). For example, one or more of the example wells 102 can be equipped with one or more variable choke valves 112 (e.g., comprised within one or more wellhead structures, such as a production tree) having multiple possible choke positions associated with a fully-open state, a partially-open state, and/or a closed state. When operating in the fully-open state, the variable choke valve 112 can enable a maximum amount of fluid (e.g., production fluid) to flow through the valve with minimal inhibition. When operating in the closed state, the variable choke valve 112 can block the flow of fluid through the valve. When operating in the partially-open state, the variable choke valve 112 can enable a less than maximum amount of fluid to flow through the valve. For instance, fluid flow through the valve can be partially blocked in the partially-open state. Further, various choke positions can be associated with the partially-open position, with each choke position associated with a respective amount of fluid flow through the valve (e.g., each choke position can be associated with a respective amount of fluid blockage by the choke valve).
For example, the one or more variable choke valves 112 controlled by the system 101 can have eleven choke positions, ranging from 0-10. Choke position 0 can be associated with 0% of the variable choke valve's 112 fluid passage being open (e.g., a closed state), and choke position 10 can be associated with 100% of the variable choke valve's 112 fluid passage being open (e.g., a fully-open state). Each choke position 1-9 can be associated with sequentially increasing percentages of the variable choke valve's 112 fluid passage being open (e.g., enabling sequentially increasing amounts of fluid flow through the valve). In various embodiments, the one or more variable choke valves 112 can have more than eleven choke positions. For example, the one or more variable choke valves 112 can have choke positions associated with less than 10% increments of fluid passage opening (e.g., 5%, 4%, 3%, 2%, and/or 1% increments).
Optionally, each of the example wells 102 can comprise a choke valve controller 120 (e.g., example choke valve controllers 120 a-h). Alternatively, a choke valve controller 120 can be comprised within the one or more remote terminal units 108 and can control multiple variable choke valves 112. In one or more embodiments, the well sensor system 110, variable choke valve 112, and/or choke valve controller 120 can be comprised within one or more wellheads (e.g., production trees).
FIG. 2 illustrates a diagram of a non-limiting example of the system 101 that can comprise the one or more remote terminal units 108 for controlling the one or more variable choke valves 112 of an i-field's 100 wells 102 to meet one or more production targets of a reservoir production strategy. In various embodiments, the one or more remote terminal units 108 (e.g., a server, a desktop computer, a laptop, a hand-held computer, a programmable apparatus, a minicomputer, a mainframe computer, an Internet of things (“IoT”) device, and/or the like) can be operably coupled to (e.g., communicate with) the one or more well sensor systems 110 via one or more networks 206. In some embodiments, the one or more remote terminal units 108 can be a supervisory control and data acquisition (“SCADA”) computer system.
As shown in FIG. 2 , the one or more remote terminal units 108 can comprise one or more processing units 208 and/or computer readable storage media 210. In various embodiments, the computer readable storage media 210 can store one or more computer executable instructions 214 that can be executed by the one or more processing units 208 to perform one or more defined functions. In various embodiments, a status checker 216, multiphase flow simulator 218, and/or the choke valve controller 120 can be computer executable instructions 214 and/or can be hardware components operably coupled to the one or more processing units 208. For instance, in some embodiments, the one or more processing units 208 can execute the status checker 216, multiphase flow simulator 218, and/or choke valve controller 120 to perform various functions described herein (e.g., such as evaluating production data 222, estimating the effects of choke valve settings, and/or controlling one or more variable choke valves 112). Additionally, the computer readable storage media 210 can store production data 222, reservoir production strategy 224, and/or steady-state multi-phase flow models 226.
The one or more processing units 208 can comprise any commercially available processor. For example, the one or more processing units 208 can be a general purpose processor, an application-specific system processor (“ASSIP”), an application-specific instruction set processor (“ASIPs”), or a multiprocessor. For instance, the one or more processing units 208 can comprise a microcontroller, microprocessor, a central processing unit, and/or an embedded processor. In one or more embodiments, the one or more processing units 208 can include electronic circuitry, such as: programmable logic circuitry, field-programmable gate arrays (“FPGA”), programmable logic arrays (“PLA”), an integrated circuit (“IC”), and/or the like.
The one or more computer readable storage media 210 can include, but are not limited to: an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, a combination thereof, and/or the like. For example, the one or more computer readable storage media 210 can comprise: a portable computer diskette, a hard disk, a random access memory (“RAM”) unit, a read-only memory (“ROM”) unit, an erasable programmable read-only memory (“EPROM”) unit, a CD-ROM, a DVD, Blu-ray disc, a memory stick, a combination thereof, and/or the like. The computer readable storage media 210 can employ transitory or non-transitory signals. In one or more embodiments, the computer readable storage media 210 can be tangible and/or non-transitory. In various embodiments, the one or more computer readable storage media 210 can store the one or more computer executable instructions 214 and/or one or more other software applications, such as: a basic input/output system (“BIOS”), an operating system, program modules, executable packages of software, and/or the like.
The one or more computer executable instructions 214 can be program instructions for carrying out one or more operations described herein. For example, the one or more computer executable instructions 214 can be, but are not limited to: assembler instructions, instruction-set architecture (“ISA”) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data, source code, object code, a combination thereof, and/or the like. For instance, the one or more computer executable instructions 214 can be written in one or more procedural programming languages. Although FIG. 2 depicts the computer executable instructions 214 stored on computer readable storage media 210, the architecture of the system 101 is not so limited. For example, the one or more computer executable instructions 214 can be embedded in the one or more processing units 208.
The one or more networks 206 can comprise one or more wired and/or wireless networks, including, but not limited to: a cellular network, a wide area network (“WAN”), a local area network (“LAN”), a combination thereof, and/or the like. One or more wireless technologies that can be comprised within the one or more networks 206 can include, but are not limited to: wireless fidelity (“Wi-Fi”), a WiMAX network, a wireless LAN (“WLAN”) network, BLUETOOTH® technology, a combination thereof, and/or the like. For instance, the one or more networks 206 can include the Internet and/or the IoT. In various embodiments, the one or more networks 206 can comprise one or more transmission lines (e.g., copper, optical, or wireless transmission lines), routers, gateway computers, and/or servers. Further, the one or more remote terminal units 108 and/or well sensor systems 110 can comprise one or more network adapters and/or interfaces (not shown) to facilitate communications via the one or more networks 206.
In various embodiments, the one or more well sensor systems 110 can be positioned at, and/or comprised within, one or more wellheads of the given i-field 100. As shown in FIG. 2 , the well sensor systems 110 can include various sensors; such as, but not limited to, one or more: flowrate sensors 227, pressure sensors 228, temperature sensors 230, water cut sensors 232, gas-oil-ratio (“GOR”) sensors 234, a combination thereof, and/or the like. In one or more embodiments, a single tool of the well sensor system 110 can comprise multiple types of the sensors described herein. For instance, the well sensor system 110 can include a pressure, temperature, and spinner (“PTS”) tool to measure and/or collect production data 222 from a down-hole position in the one or more wells of the i-field 100.
In some embodiments, each well 102 of the i-field 100 can have an associated well sensor system 110 that can measure and/or collect production data 222 characterizing the well's 102 operation and/or operation of the i-field 100. For example, the production data 222 can include data measured and/or collected by the flowrate sensors 227, pressure sensors 228, temperature sensors 230, water cut sensors 232, and/or GOR sensors 234. For instance, the production data 222 can include flowrate data, pressure data, temperature data, water cut data, and/or GOR data. The well sensor systems 110 can share the production data 222 with the one or more remote terminal units 108 via the one or more networks 206. In some embodiments, the production data 222 can be stored in one or more computer readable storage media 210 of the remote terminal units 108 (e.g., as shown in FIG. 2 ). Alternatively, the production data 222 can be stored in one or more computer readable storage media 210 outside of the remote terminal units 108 and accessed by the remote terminal unit 108 via the one or more networks 206. For instance, the production data 222 can be stored in the one or more well sensor systems 110. In another instance, the production data 222 can be stored in one or more central databases (not shown) on the network 206, which is accessible to the one or more well sensor systems 110 and/or the one or more remote terminal units 108.
