FR3136862A1 - METHODS TO PERFORM REAL-TIME ANALYSIS OF FLUID FLOW IN A WELL, METHODS TO PERFORM REAL-TIME ANALYSIS OF A WELL OPERATION, AND REAL-TIME WELL OPERATION SYSTEMS - Google Patents

Abstract

A method for performing real-time analysis of fluid flow in a well includes receiving streamed data simultaneously from a plurality of sensors and populating a model of the well with the data, where the model has a plurality of parameters that are inputs to the model, and where each parameter is associated with data streamed from one of the plurality of sensors. The method also includes calculating a fluid flow of a fluid flowing through a location of the well based on the model. Responsive to receiving new streaming data from one or more of the plurality of sensors, the method further includes dynamically calibrating the model in real time based on the new data and calculating An updated fluid flow of fluid flowing through the well location based on the recalibrated model.

Description

Methods for performing real-time analysis of fluid flow in a well, methods for performing real-time analysis of a well operation, and real-time well operations systems Context

The present disclosure generally relates to methods for performing real-time analysis of fluid flow in a well, methods for performing real-time analysis of a well operation, and real-time well operations systems. .

Sensors are sometimes positioned at multiple positions on a hydrocarbon well to monitor the flow of fluids into and out of the well. Some of the sensors are positioned to monitor the fluid flow of the hydrocarbon resources to determine the production rate and total production of the hydrocarbon resources over time.

Illustrative embodiments of the present disclosure are described in detail below with reference to the figures of the accompanying drawings, which are incorporated herein by reference and in which:

is a schematic side view of a well environment where a real-time well operations system is deployed;

is an illustration of a network of nodes positioned along multiple layers of a well area;

is a flowchart of a process for performing real-time analysis of fluid flow in a well, and real-time analysis of a well operation;

is a block diagram of the real-time well operations system of the ;

is another block diagram of the real-time well operations system according to claim 1;

is a flowchart of a process for performing real-time analysis of fluid flow in a well; And

is a flowchart of a process for performing real-time analysis of a well operation.

The figures illustrated are intended to serve as examples only and are not intended to state or imply any limitation with respect to the environment, architecture, design or process in which different embodiments may be implemented. artwork.

detailed description

In the following detailed description of the illustrative embodiments, reference is made to the accompanying drawings, which form an integral part hereof. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, and it is understood that other embodiments may be used and that logical structural, mechanical, electrical modifications and chemical can be made without departing from the spirit or scope of the invention. To avoid details that are not necessary to enable those skilled in the art to practice the embodiments described herein, the description may omit certain information known to those skilled in the art. The following detailed description should therefore not be taken in a limiting sense, and the scope of the illustrative embodiments is defined solely by the appended claims.

The present disclosure relates to methods for performing real-time analysis of fluid flow in a well, methods for performing real-time analysis of a well operation, and systems for analyzing fluid flow in a well. real time. A real-time well operations system receives streamed data simultaneously from multiple sensors that are disposed in or near a well and configured to provide data indicative of fluid flow ("data data"). 'fluid flow') and calculate the fluid flow, the condition of hardware components and devices that are positioned in or near the well, and the condition of one or more well operations that are performed at the well level. Examples of fluid flow data include, but are not limited to, data indicative of fluid flow rate, fluid composition (e.g., oil, water), fluid flow direction (such as upward, downward, in a device such as a valve, outside the device, from a first device to a second device, etc.), the fluid pressure, a derivative of the fluid pressure in the time, and other types of data indicative of fluid flowing at one or more locations in or near the well. Examples of hardware components and devices include, but are not limited to, inflow control devices, valves, pressure gauges, seals, tubulars, and other hardware components and devices that are deployed in or around the well.

The real-time well operations system populates a model of the well with the data. Specifically, the real-time well operations system simultaneously receives raw data from sensors and uses the raw data as input parameters to populate and recalibrate the model. In some embodiments, the real-time well operations system accumulates raw data that is simultaneously transmitted by the sensors, performs operations to reconcile the raw data, and populates and recalibrates the model while the raw data is streamed. continuously. As mentioned here, a well model is a virtual representation of the well based on measurements made by one or more sensors and other types of hardware components of the well. In some embodiments, the model includes or is configured to provide up-to-date fluid flow data at various locations in or near the well, and data indicative of the status of hardware components and devices that are positioned in or near the well. In some embodiments, the well model is a digital twin of the well that is dynamically or periodically updated when the model is recalibrated. As mentioned here, a well digital twin is a permanent digital model of a physical object such as a well location, a section of the well, or the entire well. In some embodiments, the real-time well operations system performs on-board calculation operations to generate and recalibrate the model. As discussed here, an edge computing operation is a distributed computing operation that places computation and data storage near or at the sink. In one or more of these embodiments, the real-time well operations system receives the raw data and performs calculations and other operations to generate the model and recalibrate the model without first storing the raw data in a real-time well operations system storage support. In some embodiments, the real-time well operations system also uses properties of hardware components as input parameters to generate and recalibrate the model. Examples of hardware component properties include, but are not limited to, dimensions of flow control devices, valves, pressure gauges, seals, tubulars, and other hardware components and devices that are deployed in or around the well, the locations and depths of the hardware components, the dimensions of the outer diameters and the inner diameters of the hardware components, and other physical, mechanical, electrical, and electromechanical properties of the hardware components.