In some embodiments, the one or more well sensor systems 110 can generate timestamped data. As used herein, “timestamped” can refer to recording a set of time series measurements indicative of a time period associated with one or more data points. For example, data can be timestamped to indicate a start time, an end time, and/or a time increment associated with the measurement and/or collection of the data. For instance, timestamped data can include dates and/or times indicating the moment of data collection and/or measurement.
The one or more flowrate sensors 227 can measure the flowrate of fluid streams (e.g., comprising production fluids, such as oil and/or gas) in the wellbore of a given well 102 associated with the well sensor system 110. For example, the one or more flowrate sensors 227 can include a multi-phase flowmeter positioned within the wellbore and/or within the wellhead. In one or more embodiments, the one or more flowrate sensors 227 include surface multi-phase flowmeters located at the wellhead (e.g., within the production tree) that measure the flowrate of one or more fluids (e.g., production fluids) exiting the wellbore. In various embodiments, the flowrate measured by the one or more flowrate sensors 227 can characterize the production rate of the given well 102. Additionally, the well sensor system 110 can generate (e.g., via the one or more flowrate sensors 227) timestamped flowrate data characterizing the operating conditions of the given well.
The one or more pressure sensors 228 can measure the pressure of fluid streams (e.g., comprising production fluids, such as oil and/or gas) in the wellbore of a given well 102 associated with the well sensor system 110. Example types of pressure sensors 228 can include, but are not limited to: pressure transducers, pressure transmitters (e.g., intrinsically safe pressure transmitters, non-incentive pressure transmitters, explosion-proof pressure transmitters, and/or hammer union pressure transmitters), a combination thereof, and/or the like. For example, the one or more pressure sensors 228 can include a surface pressure sensor positioned at the wellhead (e.g., within the production tree) that measures the wellhead pressure (“WHP”) of the well 102. Additionally, the one or more pressure sensors 228 can include one or more down-hole pressure sensors positioned at a bottom portion of the wellbore to measure the bottom hole pressure (“BHP”) of the well 102. Further, the well sensor system 110 can generate (e.g., via the one or more pressure sensors 228) timestamped pressure data characterizing the operating conditions of a given well 102 (e.g., characterizing WHP and/or BHP).
The one or more temperature sensors 230 can measure the temperature of fluid streams (e.g., comprising production fluids, such as oil and/or gas) in the wellbore of a given well associated with the well sensor system 110. Example types of temperature sensors 230 can include, but are not limited to: thermocouples, resistance temperature detectors, thermistors, a combination thereof, and/or the like. For example, the one or more temperature sensors 230 can include a surface temperature sensor positioned at the wellhead (e.g., within the production tree) that measures the wellhead temperature (“WHT”) of the well 102. In one or more embodiments, the temperature data can be formatted as absolute temperature values, as gradient values, and/or as relative gradient values. Additionally, the one or more temperature sensors 230 can include one or more down-hole temperature sensors positioned at a bottom portion of the wellbore to measure the bottom hole temperature (“BHT”) of the well 102. In various embodiments, the temperature measured by the one or more temperature sensors 230 can characterize the well 102 temperature. Additionally, the well sensor system 110 can generate (e.g., via the one or more temperature sensors 230) timestamped temperature data characterizing the operating conditions of the given well 102 (e.g., characterizing WHT and/or BHT).
The one or more water cut sensors 232 can measure the water content of fluid streams (e.g., comprising production fluids, such as oil and/or gas) in the wellbore of a given well 102 associated with the well sensor system 110. Further, the well sensor systems 110 (e.g., via the one or more water cut sensors 232) can generate water cut data based on the measured water content, where the water cut of a well can be defined as the ratio of water volume in the fluid stream (e.g., in the production fluid) to total volume of the fluid stream. Thereby, the water cut data can be indicative of the amount of water in the production fluids extracted by the well 102. Additionally, the well sensor system 110 can generate (e.g., via the one or more water cut sensors 232) timestamped water cut data characterizing the operating conditions of an associate well 102.
The one or more GOR sensors 234 can measure the GOR of fluid streams (e.g., comprising production fluids, such as oil and/or gas) in the wellbore of a given well 102 associated with the well sensor system 110. The GOR can be defined as the ratio of the volume of gas to oil within the fluid stream (e.g., within the production fluid). Additionally, the well sensor system 110 can generate (e.g., via the one or more GOR sensors 234) timestamped GOR data characterizing the operating conditions of an associate well 102.
Additionally, while FIGS. 1-2 depict the one or more flowrate sensors 227, pressure sensors 228, temperature sensors 228, temperature sensors 230, water cut sensors 232, and/or GOR sensors 234 as exclusively comprised within the one or more well sensor systems 110 at the wells 102; the architecture of the system 101 is not so limited. For example, embodiments in which the one or more flowrate sensors 227, pressure sensors 228, temperature sensors 230, water cut sensors 232, and/or GOR sensors 234 are also located at one or more positions along the pipelines 104 of the i-field 100 are also envisaged. For example, one or more flowrate sensors 227, pressure sensors 228, and/or temperature sensors 230 can be positioned within the one or more pipelines 104 to collect flowrate data, pressure data, and/or temperature data of production fluids as the fluids are being distributed through the one or more pipelines 104. For instance, one or more flowrate sensors 227, pressure sensors 228, and/or temperature sensors 230 can be positioned in the one or more pipelines 104 between wells 102 of the i-field 100 and/or between one or more wells 102 and the GOSP 106. Thereby, the production data 122 can include data characterizing the operation of the one or more pipelines 104 in addition to the one or more wells 102.
In various embodiments, the status checker 216 can track the operating characteristics (e.g., indicated by the production data 222) of one or more wells 102 in the i-field 100 and determine the wells' 102 operating status. For example, the one or more well sensor systems 110 can share the production data 222 with the one or more remote terminal units 108 in real time, or near real time (e.g. less than a minute), during production of the hydrocarbons from the reservoir. Further, the status checker 216 can monitor the production data 222 in real time, or near real time, to determine the current operating status of the associate well 102. In one or more embodiments, the status checker 216 can determine a well's 102 operating status based on production data 222, a reservoir production strategy 224, and/or auxiliary data 225.
In accordance with various embodiments described herein, the production data 222 can include data measured and/or collected by the various sensors described herein (e.g., the well sensor systems 110). The reservoir production strategy 224 can include data that characterizes: one or more reservoirs, one or more i-fields 100 extracting hydrocarbons from the one or more reservoirs, and/or one or more wells 102 of the i-fields 100. For example, the reservoir production strategy 224 can include one or more reservoir models characterizing various parameters of a given reservoir. For instance, the reservoir production strategy 224 can include integrated reservoir modeling regarding, for example, the capacity, location, age, composition, rock structure (e.g., rock type, porosity, and/or volume), and/or size of a reservoir. In another example, the reservoir production strategy 224 can include data characterizing the infrastructure of one or more i-fields. For instance, the reservoir production strategy 224 can include, but is not limited to: the number of wells 102 in an i-field 100, the distribution network employed in an i-field 100, the number of well sensor systems 110 in an i-field 100, the position of wells 102 in an i-field 100, the location of water injection sites in an i-field 100, the location and/or connectivity of one or more processing plants in relation to an i-field 100, a combination thereof and/or the like. In a further instance, the reservoir production strategy 224 can characterize the one or more pipelines 104 of the i-field 100, including but not limited to: the layout of the pipelines 104, dimensions of the pipelines 104 (e.g., diameters, lengths, and/or fluid capacities of the pipelines 104), material composition of the pipelines 104, a combination thereof, and/or the like. In a further example, the reservoir production strategy 224 can include data characterizing the operating capacity and/or operating expectations associated with one or more wells 102 of an i-field 100. For instance, the reservoir production strategy 224 can include, but is not limited to: target production fluid flowrates per well 102, target pressures per well 102 (e.g., target WHP and/or BHP), target temperatures per well 102 (e.g., target WHTs and/or BHTs), target water cuts per well 102, and/or target GORs per well 102.
For example, in some embodiments the reservoir production strategy 224 can define one or more target production rates (e.g. a function of temperature and/or pressure data) per well 102 of an i-field 100 extracting hydrocarbons (e.g., oil and/or gas) from a given reservoir. In one or more embodiments, the target production rates can be defined based on one or more characteristics of the reservoir, such as the probable volume of production fluids in the reservoir, the number of wells 102 accessing the reservoir, and/or the geological composition of the reservoir. For instance, the target production rates can be manually defined and/or autonomously defined via one or more artificial neural network (“ANN”) models. In various embodiments, the reservoir production strategy 224 can include one or more tables, charts, and/or diagrams correlating the target parameters (e.g., target production rates) to specific wells 102 in the i-field 100.
In some embodiments, the auxiliary data 225 can include one or more maintenance schedules regarding the wells controlled by system 101. For example, the auxiliary data 225 can define periods of time in which one or more of the wells 102 are undergoing a scheduled maintenance operation. Additionally, the auxiliary data 225 can include one or more user preferences regarding, for example, how frequently the wells 102 are monitored by the one or more remote terminal units 108. In various embodiments, the production data 222, reservoir production strategy 224, and/or auxiliary data 225 can be stored on the one or more remote terminal units 108, or can be stored in one or more central databases accessible by the remote terminal units 108 via the one or more networks 206.
In various embodiments, the status checker 216 can determine an operating status of one or more wells controlled by the one or more remote terminal units 108. For example, the status checker 216 can determine whether a given well 102 is: under maintenance, inoperable; compliant with the reservoir production strategy 224; or actively performing as desired. In one or more embodiments, the status checker 216 can continuously monitor the production data 222 and/or continuously determine the operating status of the one or more wells 102. Alternatively, the status checker 216 can monitor the production data 222 and/or determine the operating status of the one or more wells 102 in accordance with a schedule defined by, for example, the auxiliary data 225.
In some embodiments, the status checker 216 can reference one or more maintenance schedules (e.g., included in the auxiliary data 225) to determine whether a well 102 is under maintenance. For example, the status checker 216 may reference the one or more maintenance schedules based on the production data 222 for the well 102 indicating a sudden and/or substantial decrease in production (e.g., a drop in the flowrate of production fluids and/or an increase in one or more pressure measurements). The status checker 216 can determine the status of a well 102 as “under maintenance” based on a maintenance procedure being scheduled for the given date and/or time associated with the deviations in production. Additionally, the remote terminal unit 108 can refrain from enacting one or more production improvement operations (e.g., refrain from adjusting variable choke valve 112 settings) until the given well 102 is no longer under maintenance.
In one or more embodiments, the status checker 116 can monitor the production data 222 associated with each well 102 of an i-field 100 to determine whether the respective wells 102 are operable. For example, the status checker 216 can determine that a given well 102 is operable based on one or more parameters of the production data 222 being within a defined operating range. For example, the reservoir production strategy 224 and/or the auxiliary data 225 can define one or more operating ranges with regards to one or more parameters included in the production data 222. Additionally, the operating ranges can be well-specific, depending on one or more characteristics of the well 102 (e.g., well 102 depth, wellhead equipment, and/or the like). For instance, the reservoir production strategy 224 and/or the auxiliary data 225 can define a minimum and maximum: flowrate, pressure, temperature, water cut and/or GOR. Where the production data 222 for a given well 102 comprises parameter values within the one or more operating ranges, the status checker 216 can determine that the well 102 is operable. Where the production data 222 for a given well 102 comprises parameter values outside the one or more operating ranges, the status checker 216 can determine that the well 102 is inoperable.
Additionally, in some embodiments, the status checker 216 can compare the production data 222 of operable wells 102 to one or more target production parameters (e.g., target production rates, as a function of flowrates and/or pressure) to determine whether the operable wells 102 are operating as desired. In various embodiments, the target production parameters can be an optimal threshold value or an optimal value range. In accordance with various embodiments described herein, the target production parameters can be defined, per well 102, in the reservoir production strategy 224.
For example, the status checker 216 can compare the production data 222 to a predefined optimal threshold. For instance, the status checker 216 can determine that a well 102 is non-compliant based on one or more of the production data 222 parameters (e.g., flowrate, pressure, temperature, water cut, and/or GOR) being less than the predefined optimal threshold or outside of a predefined optimal value range. Alternatively, the status checker 216 can determine that a well 102 is performing as desired based on one or more of the parameter values being greater than or equal to the predefined optimal threshold or within the predefined optimal value range. For instance, the status checker 216 can determine that an operable well 102 is non-compliant with the reservoir production strategy 224 based on the measured production fluid flowrate (e.g., included in the production data 222) being less than a target production rate threshold or outside of a target production rate range. Alternatively, the status checker 216 can determine that an operable well 102 is compliant with the reservoir production strategy 224 (e.g., performing as desired) based on the measured production fluid flowrate (e.g., included in the production data 222) being greater than or equal to the target production rate threshold and/or within the target production rate range.
In some embodiments, the status checker 216 can utilize timestamped data of the production data 222 to identify one or more operating trends of the one or more wells 102 controlled by the system 101. For example, the status checker 216 can identify periods of consecutive diminishment or increase in one or more parameter values defined by the production data 222. For instance, the status checker 216 can identify when the flowrate of well is consistently diminishing over a period of time. Additionally, the status checker 216 can generate one or more alerts and/or notifications regarding the one or more operating trends and/or the operating status of a well 102.
In various embodiments, the alerts and/or notifications generated by the one or more remote terminal units 108 (e.g., via the status checker 216) can be formatted as any suitable media, such as: text, audio, video, numbers, charts, diagrams, images, a combination thereof, and/or the like. In some embodiments, the alerts and/or notifications can be displayed to one or more system 101 users via one or more displays operably coupled to the one or more remote terminal units 108. In some embodiments, the one or more remote terminal units 108 can send the one or more alerts and/or notifications to one or more external devices (e.g., another computer and/or a mobile device, such as a smart phone and/or a computer tablet) via the one or more networks 206.
In some embodiments, the multi-phase flow simulator 218 can generate one or more steady-state multi-phase flow models 226 (e.g., utilized to model multi-phase flow, heat transfer, and/or fluid behavior) based on the production data 222 (e.g., which can characterize well 102 operation and/or pipeline operation 104) and/or the reservoir production strategy 224 (e.g., which can define one or more infrastructure characteristics of the i-field 100) for one or more under-performing wells 102. For example, the multi-phase flow simulator 218 can utilize computational fluid dynamics (“CFD”) to generate one or more steady-state multi-phase flow models 226 that simulate the simultaneous interaction of multiple phases of matter. For instance, the production fluid can be a multiphase flow of various components, such as solid particles, liquids (e.g., oil and/or water), and/or gases. In various embodiments, the multi-phase flow simulator 218 can generate steady-state multi-phase flow models 226 regarding a single type of multi-phase flow regime (e.g., a bubbly regime, plug regime, stratified regime, wavy regime, slug regime, or annular regime), or a combination of multi-phase flow regimes. Further, the multi-phase flow simulator 218 can utilize various modeling techniques, including, but not limited to: Eulerian multi-phase modeling, volume of fluid modeling, fluid film modeling, lagrangian multi-phase modeling, and/or discrete element method of modeling.