The real-time well operations system calculates the fluid flow properties of a fluid flowing through a desired location at or around the well based on the model. For example, when the desired location is the location that is a threshold number of feet below the surface and within a first area of interest, the real-time well operations system uses the generated model to obtain current flow rate, fluid composition, flow direction, and other fluid flow data at the location. In some embodiments, the fluid flow analysis system also determines the state of a hardware component at a desired location based on the model. For example, when the device is an inflow control device that is disposed in a second area of interest, the real-time well operations system uses the generated model to determine fluid flow through the inflow control device, the operational status of the inflow control device, and if the inflow control device malfunctions (e.g., fails to open at a desired location, does not close, does not open at a desired flow rate, does not close at a desired flow rate, does not provide the desired fluid flow, or some other type of malfunction). In some embodiments, the real-time well operations system receives the raw data and calculates fluid flow based on the raw data without first storing the raw data in a storage medium of the operations system wells in real time. Likewise, in some embodiments, the real-time well operations system receives the raw data and determines the status of a hardware component at the desired location based on the raw data without first storing the raw data into a real-time well operations system storage media. Additional descriptions of operations performed by the real-time well operations system to calculate fluid flow and to analyze hardware components and other devices located at or near the well are provided here.

During a well operation, up-to-date data is continuously transmitted from sensors to the well operations system in real time. The real-time well operations system, in response to receiving new streaming data from one or more sensors, dynamically recalibrates the real-time well model based on the new data, and calculates updated fluid flow properties of the fluid based on the recalibrated model. Continuing with the previous example, the real-time well operations system, in response to receiving new data, uses the recalibrated model to obtain the current flow rate, fluid composition, flow direction and d other fluid flow data at the location. Although the preceding example describes performing operations to obtain the current flow rate, fluid composition, flow direction, and other fluid flow data at a location, the operations system real-time well monitoring is configured to perform the operations described herein to simultaneously or nearly simultaneously obtain current flow rate, fluid composition, flow direction, and other fluid flow data at multiple locations at or near the well and/or throughout the well. In some embodiments, the real-time well operations system dynamically calculates and recalculates an up-to-date map of fluid flowing through a location, a section of the well, and/or through the entire well.

In some embodiments, the real-time well operations system, in response to receiving new streaming data from one or more sensors, determines whether a characteristic of the fluid flow (e.g. (e.g., flow rate, fluid density, fluid composition, fluid pressure, or other quantifiable fluid flow characteristic of the fluid) has changed over a threshold period of time (e.g., one minute , an hour, a day or another period of time). In one or more of these embodiments, the real-time well operations system dynamically recalibrates the real-time model based on the change in the fluid flow characteristic over the period of time. For example, the real-time well operations system continuously monitors the flow rate (first characteristic) and fluid composition (second characteristic) of a fluid flowing through an orifice positioned proximate a zone of production over a period of time. Additionally, the real-time well operations system, in response to a determination that the flow rate has increased or decreased by more than a threshold flow rate or threshold range within the last hour, day, from the last week or other time period, dynamically recalibrates the model in real time to account for the change in flow. Likewise, the real-time well operations system, in response to a determination that the fluid composition of the fluid has changed by more than a threshold amount (e.g., the composition of hydrocarbon sources within fluid has increased or decreased by more than a threshold percentage) in the last hour, day, week, or other period of time, dynamically recalibrates the model in real time to account for the change of the fluid composition of the fluid. In some embodiments, the real-time well operations system continuously and dynamically monitors changes in one or more calibration coefficients of the model, and in response to a determination that the change is greater than a value threshold, dynamically recalibrates the model in real time. For example, when a calibration coefficient defines a pressure difference across an inflow control device, the real-time well operations system dynamically calculates the calibration coefficient based on the most recent data obtained by the sensors. Further, the real-time well operations system, in response to a determination that the most recently calculated calibration coefficient varies from the calibration coefficient used by the model by more than a threshold value, applies the coefficient most recently calculated calibration value to dynamically recalibrate the model.

In some embodiments, where the recalibrated model is not an existing digital twin of the well, the real-time well operations system compares the recalibrated model to the digital twin of the well to determine whether the digital twin matches the recalibrated model . In one or more of these embodiments, and in response to a determination that a property of the recalibrated model (e.g., net fluid flow out of a location, composition of fluid flowing at the location (location, or other property of the recalibrated model) varies by a corresponding property of the digital twin by more than a threshold range, dynamically updates the digital twin based on the recalibrated model. In one or more of these embodiments, the most recently recalibrated model is saved as a digital twin.