In some embodiments, the one or more steady-state multi-phase flow models 226 can utilize the CFD techniques to predict the operational capabilities of a given well 102 based on the production data 222 associated with the well 102 and/or features defined by the reservoir production strategy 224 and/or the auxiliary data 225. For instance, the reservoir production strategy 224 and/or the auxiliary data 225 can define equipment specifications utilized at each well 102 and/or pipeline 104 of the i-field 100. Example equipment specification can include, but are not limited to: dimensions of the wellbore, the type of wellhead employed, the type of variable choke valves 112 employed (e.g., including potential operating settings and/or rate capacities associated with each operating setting), layout of the pipelines 104, dimensions of the pipelines 104, a combination thereof, and/or the like.
Additionally, the one or more steady-state multi-phase flow models 226 can characterize relationships between flowrate, pressure, and temperature of a production fluid based on the composition of the fluid (e.g., water cut and/or GOR) and/or characteristics of the well. For instance, a wellhead can comprise one or more variable choke valves 112 in accordance with various embodiments described herein. The variable choke valve 112 can modulate the flowrate of the production fluids through the wellhead, and thereby the one or more pipelines 104, by defining the amount of open passageway through which the production fluid can travel. Further, the one or more steady-state multi-phase flow models 226 can define one or more correlations between the amount of available open passageway controlled by the one or more variable choke valves 112 and the flowrate of the production fluid. Thereby, the one or more steady-state multi-phase flow models 226 can be used to predict how adjustments to the variable choke valve 112 will affect production fluid flowrates within the i-field 100.
In one or more embodiments, the one or more the one or more steady-state multi-phase flow models 226 can model the production fluids of the i-field 100 as a function of the operations of multiple wells 102 and/or the reservoir production strategy 122. For example, the steady-state multi-phase flow model 226 can model individual well 102 characteristics, pipeline 104 characteristics, and/or fluid characteristics of production fluids traveling through the one or more wells 102 and/or pipelines 104. Thereby, the multi-phase flow simulator 218 can utilize the one or more steady-state multi-phase flow models 226 to simulate various parameters exhibited across the i-field 100 and/or components thereof; including, for example, overall flow, velocity, pressure, temperature, and/or composition of the production fluid through i-field 100. For instance, the one or more steady-state multi-phase flow models 226 can include (e.g., based on the production data 122 and/or reservoir production strategy 124): a well 102 model component (e.g., which can characterize well 102 completion and/or operating status, artificial lift equipment, and/or other well 102 components described herein); a fluid model component (e.g., which can characterize fluid behavior observed at respective wells 102, a group of wells 102, and/or the one or more pipelines 104); and/or a pipeline 104 model component (e.g., which can characterize one or more properties of the i-field's 100 pipelines 104).
In one or more embodiments, the choke valve controller 120 can control the one or more variable choke valves 112 of one or more of the wells 102 controlled by the system 101. For example, the one or more variable choke valves 112 can be operated at various choke positions (e.g., various choke settings and/or states) to regulate the flow of production fluids extracted from each well 102, where the choke valve controller 120 can adjust the employed choke position to control one or more parameter values of the production data 222 (e.g., such as flowrate and/or pressure). For instance, the choke valve controller 120 can generate one or more commands that control operation of a mechanical actuator that sets the choke position of a given variable choke valve 112.
In some embodiments, the one or more choke valve controllers 120 can be comprised within the one or more remote terminal units 108 and can control the one or more variable choke valves 112 via a remote connection (e.g., as shown in FIG. 1 ). For example, the one or more choke valve controllers 120 can generate one or more commands and/or operating instructions, which can be sent to the one or more variable choke valves 112 via the one or more networks 206. Alternatively, one or more of the choke valve controllers 120 can be positioned at the respective wells 102 within the i-field 100 (e.g., as shown in FIG. 1 ). For instance, the one or more choke valve controllers 120 can remotely communicate with the one or more remote terminal units 108 (e.g., via the one or more networks 206) and control the one or more variable choke valves 112 via a direct coupling.
In view of the foregoing structural and functional features described above, example methods will be better appreciated with reference to FIGS. 3-4 . While, for purposes of simplicity of explanation, the example methods of FIGS. 3-4 are shown and described as executing serially, it is to be understood and appreciated that the present examples are not limited by the illustrated order, as some actions could in other examples occur in different orders, multiple times and/or concurrently from that shown and described herein. Moreover, it is not necessary that all described actions be performed to implement the methods.
FIG. 3 illustrates a flow diagram of a non-limiting example method 300 that can be implemented by the system 101 in accordance with one or more embodiments described herein. In various embodiments, the system 101 (e.g., via the one or more remote terminal units 108) can perform one or more features of method 300 to monitor and/or control one or more wells 102 (e.g., as exemplified by example wells 102 a-h) of an i-field (e.g., as exemplified by example i-field 100).
At 302, the method 300 can comprise monitoring production data 222 characterizing a well's 102 operating performance. In accordance with various embodiments described herein, the production data 222 can be monitored by one or more remote terminal units 108 (e.g., via the status checker 216 and/or processing units 208). For example, the production data 222 can be measured and/or collected by one or more well sensor systems 110 associated with the well 102. The monitoring at 302 can be performed in real time, or near real time, or in accordance with one or more monitoring schedules (e.g., defined in the auxiliary data 225).
At 304, the method 300 can comprise determining an operating status of the well 102. In accordance with various embodiments described herein, the one or more remote terminal units 108 (e.g., via the status checker 216 and/or processing units 208) can determine the operating status based on the production data 222 monitored at 302. For example, the status checker 216 can reference one or more maintenance schedules (e.g., defined in the auxiliary data 225) to determine if the well 102 is under maintenance. In another example, the status checker 216 can compare the production data 222 monitored at 302 with one or more operating thresholds and/or ranges. For instance, the status checker 216 can compare the measured pressure data and/or temperature data of the well 102 to the one or more operating thresholds and/or ranges to determine the operating status of the well 102. Where the production data 222 fails to meet the operating threshold, or is outside the operating range, the status checker 216 can determine that the well 102 is inoperable and can generate one or more alerts and/or notifications describing the inoperability of the well 102. For instance, the one or more alerts and/or notifications can be shared with one or more users of the system 101 to prompt remediation of the well 102. Where the production data 222 meets the operating threshold, or is inside the operating range, the status checker 216 can determine that the well 102 is operational and can further evaluate the well's 102 operation.
At 306, the method 300 can comprise determining whether the operational well 102 is under-performing. In accordance with various embodiments described herein, the one or more remote terminal units 108 (e.g., via the status checker 216 and/or processing units 208) can compare the production data 222 to one or more target production values, which can be defined by the reservoir production strategy 224. For example, the reservoir production strategy 224 can define the one or more target production values as optimal thresholds and/or ranges for one or more parameters characterized by the production data 222 (e.g., such as flowrate, temperature, pressure, water cut, and/or GOR). For instance, the reservoir production strategy 224 can define a target production fluid flowrate for the well 102. In some embodiments, the status checker 216 can compare the measured flowrate data of the well 102 to the target production fluid flowrate, which can be defined via an optimal flowrate range. Where the measured flowrate data is outside the optimal flowrate range (e.g., the measured flowrate is less than the minimum optimal flowrate or greater than the maximum optimal flowrate), the status checker 216 can determine that the well 102 is non-compliant with the reservoir production strategy 224. Where the measured flowrate data is within the optimal flowrate range (e.g., the measured flowrate is greater than the minimum optimal flowrate and less than the maximum optimal flowrate), the status checker 216 can determine that the well 102 is compliant with the reservoir production strategy 224.