In some embodiments, the real-time well operations system continuously and dynamically monitors changes in one or more fluid flow characteristics or one or more model characteristics to determine whether changes are within an acceptable threshold range. In one or more of these embodiments, the real-time well operations system also performs the operations described herein to dynamically recalibrate the model while the characteristics of the fluid flow or model remain within the acceptable threshold range . In one or more of these embodiments, the real-time well operations system, in response to a determination that the output is not within a threshold range, requests a manual recalibration of the model, or requests a manual review of the model by an operator. For example, when the fluid flow through a production area is initially 1,000 barrels of oil and 0 barrels of water over a period of time, and the acceptable threshold range is less than 100 barrels of water over the time period, the real-time well operations system dynamically recalibrates the model while less than 100 barrels of water flow through the production area over the time period . However, the real-time well operations system alerts the operator and instructs the operator to review the model to manually recalibrate the model or make manual adjustments to one or more model parameters to account for increasing water flow through the production area beyond the threshold range. In some embodiments, the real-time well operations system, in response to a determination that the output is not within a threshold range, dynamically recalibrates the model to fit the model within the threshold range, or recalibrates the model to adjust the model within the threshold range if manual recalibration is not performed within a threshold time period.

In some embodiments, the real-time well operations system determines one or more directions of fluid flow at a location. In some embodiments, the real-time well operations system, in response to receiving the new data, dynamically recalibrates the real-time model based on the new data and determines the fluid flow direction. flowing through the well location based on the recalibrated model. As discussed herein, a fluid flow direction refers not only to net fluid flow in a single direction, but also to different fluid flow directions at a location or area, or to different directions of fluid flow into and out of various hardware components and devices that are placed along or near the well. For example, when 1,190 barrels of oil out of 1,200 barrels of oil flowing from a formation in a producing area flow out of the producing zone and toward the surface, and 10 of the 1,200 barrels of oil flows into an adjacent production zone that is further downhole from the production zone of interest, the net fluid flow out of the production zone to the surface is 1,190 barrels of oil, however , net fluid flow does not indicate the total amount of oil actually produced at the production area due to cross flow or spillage. The real-time well operations system is configured to determine not only the direction of net fluid flow at a location, but also fluid flow in multiple directions at the location. In one or more of these embodiments, the real-time well operations system determines, based on the direction of fluid flow, the presence of a malfunctioning device, such as a leaking joint that causes fluid to flow into an adjacent production area.

In some embodiments, the real-time well operations system dynamically analyzes current data and previously received data from a pattern associated with fluid flow of the fluid. For example, the real-time well operations system is configured to recognize existing and new fluid flow patterns such as continued flow out of the production zone, fluid composition of the fluid flowing out of the production area and other patterns associated with fluid flow or one or more properties of fluid flow. The real-time well operations system determines a change in the pattern associated with fluid flow and, in response to a determination that the change in the pattern is greater than a threshold, dynamically recalibrates the model in real time. Continuing with the previous example, when the real-time well operations system recognizes that the fluid composition of the fluid flowing out of the production zone is approximately 80% oil and 20% water for the past month, the real-time well operations system, in response to a determination that the fluid composition of the water has increased above 25% (or other threshold), dynamically recalibrates the model in time real to update the model.

In some embodiments, the real-time well operations system predicts fluid flow of the fluid at a future time or during a threshold time period in the future based on the model. In one or more of these embodiments, the real-time well operations system dynamically analyzes current data and previously received data for a pattern associated with fluid flow of the fluid. The real-time well operations system then generates a prediction of fluid flow at the future time or during the threshold time period in the future based on the pattern. In some embodiments, the real-time well operations system dynamically updates the fluid flow pattern and generates updated predictions of fluid flow at the future time or during the period threshold time in the future based on the most recently determined fluid flow pattern. In one or more of these embodiments, the real-time well operations system also improves and/or optimizes existing predictions of fluid flow at the future time or during the threshold time period in the future over the basis of the most recently determined fluid flow pattern.

In some embodiments, the real-time well operations system projects fluid flow at a location, such as the wellhead of the well, and obtains measured fluid flow at the location . The real-time well operations system compares the projected fluid flow to the measured fluid flow, and dynamically recalibrates the model in real time in response to a determination that the projected fluid flow and the measured fluid flow fluid measured at the location vary by more than one threshold. In one or more of these embodiments, the real-time well operations system also recalculates fluid flow at other locations in the well or near the well based on the recalibrated model. In some embodiments, the real-time well operations system, after receiving new data, determines whether there is a change in one or more model parameters over a period of time, and dynamically recalibrates the model in real time based on a change in the one or more parameters.

The real-time well operations system is also configured to perform real-time analysis of a well operation, including determining the presence of defective hardware components. More particularly, the real-time well operations system determines, based on data streamed from sensors disposed in a well, the presence of defective equipment disposed in the well, where the data is associated with parameters of a digital twin of the well. In some embodiments, the real-time well operations system analyzes current data and previously streamed data over a threshold time period (e.g., over the last hour, last day , from the last week, etc.) to determine if a hardware component has malfunctioned. The real-time well operations system determines whether a property of the digital twin falls within a threshold range. Further, the real-time well operations system, in response to a determination that the model is not within the threshold range, determines an improvement in the property of the digital twin, and dynamically recalibrates the digital twin in real time based on the data streamed from the plurality of sensors to improve the property of the digital twin. In some embodiments, the real-time well operations system predicts, based on the digital twin, fluid flow of the fluid flowing through the well at a future time or over a period of time. time in the future. In some embodiments, the real-time well operations system uses the digital twin to perform a fluid flow simulation of a fluid flowing through the well to determine how to improve the fluid flow fluid. In one or more of these embodiments, the real-time well operations system determines an improvement to an existing hardware configuration to improve fluid flow of the fluid. The real-time well operations system then provides a recommendation to reconfigure the equipment to improve the fluid's fluid flow. In some embodiments, the real-time well operations system is configured to analyze historical and/or live data indicative of sensor and hardware operations, and to replace and/or supplement missing data from a or multiple defective sensors or hardware. In one or more of these embodiments, the real-time well operations system analyzes historical and/or live data from functional sensors and hardware and estimates the data that would have been transmitted by one or more sensors or defective hardware (if the malfunction had not occurred) to complete and/or replace the missing data.

Although the preceding paragraphs describe operations performed by the real-time well operations system to determine fluid flow at a location, the real-time well operations system is configured to simultaneously determine the fluid flow at multiple locations. Likewise, although the preceding paragraphs describe operations performed by the real-time well operations system to determine the presence of defective hardware, the real-time well operations system is configured to simultaneously determine the presence multiple defective hardware, such as multiple defective sensors and/or valves. Likewise, although the preceding paragraphs describe operations performed by the real-time well operations system to provide a recommendation for improving fluid flow, the real-time well operations system is configured to simultaneously provide multiple recommendations for improving fluid flow at different locations, improving different aspects of a well operation, providing multiple forecasts of well operations of the well, and dynamically receiving user inputs and configurations. Additional descriptions of the foregoing methods for performing real-time analysis of fluid flow in a well, methods for performing real-time analysis of a well operation, and real-time well operations systems are described in the paragraphs below and are illustrated in Figures 1 to 7.

Turning now to the figures, the is a schematic side view of a well environment 100 in which a real-time well operations system 118 is deployed proximate a surface 108 of a well 102. As illustrated in , a wellbore 114 of well 102 extends from surface 108 of well 102 to or through formation 126. Completion 116 is coupled to or has one or more orifices, valves, and other devices that allow fluids (such as hydrocarbon resources and reservoir fluids) to flow from formation 126 through perforations 121A to 121C into completion 116, and via completion 116 back to surface 108. To this end, a baffle or an outlet conduit 128 may be connected to a container 130 at the wellhead 106 to provide a fluid return flow path from the wellbore 114.

In the embodiment of the , the completion 116 extends through three zones 111A, 111B and 111C. Additionally, the packing assemblies 110A to 110C and other hardware components (not shown), and the sensors 131A to 131C and 141A to 141C and other sensors (not shown) are also lowered downhole with completion 116, and are deployed or activated to isolate zones 111A, 111B and 111C, control fluid flow into and out of zones 111A, 111B and 111C, and continuously measure and broadcast fluid flow data, and data indicative of the condition of the hardware components deployed within the wellbore 114, at or near the wellbore 114, and near the surface 108, and data indicative of the operation of wells by telemetry to the real-time well operations system 118.

The real-time well operations system 118 receives streamed data from the sensors 131A to 131C and 141A to 141C and populates an initial fluid flow model in the zones 111A to 111C based on the broadcast data. continuously. In the embodiment of the , the sensors 131A to 131C are positioned outside the completion 116, while the sensors 141A to 141C are positioned inside the completion 116. In addition, each pair of sensors 131A and 141A, 131B and 141B, and 131C and 141C is configured to measure fluid pressure, measure data indicative of fluid flow, and/or measure data that is derived to determine fluid flow at or near their corresponding locations. The measurements are used by the real-time well operations system 118 as input parameters to populate the initial model of the well 102 which provides a virtual representation of various aspects of the well 102, including fluid flow in the wells. zones 111A to 111C, the net fluid flow out of each of zones 111A to 111C, the direction of fluid flow at different locations within zones 111A to 111C, the fluid flow at of the wellhead 106, the fluid composition of the fluids flowing into and out of the zones 111A to 111C, the fluid pressure of the fluids in the zones 111A to 111C, other fluid flow properties and other aspects of well 102 and well operations performed at well 102. In some embodiments, while sensors 131A to 131C and 141A to 141C and other sensors continuously provide data to the well operations system real-time well 118, the real-time well operations system 118 uses the updated data to recalibrate the model. In the embodiment of the , sensors 131D and 141D are positioned at or near wellhead 106 to measure actual fluid flow (e.g., actual flow rate, actual fluid pressure, or other fluid measurements) of the fluids flowing at the level of the wellhead 106.

In some embodiments, when the model projects a fluid flow of fluids flowing at the wellhead 106, the real-time well operations system 118 compares the projected fluid flow with the flow of fluid measured by the sensors 131D and 141D, and dynamically adjusts the model if the projected fluid flow differs from the measured fluid flow by more than a threshold value. In some embodiments, the real-time well operations system 118 continuously and dynamically monitors changes in one or more characteristics of the fluid flow or pattern to determine whether the changes are within a acceptable threshold range. In one or more of these embodiments, the real-time well operations system 118 also performs the operations described herein to dynamically recalibrate the model while the fluid flow characteristics or model characteristics remain within the range. acceptable threshold range. In one or more of these embodiments, the real-time well operations system 118, in response to a determination that the output is not within a threshold range, requests a manual recalibration of the model, or requests a revision manual of the model by an operator. In some embodiments, real-time well operations system 118 dynamically analyzes data obtained from sensors 131A to 131C and 141A to 141C to project fluid flow in zones 111A, 111B or 111C at a future date or for a period of time in the future.