In accordance with various embodiments described herein, the reservoir production strategy 224 can define the target production rate per well 102 in accordance with a reservoir management scheme employed across the entire i-field 100. For example, the reservoir production strategy 224 can define target production rates per well 102 such that the production efficiency of the i-field (e.g., exemplified by i-field 100) is optimized. Additionally, the target production rates per well 102 can vary over time. For example, the target production rates can be re-evaluated in accordance with a defined schedule (e.g., re-evaluated monthly).
Where the well 102 is found to be compliant with the reservoir production strategy 224 (e.g., with the target production rate), the method 300 can proceed back to 302 and the well 102 can continue to be monitored. For example, where the well 102 is found to be compliant with the reservoir production strategy 224 (e.g., with the target production rate), the well 102 can be operating as desired and therefore does not need an operation adjustment. Where the well 102 is found to be non-compliant with the reservoir production strategy 224 (e.g., with the target production rate), the method 300 can proceed to 308. For example, where the well 102 is found to be non-compliant with the reservoir production strategy 224 (e.g., with the target production rate), the well 102 can be in need of an operation adjustment executed via subsequent features of the method 300.
At 308, the method 300 can comprise generating and/or updating one or more steady-state multi-phase flow models 226 for the well 102. In accordance with various embodiments described herein, the one or more remote terminal units 108 (e.g., via the multi-phase flow simulator 218 and/or processing units 208) can generate and/or maintain one or more steady-state multi-phase flow models 226 for each well 102 controlled by the system 101. For example, the multi-phase flow simulator 218 can generate a steady-state multi-phase flow model 226 based on the production data 222 (e.g., water cut data and/or GOR data) and/or equipment specifications (e.g., defined via the reservoir production strategy 224 and/or the auxiliary data 225) for the well 102. In another example, where the well 102 has been previously evaluated, the multi-phase flow simulator 218 can update an existing steady-state multi-phase flow model 226 based on the production data 222 monitored at 302. In various embodiments, the steady-state multi-phase flow model 226 can delineate production parameter values attainable by the well 102.
At 310, the method 300 can determine whether the one or more target production rates are attainable by the well based on the steady-state multi-phase flow model 226. For example, the multi-phase flow simulator 218 can compare the target production rate (e.g., defined via an optimal range) defined by the reservoir production strategy 224 to the maximum production rates estimated by the steady-state multi-phase flow model 226 for the given well 102 to facilitate the determination at 310. Where the estimated capability of the well 102 is unable to meet the target production rate, the method 300 can proceed to 312. At 312, the method 300 can comprise generating one or more alerts regarding the well's 102 operating conditions. For example, the one or more remote terminal units 108 can generate one or more alerts to proctor maintenance to the given well 102.
Where the well 102 is estimated to be able to meet the target production rate (e.g., where the estimated maximum production rate exceed the target production rate), the method 300 can proceed to 314. At 314, the method 300 can comprise adjusting the choke position (e.g., adjust open, partially open, or closed state of a fluid passage enabled by the variable choke valve 112, in accordance with various embodiments described herein) of the well's 202 variable choke valve 112 to meet the target production rate. In accordance with various embodiments described herein, the one or more remote terminal units 108 (e.g., via the choke valve controller 120 and/or processing units 208) can instruct one or more mechanical actuators to alter the choke position of the variable choke valve 112 to a higher or lower position so as to increase or decrease the flowrate of the well 102 and modulate one or more parameters of the production data 222. For example, the adjustment at 314 can reduce the flowrate of the well 102 by partially closing the variable choke valve 112 to meet a target production rate. In another example, the adjustment at 314 can increase the flowrate of the well 102 by partially opening the variable choke valve 112 to meet the target production rate. In accordance with one or more embodiments described herein, the choke position adjustments employed at 314 can be based on the one or more steady-state multi-phase flow models 226 generated and/or updated at 308. Following the choke position adjustment a 314, the method 300 can proceed to monitoring the production data 222 at 302.
FIG. 4 illustrates a flow diagram of a non-limiting example method 400 that can be implemented by the system 101 (e.g., via the one or more remote terminal units 108) to perform the one or more choke position adjustments at 314 of method 300 in accordance with one or more embodiments described herein. In various embodiments, the choke position of the one or more variable choke valves 112 can be incrementally adjusted and operation of the given well 102 can be re-evaluated.
For example, at 402 the method 400 can comprise adjusting the variable choke valve 112 of the given well 102 by a first increment of choke positions. In accordance with various embodiments described herein, the one or more remote terminal units 108 (e.g., via the choke valve controller 120 and/or processing units 208) can instruct one or more mechanical actuators to alter the choke position of the variable choke valve 112 by a defined increment (e.g., by a defined number of positions and/or by a defined percentage). For example, the choke valve controller 120 can define the increment in terms of a percentage of the fully-open state. For instance, the choke valve controller 120 can further open the variable choke valve 112 by 5%. In another instance, the choke valve controller 120 can further close the variable choke valve 112 by 5%. Additionally, the adjustment increment is not limited to 5%. For example, increments greater than 5% (e.g., 8%, 10% 15%, 20%, etc.) or less than 5% (e.g., 4%, 3%, 2%, or 1%) can be employed by the choke valve controller 120.
In one or more embodiments, the adjustment increment value employed by the choke valve controller 120 can be based on the difference between the production data 222 (e.g., the measured flowrate of the well 102) and the target production rate (e.g., defined by the reservoir production strategy 224 and/or analyzed at 306). For example, as the absolute value of the difference between the production data 222 and the target production rate increases, the absolute value of the first increment of adjustment can likewise increase. In one or more embodiments, the adjustment increment value employed by the choke valve controller 120 can be predefined (e.g., by the auxiliary data 225). For instance, the choke valve controller 120 can adjust the one or more variable choke valves 112 by a default increment in accordance with one or more user preferences.
At 404, the method 400 can comprise monitoring the production data 222 during an evaluation period. In accordance with various embodiments described herein, the production data 222 can be monitored by one or more remote terminal units 108 (e.g., via the status checker 216 and/or processing units 208) continuously over a defined period of time. For example, the status checker 216 can monitor the production data 222 of the well 102 operating with the adjusted choke position over an evaluation period, which can be defined by, for example, the auxiliary data 225. For instance, the evaluation period can extend for a defined amount of minutes, hours, days, weeks, or months. In one or more embodiments, the evaluation period can extend for six hours.
At the end of the evaluation period, the method 400 can proceed to 406; where the performance of the well 102 can be revaluated. At 406, the method 400 can comprise reassessing whether the well 102 is compliant with the reservoir production strategy 224 (e.g., with the target production rate). In accordance with various embodiments described herein, the one or more remote terminal units 108 (e.g., via the status checker 216 and/or processing units 208) can compare the production data 222 (e.g., flowrate data) resulting from operation of the adjusted variable choke valve 112 to one or more target production rates, which can be defined by the reservoir production strategy 224. For example, the target production rates can be defined via one or more optimal thresholds and/or optimal ranges. Where the adjusted well 102 is found to be compliant with the target production rate of the reservoir production strategy 224, the method 400 can proceed to feature 302 of method 300. For instance, adjustments to the well's 102 variable choke valve 112 can cease and the well's 102 operation can continue to be monitored (e.g., by the status checker 216). Where the adjusted well 102 is found to be non-compliant, the method 400 can proceed to 402 and the variable choke valve 112 can be subject to a further iteration of adjustment and evaluation.
During the second and subsequent iterations of method 400, the one or more choke valve controllers 120 can adjuster-adjust the variable choke valve 112 by an increment of choke positions to align the production of the well 102 with the target production rate. In one or more embodiments, the increment of adjustment employed in the second and subsequent of method 400 can be different than the increment of adjustment employed in the first iteration of method 400. For example, as a result of the choke position adjustment enacted during the first iteration, the difference between the production data 222 resulting from the evaluation period and the target production rate can decrease; thereby the adjustment increment employed during the second iteration can likewise decrease. In one or more embodiments, the direction of flowrate adjustment employed in the second iteration of method 400 can be different than the direction of flowrate adjustment employed in the first iteration of method 400. For example, the first iteration can adjust the choke position to increase the well's 102 flowrate; whereas the second iteration can adjust the choke position to decrease the well's 102 flowrate (e.g., where the first iteration of method 400 over-adjusted the variable choke valve 112).
By executing multiple iterations of method 400 the system 101 can gradually tune the variable choke valve 112 to a setting that results in the one or more target production rates defined by the reservoir production strategy 224. During the production life of the well 102, the variable choke valve 112 may need to be adjusted multiple times for the well to maintain compliance with the one or more target production rates. For example, even where the one or more target production rates remain constant, operating conditions of the well 102 can vary; thereby changing the production associated with a given choke position. However, the system 101 can implement methods 300 and/or 400 to: continuously monitor production of the well 102, identify when the well 102 is non-compliant with target production rates, update a steady-state multi-phase flow model 226 to accurately characterize the current operational capabilities of the well 102, and/or control the variable choke valve 112 to align the well's 102 production with the one or more target production values.
In view of the foregoing structural and functional description, those skilled in the art will appreciate that portions of the embodiments may be embodied as a method, data processing system, or computer program product. Accordingly, these portions of the present embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware, such as shown and described with respect to the computer system of FIG. 5 . Furthermore, portions of the embodiments may be a computer program product on a computer-usable storage medium having computer readable program code on the medium. Any non-transitory, tangible storage media possessing structure may be utilized including, but not limited to, static and dynamic storage devices, hard disks, optical storage devices, and magnetic storage devices, but excludes any medium that is not eligible for patent protection under 35 U.S.C. § 101 (such as a propagating electrical or electromagnetic signal per se). As an example and not by way of limitation, a computer-readable storage media may include a semiconductor-based circuit or device or other IC (such, as for example, a field-programmable gate array (FPGA) or an ASIC), a hard disk, an HDD, a hybrid hard drive (HHD), an optical disc, an optical disc drive (ODD), a magneto-optical disc, a magneto-optical drive, a floppy disk, a floppy disk drive (FDD), magnetic tape, a holographic storage medium, a solid-state drive (SSD), a RAM-drive, a SECURE DIGITAL card, a SECURE DIGITAL drive, or another suitable computer-readable storage medium or a combination of two or more of these, where appropriate. A computer-readable non-transitory storage medium may be volatile, nonvolatile, or a combination of volatile and non-volatile, where appropriate.
Certain embodiments have also been described herein with reference to block illustrations of methods, systems, and computer program products. It will be understood that blocks of the illustrations, and combinations of blocks in the illustrations, can be implemented by computer-executable instructions. These computer-executable instructions may be provided to one or more processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus (or a combination of devices and circuits) to produce a machine, such that the instructions, which execute via the processor, implement the functions specified in the block or blocks.
These computer-executable instructions may also be stored in computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture including instructions which implement the function specified in the flowchart block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.
In this regard, FIG. 5 illustrates one example of a computer system 500 that can be employed to execute one or more embodiments of the present disclosure. Computer system 500 can be implemented on one or more general purpose networked computer systems, embedded computer systems, routers, switches, server devices, client devices, various intermediate devices/nodes or standalone computer systems. Additionally, computer system 500 can be implemented on various mobile clients such as, for example, a personal digital assistant (PDA), laptop computer, pager, and the like, provided it includes sufficient processing capabilities.
Computer system 500 includes processing unit 502, system memory 504, and system bus 506 that couples various system components, including the system memory 504, to processing unit 502. Dual microprocessors and other multi-processor architectures also can be used as processing unit 502. System bus 506 may be any of several types of bus structure including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. System memory 504 includes read only memory (ROM) 510 and random access memory (RAM) 512. A basic input/output system (BIOS) 514 can reside in ROM 510 containing the basic routines that help to transfer information among elements within computer system 500.
Computer system 500 can include a hard disk drive 516, magnetic disk drive 518, e.g., to read from or write to removable disk 520, and an optical disk drive 522, e.g., for reading CD-ROM disk 524 or to read from or write to other optical media. Hard disk drive 516, magnetic disk drive 518, and optical disk drive 522 are connected to system bus 506 by a hard disk drive interface 526, a magnetic disk drive interface 528, and an optical drive interface 530, respectively. The drives and associated computer-readable media provide nonvolatile storage of data, data structures, and computer-executable instructions for computer system 500. Although the description of computer-readable media above refers to a hard disk, a removable magnetic disk and a CD, other types of media that are readable by a computer, such as magnetic cassettes, flash memory cards, digital video disks and the like, in a variety of forms, may also be used in the operating environment; further, any such media may contain computer-executable instructions for implementing one or more parts of embodiments shown and described herein.
A number of program modules may be stored in drives and RAM 510, including operating system 532, one or more application programs 534, other program modules 536, and program data 538. In some examples, the application programs 534 can include the status checker 216, multi-phase flow simulator 218, and/or choke valve controller 120, and the program data 538 can include the production data 222, the reservoir production strategy 224, the auxiliary data 225, the steady-state multi-phase flow models 226, and/or one or more choke position adjustment instructions. The application programs 534 and program data 538 can include functions and methods programmed to optimize one or more i-fields 100 by monitoring well 102 production and/or controlling variable choke valves 112, such as shown and described herein.
A user may enter commands and information into computer system 500 through one or more input devices 540, such as a pointing device (e.g., a mouse, touch screen), keyboard, microphone, joystick, game pad, scanner, and the like. For instance, the user can employ input device 540 to edit or modify one or more schedules, operating thresholds and/or ranges, optimal thresholds and/or ranges, default adjustment increments, reservoir production strategy 224, a combination thereof, and/or the like. These and other input devices 540 are often connected to processing unit 502 through a corresponding port interface 542 that is coupled to the system bus, but may be connected by other interfaces, such as a parallel port, serial port, or universal serial bus (USB). One or more output devices 544 (e.g., display, a monitor, printer, projector, or other type of displaying device) is also connected to system bus 506 via interface 546, such as a video adapter.
Computer system 500 may operate in a networked environment using logical connections to one or more remote computers, such as remote computer 548. Remote computer 548 may be a workstation, computer system, router, peer device, or other common network node, and typically includes many or all the elements described relative to computer system 500. The logical connections, schematically indicated at 550, can include a local area network (LAN) and a wide area network (WAN). When used in a LAN networking environment, computer system 500 can be connected to the local network through a network interface or adapter 552. When used in a WAN networking environment, computer system 500 can include a modem, or can be connected to a communications server on the LAN. The modem, which may be internal or external, can be connected to system bus 506 via an appropriate port interface. In a networked environment, application programs 534 or program data 538 depicted relative to computer 500, or portions thereof, may be stored in a remote memory storage device 554.