Although the illustrates three pairs of sensors 131A and 141A, 131B and 141B, and 131C and 141C arranged in zones 111A, 111B and 111C, respectively, in certain embodiments, a different number and type of sensors are arranged in zones 111A, 111B, and 111C. Furthermore, although the preceding paragraphs describe the real-time well operations system 118 using data obtained from the sensors 131A and 141A, 131B and 141B, and 131C and 141C to populate and update the models of the well 102, in some embodiments, the real-time well operations system 118 is also configured to use data obtained from other sensors (not shown) and hardware components (not shown), data indicative of the well trajectory, data indicative of fluid composition (PVT), data indicative of reservoir information, and data indicative of other aspects of the well 102 and components and equipment disposed in or around the well 102 to fill and update models. Furthermore, although the illustrates the completion 116 deployed over three zones 111A to 111C, in some embodiments the completion 116 is deployed over a different number of zones. Furthermore, although the illustrates a completion operation, the real-time well operations system 118 may be deployed during other well operations, including, but not limited to, production operations, injection operations and d other types of well operations to perform real-time analysis of fluid flow, real-time analysis of the well operation, and to perform other operations described herein. Furthermore, although the illustrates the real-time well operations system 118 as a surface-based system, in some embodiments the real-time well operations system 118 is positioned in a downhole location or is a system cloud-based. In some embodiments, the real-time well operations system 118 is deployed near a subsea well and configured to perform the operations described herein to populate and recalibrate a model of the subsea well. Additional descriptions of the real-time well operations system 118 and the operations performed by the real-time well operations system 118 or similar systems are provided herein and are illustrated at least in Figures 3 through 7.

There is an illustration of a network 200 of nodes positioned along multiple layers of a zone of a well, such as one of zones 111A, 111B or 111C of the , where each node represents a location at or around the well. In the embodiment of the , the network 200 comprises a series of nodes along a first annular layer 210 comprising nodes 212 and 214, a second annular layer 220 comprising nodes 222 and 224, a third annular layer 230 comprising nodes 232 and 234, a fourth annular layer 240 having nodes 242 and 244, a reservoir layer 250 having nodes 252 and 254, and a casing layer 260 having nodes 262 and 264, where a sensor is positioned at a corresponding location of the node . A real-time well operations system, such as the real-time well operations system 118 of the , uses the flow data obtained by the sensors that are deployed at the nodes to determine the fluid flow properties (such as flow rate, fluid flow direction, fluid pressure and other aspects of fluid flow) at each node, to populate a model of the well area and to dynamically recalibrate the model based on up-to-date data streamed from the sensors. In some embodiments, the real-time well operations system automatically correlates fluid data obtained by sensors positioned at different nodes (such as nodes 232 and 234) and compares the different fluid data obtained by the different sensors to dynamically recalibrate the model. In some embodiments, the real-time well operations system uses one or more calibration coefficients to correlate different readings obtained from different sensors that are positioned at different locations, and to compensate for different readings due to placement and locations of sensors. In one or more of these embodiments, the real-time well operations system periodically or dynamically adjusts one or more values of the calibration coefficients based on one or more changes in fluid flow, changes to one or more sensors, and/or changes to one or more hardware components of the well.

Although the illustrates a set of nodes positioned along six layers within an area, in some embodiments, the network 200 has a different number of nodes that are positioned along a different number of layers within the area. Furthermore, although the illustrates nodes along a single zone, the real-time well operations system is configured to perform the operations described herein to simultaneously determine fluid flow at the nodes across multiple zones of the well, fill a model the well across multiple zones, automatically correlate sensor readings across multiple nodes, and dynamically recalibrate the model based on up-to-date data streamed from sensors positioned across multiple zones.

There is a flowchart of a process 300 for performing real-time analysis of fluid flow in a well, and real-time analysis of a well operation. At block 302, a well project is created. At block 304, a well digital twin is initialized. Additionally, at blocks 338 and 334, a well simulator uses the well model data to initialize the well digital twin. At block 306, the well digital twin is populated with real-time data. More specifically, the real-time data obtained by the sensors at block 336 is validated at block 332, before the real-time data is used as input parameters to populate the well digital twin. In block 308, a simulation of the well is executed. At block 310, the well data validation is output. At block 312, and in response to a determination that the output is valid, process 300 proceeds to block 316. Alternatively, at block 312, and in response to determining that the output is invalid, process 300 proceeds at block 324. At block 316, the output data is published. In block 314, the output data is provided via a machine communication interface to another electronic device, such as an operator electronic device. At block 318, the data inputs and outputs are stored in a database, and process 300 proceeds to block 320, where the next record is accessed, and process 300 returns to block 336. At block 318, after the data inputs and outputs are stored in the database, the process 300 also proceeds to block 322, where the data analysis and decision-making processes are performed. Process 300 then loops back from block 322 to block 316, where the output data is published.