ADDITIONAL EMBODIMENTS

The present disclosure is also directed to the following exemplary embodiments:
Embodiment 1: A method, comprising: monitoring production data that characterizes operation of a well extracting production fluid from a hydrocarbon reservoir; generating a steady-state multi-phase flow model based on the production data; and controlling a variable choke valve of the well to adjust a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy data regarding the hydrocarbon reservoir.
Embodiment 2: The method of embodiment 1, further comprising: comparing the production data to a target production rate range defined by the reservoir production strategy data to evaluate the operation of the well.
Embodiment 3: The method of any of embodiments 1 and/or 2, further comprising: determining that the well is non-compliant with the reservoir production strategy data based on flowrate data included in the production data being outside the target production rate range; and analyzing the steady-state multi-phase flow model to determine whether the well is capable of meeting the target production value.
Embodiment 4: The method of any of embodiments 1-3, further comprising: generating a notification delineating that the well is non-compliant with the reservoir production strategy data based on a determination that the well is non-compliant and a determination that the well is incapable of meeting the target production value under current operating conditions.
Embodiment 5: The method of any of embodiments 1-4, further comprising: adjusting the variable choke valve from a first choke position to a second choke position; monitoring a second set of production data that characterizes a second operation of the well at the second choke position; and comparing the second set of production data to the target production value to evaluate the second operation of the well.
Embodiment 6: The method of any of embodiments 1-5, where the production data includes a measured flowrate value. Also, the target production value defines an optimal flowrate. Further, the measured flow rate value is less than the optimal flowrate value. Moreover, the adjusting the variable choke valve from the first choke position to the second choke position increases the flowrate of the production fluid.
Embodiment 7: The method of any of embodiments 1-6, where the second set of production data is monitored for a defined evaluation period. Also, the second set of production data is compared to the target production value at an end of the defined evaluation period.
Embodiment 8: A system, comprising: memory to store computer executable instructions; one or more processors, operatively coupled to the memory, that execute the computer executable instructions to implement: a status checker configured to monitor production data that characterizes operation of a well extracting production fluid from a hydrocarbon reservoir; a multi-phase flow simulator configured to generate a steady-state multi-phase flow model based on the production data; and a choke valve controller configured to control a variable choke valve of the well to adjust a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy data regarding the hydrocarbon reservoir.
Embodiment 9: The system of embodiment 8, where the status checker is further configured to compare the production data to a target production rate range defined by the reservoir production strategy data to evaluate the operation of the well.
Embodiment 10: The system of any of embodiments 8 and/or 9, where the status checker is configured to determine that the well is non-compliant with the reservoir production strategy data based on flowrate data included in the production data being outside the target production rate range. Also, the multi-phase flow simulator is further configured to analyze the steady-state multi-phase flow model to determine whether the well is capable of meeting the target production value.
Embodiment 11: The system of any of embodiments 8-10, further comprising: a remote terminal unit configured to generate a notification delineating that the well is non-compliant with the reservoir production strategy data based on a determination that the well is non-compliant and a determination that the well is incapable of meeting the target production value under current operating conditions.
Embodiment 12: The system of any of embodiments 8-11, where the choke valve controller is further configured to adjust the variable choke valve from a first choke position to a second choke position. Also, the status checker is further configured to monitor a second set of production data that characterizes a second operation of the well at the second choke position and compare the second set of production data to the target production value to evaluate the second operation of the well.
Embodiment 13: The system of any of embodiments 8-12, where the choke valve controller increases the flowrate of the production fluid by adjusting the variable choke valve from the first choke position to the second choke position.
Embodiment 14: The system of any of embodiments 8-13, where the status checker is configured to monitor the second set of production data for a defined evaluation period and compare the second set of production data to the target production value at an end of the defined evaluation period.
Embodiment 15: A computer program product for controlling an intelligent oil field. The computer program product comprising a computer readable storage medium having computer executable instructions embodied therewith. The computer executable instructions executable by one or more processors to cause the one or more processors to: monitor production data that characterizes operation of a well at extracting production fluid from a hydrocarbon reservoir; generate a steady-state multi-phase flow model based on the production data; and control a variable choke valve of the well to adjust a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy data regarding the hydrocarbon reservoir.
Embodiment 16: The computer program product of embodiment 15, where the computer executable instructions further cause the one or more processors to: compare the production data to a target production rate range defined by the reservoir production strategy data to evaluate the operation of the well.
Embodiment 17: The computer program product of any of embodiments 15 and/or 16, where the computer executable instructions further cause the one or more processors to: determine that the well is non-compliant with the reservoir production strategy data based on flowrate data included in the production data being outside the target production rate range; and analyze the steady-state multi-phase flow model to determine whether the well is capable of meeting the target production value.
Embodiment 18: The computer program product of any of embodiments 15-17, where the computer executable instructions further cause the one or more processors to generate a notification delineating that the well is non-compliant with the reservoir production strategy data based on a determination that the well is non-compliant and a determination that the well is incapable of meeting the target production value under current operating conditions.
Embodiment 19: The computer program product of any of embodiments 15-18, where the computer executable instructions further cause the one or more processors to: adjust the variable choke valve from a first choke position to a second choke position; monitor a second set of production data that characterizes a second operation of the well at the second choke position; and compare the second set of production data to the target production value to evaluate the second operation of the well.
Embodiment 20: The computer program product of any of embodiments 15-19, where the production data includes a measured flowrate value. Also, the target production value defines an optimal flowrate. Further, the measured flow rate value is less than the optimal flowrate value. Moreover, adjusting the variable choke valve from the first choke position to the second choke position increases the flowrate of the production fluid.
Portions of the methods described herein can be performed by software or firmware in machine readable form on a tangible (e.g., non-transitory) storage medium. For example, the software or firmware can be in the form of a computer program including computer program code adapted to cause the communication system to perform various actions described herein when the program is run on a computer or suitable hardware device, and where the computer program can be embodied on a computer readable medium. Examples of tangible storage media include computer storage devices having computer-readable media such as disks, thumb drives, flash memory, and the like, and do not include propagated signals. Propagated signals can be present in a tangible storage media. The software can be suitable for execution on a parallel processor or a serial processor such that various actions described herein can be carried out in any suitable order, or simultaneously.
It is to be further understood that like or similar numerals in the drawings represent like or similar elements through the several figures, and that not all components or steps described and illustrated with reference to the figures are required for all embodiments or arrangements.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “contains”, “containing”, “includes”, “including,” “comprises”, and/or “comprising,” and variations thereof, when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Terms of orientation are used herein merely for purposes of convention and referencing and are not to be construed as limiting. However, it is recognized these terms could be used with reference to an operator or user. Accordingly, no limitations are implied or to be inferred. In addition, the use of ordinal numbers (e.g., first, second, third) is for distinction and not counting. For example, the use of “third” does not imply there is a corresponding “first” or “second.” Also, the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of “including,” “comprising,” “having,” “containing,” “involving,” and variations thereof herein, is meant to encompass the items listed thereafter and equivalents thereof as well as additional items.
While the disclosure has described several exemplary embodiments, it will be understood by those skilled in the art that various changes can be made, and equivalents can be substituted for elements thereof, without departing from the spirit and scope of the invention. In addition, many modifications will be appreciated by those skilled in the art to adapt a particular instrument, situation, or material to embodiments of the disclosure without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, or to the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the appended claims.
While the present disclosure has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this disclosure, will appreciate that other embodiments may be devised which do not depart from the scope of the disclosure as described herein. Accordingly, the scope of the disclosure should be limited only by the attached claims.