At block 324, an automated calibration process described herein is executed. Process 300 then proceeds to block 326, and, in response to a determination that the calibration is successful, process 300 proceeds to block 330, and the new calibrated data is used. Alternatively, at block 326, and, in response to a determination that the calibration is not successful, process 300 proceeds to block 328, and a request for manual calibration is made, and the manually calibrated data is used at block 330 Process 300 then proceeds to block 334, where the existing well model data is updated or replaced with the newly calibrated data.

There is a block diagram of a real-time well operations system 400 that is similar to the real-time well operations system 118 of the , and which is configured to perform the operations illustrated in process 600 of the . The real-time well operations system 400 includes a storage medium 406 and a processor 410. The storage medium 406 may be formed from data storage components such as, among others, a read only memory (ROM) , random access memory (RAM), flash memory, magnetic hard disks, semiconductor hard disks, CD-ROM drives, DVD drives, floppy disk drives, and other types of components and data storage devices. In some embodiments, storage media 406 includes multiple data storage devices. In other embodiments, the multiple data storage devices may be physically stored at different locations. In one of these embodiments, the data storage devices are components of a server station, such as a cloud server. Fluid flow data, data indicative of the condition of hardware components and devices that are positioned in or near the well, and data indicative of the condition of one or more well operations that are being performed Well fluid flow data (collectively "well data") is stored at a first location 420 of the storage medium 406. Additionally, instructions for receiving streamed data simultaneously from of a plurality of sensors disposed in a well are stored at a second location 422 of the storage medium 406. Additionally, instructions for populating a model of the well with the data, where the model includes a plurality of parameters which are inputs to the model, are stored at a third location 424 of the storage medium 406. Additionally, instructions for calculating fluid flow of a fluid flowing through a location of the well based on the model are stored at a fourth location 426 of the storage medium 406. Additionally, in response to receiving new streamed data from one or more of the plurality of sensors, instructions for recalibrating dynamically the real-time model based on the new data is stored at a fifth location 428 of the storage medium 406. Additionally, in response to receiving new data streamed from one or more sensors of the plurality of sensors, instructions for calculating an updated fluid flow of the fluid flowing through the well location based on the recalibrated model are stored at a sixth storage media location 430 406. Additionally, additional instructions that are executed by processor 410 are stored in other locations of storage media 406.

There is a block diagram of a real-time well operations system 500 that is similar to the real-time well operations system 118 of the , and is configured to perform the operations illustrated in process 700 of the . The real-time well operations system 500 includes a storage media 506 and a processor 510 that are similar or identical to the storage media 406 and processor 410 of the . The well data is stored at a first location 520 of the storage medium 506. Additionally, instructions for determining, based on data initially streamed from a plurality of sensors disposed in a well, the presence of defective hardware disposed in the well are stored at a second location 522 of the storage medium 506. Additionally, instructions for determining whether a property of the model is within a threshold range are stored at a third location 524 of the storage medium 506. Additionally, and in response to a determination that the model is not within the threshold range, instructions for determining an improvement in the property of the model are stored at a fourth location 526 of storage media 506. Additionally, and in response to a determination that the model is not within the threshold range, instructions to dynamically recalibrate the model in real time based on the data streamed from the plurality of sensors for improving the model property are stored at a fifth location 528 of the storage medium 506. Additionally, additional instructions that are executed by the processor 510 are stored in other locations of the storage medium 506.

There is a flowchart of a process 600 for performing real-time analysis of a well operation. Although the operations of process 600 are shown in a particular sequence, some operations may be performed in different sequences or at the same time when possible. As described below, process 600 provides an intuitive way to determine activity associated with an object of interest.

At block S602, data streamed simultaneously from a plurality of sensors that are disposed in a well is received. For example, the real-time well operations system 118 of the receives, from sensors 131A to 131C and 141A to 141C of the , fluid flow data indicative of fluid flow at or near the corresponding locations 131A to 131C and 141A to 141C. In block S604, a model of the well is populated based on the data. In the embodiment of the , the real-time well operations system 118 is configured to populate the model while data is streamed simultaneously from the sensors 131A to 131C and 141A to 141C.

In block S606, the fluid flow of a fluid flowing through a location of the well is calculated based on the model. Continuing with the previous example, the real-time well operations system 118 of the uses the well model to determine fluid flow at a desired location or at other locations in the well. At block S608, in response to non-receipt of new streaming data from the one or more sensors, process 600 proceeds to block S613. Alternatively, at block S608, and in response to receiving new streaming data from the one or more sensors, process 600 proceeds to block S610, and the model is dynamically recalibrated in real time based on the new data . Continuing with the previous example, the real-time well operations system 118 continuously receives new data from the sensors 131A to 131C and 141A to 141C of the , and, in response to receiving the new data, dynamically recalibrates the well model based on the new data. At block S612, an updated fluid flow of the fluid flowing through the well location is calculated based on the recalibrated model. Continuing with the previous example, the real-time well operations system 118 uses the recalibrated model to determine fluid flow at the desired location or other locations in the well. Process 600 then proceeds to block S613 and a determination of whether or not to continue the recalibration operation is made. Process 600 returns to block S608 in response to a determination to continue the recalibration operation. Alternatively, process 600 terminates if a determination not to continue the recalibration operation is made.

There is a flowchart of a process 700 for performing real-time analysis of a well operation. Although the operations of process 700 are shown in a particular sequence, some operations may be performed in different sequences or at the same time when possible. As described below, process 700 provides an intuitive way to determine activity associated with an object of interest.

At block S702, the presence of defective hardware disposed in a well is determined based on data streamed from a plurality of sensors that are disposed in a well. For example, the real-time well operations system 118 of the is configured to analyze or run a digital twin of the well, where the data is associated with one or more parameters of the digital twin. More particularly, the real-time well operations system 118 analyzes the parameters and/or outputs of the digital twin to determine the presence of defective hardware, including, but not limited to, a leaking valve, a valve having an incorrect open or closed position, a defective pressure gauge and/or other defective hardware component located at or near the well. In block S704, a determination of whether a property of the model is within a threshold range is made. Continuing with the previous example, real-time well operations system 118 periodically or continuously determines whether one or more model properties, features, coefficients, and/or outputs are not within a predefined threshold range. At block S706, a determination that the model is not within a threshold range is made. Process 700 proceeds to block S711 in response to a determination that the model property is within the threshold range. Alternatively, process 700 proceeds to block S708 in response to a determination that the model property is indeed not within the threshold range. In block S708, an improvement of the model property is determined. In block S710, the model is dynamically recalibrated in real time based on the data streamed from the plurality of sensors to improve the property of the model. Process 700 then proceeds to block S711, and a determination whether to continue process 700 is made. Process 700 terminates in response to a determination not to proceed. Alternatively, process 700 returns to block S702 in response to a determination to continue.

The embodiments disclosed above have been presented for purposes of illustration and to enable those skilled in the art to practice the disclosure, but the disclosure is neither intended to be exhaustive nor limited to the forms described. Many non-substantive modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the disclosure. For example, although flowcharts describe a serial process, some of the processes/steps may be executed in parallel or out of sequence, or combined into a single step/process. The scope of the claims is intended to cover generally the disclosed embodiments and any such modifications. In addition, the following clauses represent additional embodiments of the disclosure and should be considered in connection with the disclosure.

Clause 1, a computer-implemented method for performing real-time analysis of fluid flow in a well, comprising: receiving streamed data simultaneously from a plurality of sensors disposed in a well; populating a model of the well with the data, wherein the model includes a plurality of parameters that are inputs to the model, and wherein each of the plurality of parameters is associated with data streamed from one sensor of the plurality of sensors; calculating a fluid flow of a fluid flowing through a location of the well based on the model; and in response to receiving new streamed data from one or more of the plurality of sensors: dynamically recalibrating the model in real time based on the new data; and calculating an updated fluid flow of the fluid flowing through the well location based on the recalibrated model.

Clause 2, the computer-implemented method of clause 1, wherein filling the model includes filling the model while data is streamed simultaneously from the plurality of sensors, and wherein calculating the Fluid flow includes calculating fluid flow while data is streamed simultaneously from the plurality of sensors.

Clause 3, the computer implemented method according to clauses 1 or 2, wherein calculating the fluid flow of the fluid flowing through the location includes calculating the fluid flow through the location before the data is stored on a storage medium, and wherein calculating the updated fluid flow of the fluid flowing through the location includes calculating the fluid flow of the fluid s 'flowing through the location before the updated data is stored on the storage media.

Clause 4, the computer-implemented method of any of clauses 1 to 3, wherein, in response to receiving the new data, the method further comprising: determining a change in a parameter of the plurality of parameters over a period of time; and dynamic recalibration of the model in real time based on the change of the parameter over the time period.

Clause 5, the computer-implemented method of any of clauses 1 to 4, wherein, in response to receiving the new data, the method further comprising: determining a change in a characteristic of fluid flow over a period of time; and dynamic recalibration of the model in real time based on the change in the fluid flow characteristic over the time period.

Clause 6, the computer-implemented method of any of clauses 1 to 5, further comprising: determining whether a model is within a threshold range; and in response to a determination that the output is not within a threshold range, dynamically recalibrating the model to fit the model within the threshold range.

Clause 7, the computer-implemented method of any of clauses 1 to 5, further comprising: determining whether a model is within a threshold range; and in response to a determination that the output is not within a threshold range, requesting a manual recalibration of the model.

Clause 8, the computer implemented method according to any of clauses 1 to 7, wherein the data and the new data comprise data indicative of at least one of a flow rate, a pressure and of a derivative of the pressure over time at the location.

Clause 9, the computer-implemented method according to any of clauses 1 to 8, further comprising: determining a change in a coefficient of the model; and in response to a determination that the change is greater than a threshold value, dynamically recalibrating the model in real time.

Clause 10, the computer-implemented method of any of clauses 1 to 9, further comprising: projecting a first flow rate at a wellhead based on the model; determining a second flow rate which is measured at the wellhead; comparing the first flow rate and the second flow rate; and in response to a determination that the first flow rate and the second flow rate vary by more than a threshold; dynamic recalibration of the model in real time; and calculating an updated fluid flow of the fluid flowing through the well location based on the recalibrated model.

Clause 11, the computer-implemented method of any of clauses 1 to 10, further comprising: projecting a first pressure at a wellhead based on the model; determining a second pressure which is measured at the wellhead; and in response to a determination that the first pressure and the second pressure vary by more than a threshold; dynamic recalibration of the model in real time; and calculating an updated fluid flow of the fluid flowing through the well location based on the recalibrated model.