Claims

1. A method, comprising:

monitoring production data that characterizes operation of a well extracting production fluid from a hydrocarbon reservoir;

generating a steady-state multi-phase flow model based on the production data; and

controlling a variable choke valve of the well to adjust a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy regarding the hydrocarbon reservoir, wherein the hydrocarbon reservoir comprises two or more wells.

2. The method of claim 1, further comprising:

comparing the production data to a target production rate range defined by the reservoir production strategy data to evaluate the operation of the well.

3. The method of claim 2, further comprising:

determining that the well is non-compliant with the reservoir production strategy data based on flowrate data included in the production data being outside the target production rate range; and

analyzing the steady-state multi-phase flow model to determine whether the well is capable of meeting the target production value.

4. The method of claim 3, further comprising:

generating a notification delineating that the well is non-compliant with the reservoir production strategy data based on a determination that the well is non-compliant and a determination that the well is incapable of meeting the target production value under current operating conditions.

5. The method of claim 3, further comprising:

adjusting the variable choke valve from a first choke position to a second choke position;

monitoring a second set of production data that characterizes a second operation of the well at the second choke position; and

comparing the second set of production data to the target production value to evaluate the second operation of the well.

6. The method of claim 5, wherein the production data includes a measured flowrate value, wherein the target production value defines an optimal flowrate, wherein the measured flow rate value is less than the optimal flowrate value, and wherein the adjusting the variable choke valve from the first choke position to the second choke position increases the flowrate of the production fluid.

7. The method of claim 5, wherein the second set of production data is monitored for a defined evaluation period, and wherein the second set of production data is compared to the target production value at an end of the defined evaluation period.

8. A system, comprising:

memory to store computer executable instructions;

one or more processors, operatively coupled to the memory, that execute the computer executable instructions to implement:

a status checker configured to monitor production data that characterizes operation of a well extracting production fluid from a hydrocarbon reservoir;

a multi-phase flow simulator configured to generate a steady-state multi-phase flow model based on the production data; and

a choke valve controller configured to control a variable choke valve of the well to adjust a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy data regarding the hydrocarbon reservoir, wherein the hydrocarbon reservoir comprises two or more wells.

9. The system of claim 8, wherein the status checker is further configured to compare the production data to a target production rate range defined by the reservoir production strategy data to evaluate the operation of the well.

10. The system of claim 9, wherein the status checker is configured to determine that the well is non-compliant with the reservoir production strategy data based on flowrate data included in the production data being outside the target production rate range; and wherein the multi-phase flow simulator is further configured to analyze the steady-state multi-phase flow model to determine whether the well is capable of meeting the target production value.

11. The system of claim 9, further comprising:

a remote terminal unit configured to generate a notification delineating that the well is non-compliant with the reservoir production strategy data based on a determination that the well is non-compliant and a determination that the well is incapable of meeting the target production value under current operating conditions.

12. The system of claim 11, wherein the choke valve controller is further configured to adjust the variable choke valve from a first choke position to a second choke position, wherein the status checker is further configured to monitor a second set of production data that characterizes a second operation of the well at the second choke position and compare the second set of production data to the target production value to evaluate the second operation of the well.

13. The system of claim 12, wherein the choke valve controller increases the flowrate of the production fluid by adjusting the variable choke valve from the first choke position to the second choke position.

14. The system of claim 13, wherein the status checker is configured to monitor the second set of production data for a defined evaluation period and compare the second set of production data to the target production value at an end of the defined evaluation period.

15. A computer program product for controlling an intelligent oil field, the computer program product comprising a computer readable storage medium having computer executable instructions embodied therewith, the computer executable instructions executable by one or more processors to cause the one or more processors to:

monitor production data that characterizes operation of a well at extracting production fluid from a hydrocarbon reservoir;

generate a steady-state multi-phase flow model based on the production data; and

control a variable choke valve of the well to adjust a flowrate of the production fluid based on the steady-state multi-phase flow model and reservoir production strategy data regarding the hydrocarbon reservoir, wherein the hydrocarbon reservoir comprises two or more wells.

16. The computer program product of claim 15, wherein the computer executable instructions further cause the one or more processors to:

compare the production data to a target production rate range defined by the reservoir production strategy data to evaluate the operation of the well.

17. The computer program product of claim 16, wherein the computer executable instructions further cause the one or more processors to:

determine that the well is non-compliant with the reservoir production strategy data based on flowrate data included in the production data being outside the target production rate range; and

analyze the steady-state multi-phase flow model to determine whether the well is capable of meeting the target production value.

18. The computer program product of claim 17, wherein the computer executable instructions further cause the one or more processors to:

generate a notification delineating that the well is non-compliant with the reservoir production strategy data based on a determination that the well is non-compliant and a determination that the well is incapable of meeting the target production value under current operating conditions.

19. The computer program product of claim 18, wherein the computer executable instructions further cause the one or more processors to:

adjust the variable choke valve from a first choke position to a second choke position;

monitor a second set of production data that characterizes a second operation of the well at the second choke position; and

compare the second set of production data to the target production value to evaluate the second operation of the well.

20. The computer program product of claim 19, wherein the production data includes a measured flowrate value, wherein the target production value defines an optimal flowrate, wherein the measured flow rate value is less than the optimal flowrate value, and wherein adjusting the variable choke valve from the first choke position to the second choke position increases the flowrate of the production fluid.