Clause 12, the computer-implemented method of any of clauses 1 to 11, further comprising: analyzing the data and previously received data from the plurality of sensors for a pattern associated with fluid flow fluid; determining a change in pattern associated with fluid flow; and in response to a determination that the change in the pattern is greater than a threshold, dynamically recalibrating the model in real time.

Clause 13, the computer-implemented method of any of clauses 1 to 12, further comprising: determining a flow direction of fluid flowing through the well location based on the model ; and in response to receipt of new data: dynamic recalibration of the model in real time based on the new data; and determining the flow direction of fluid flowing through the well location based on the recalibrated model.

Clause 14, the computer-implemented method according to any of clauses 1 to 13, further comprising: predicting fluid flow of the fluid during a threshold time period based on the model; and in response to receiving the new data, predicting fluid flow of the fluid during the threshold time period based on the new data.

Clause 15, the computer-implemented method of any of clauses 1 to 14, wherein the properties of one or more hardware components of the well are parameters of the plurality of parameters, and wherein filling the well model with data includes filling the well model based on the properties of one or more hardware components.

Clause 16, the computer-implemented method of any of clauses 1 to 15, further comprising: after recalibrating the model, comparing the model with a digital twin of the well; and in response to determining that a property of the model and a corresponding property of the digital twin vary by a threshold range, updating the digital twin based on the model.

Clause 17, the computer-implemented method of any of clauses 1 to 16, wherein calculating the fluid flow includes calculating a flow rate of a hydrocarbon resource at the location , and wherein calculating the updated fluid flow includes calculating the updated flow rate of the hydrocarbon resource at the location.

Clause 18, the computer-implemented method of any of clauses 1 to 17, further comprising: calculating a fluid flow map of fluid flow through a section of the well; and in response to receiving new streamed data from the one or more sensors of the plurality of sensors: calculating an updated fluid flow map of the fluid flow through the section of the well.

Clause 19, a computer implemented method for performing real-time analysis of a well operation, comprising: determining, based on data streamed from a plurality of sensors disposed in a well, a presence of defective hardware disposed in the well, wherein the data is associated with a plurality of parameters of a model of a well, the model being a digital twin of the well; determining whether a property of the model is within a threshold range; and in response to a determination that the model is not within the threshold range: determining an improvement in the property of the model; and dynamically recalibrating the model in real time based on the data streamed from the plurality of sensors to improve the property of the model.

Clause 20, the computer-implemented method of clause 19, wherein determining the presence of the defective hardware comprises determining, based on data streamed from the plurality of sensors over a period of time, the presence of defective equipment.

Clause 21, the computer implemented method according to clauses 19 or 20, further comprising predicting, based on the model, a fluid flow of a fluid flowing through the well during a threshold period of time.

Clause 22, the computer implemented method of any of clauses 19 to 21, further comprising: performing a fluid flow simulation of a fluid flowing through the well to determine a improving fluid flow of the fluid; determining an improvement to an existing hardware configuration to improve fluid flow of the fluid; and providing a recommendation for reconfiguring the hardware.

Clause 23, a real-time well operations system, comprising: a storage medium; and one or more processors configured to: receive streamed data simultaneously from a plurality of sensors disposed in a well; populate a model of the well with the data, wherein the model includes a plurality of parameters that are inputs to the model, and wherein each parameter of the plurality of parameters is associated with data streamed continuously from a sensor of the plurality of sensors; calculating a fluid flow of a fluid flowing through a location of the well based on the model; and in response to receiving new streamed data from one or more of the plurality of sensors: dynamically recalibrating the model in real time based on the new data; and calculating an updated fluid flow of the fluid flowing through the well location based on the recalibrated model.

Clause 24, the real-time well operations system according to clause 23, wherein the one or more processors are further configured to: determine a change in one of the plurality of parameters over a period of time ; and dynamically recalibrating the model in real time based on the change in the parameter over the time period.

As used herein, the singular forms "a", "an" and "the" or "the" are intended to also include the plural forms, unless the context clearly indicates otherwise. It will further be understood that the terms "include" and/or "comprising", when used in this description and/or in the claims, specify the presence of features, steps, operations, elements and /or components presented, but do not exclude the presence or addition of one or more other characteristics, steps, operations, elements, components and/or groups thereof. Additionally, the steps and components described in the above embodiments and figures are merely illustrative and do not imply that any particular step or component is a requirement of a claimed embodiment.

Claims (15)

A computer implemented method for performing real-time analysis of fluid flow in a well, comprising:
receiving streamed data simultaneously from a plurality of sensors disposed in a well;
populating a model of the well with the data, wherein the model includes a plurality of parameters that are inputs to the model, and wherein each of the plurality of parameters is associated with data streamed from one sensor of the plurality of sensors;
calculating a fluid flow of a fluid flowing through a location of the well based on the model; And
in response to receiving new streaming data from one or more of the plurality of sensors:
dynamic recalibration of the model in real time based on new data; And
calculating an updated fluid flow of the fluid flowing through the well location based on the recalibrated model. The computer-implemented method of claim 1, wherein filling the model includes filling the model while data is streamed simultaneously from the plurality of sensors, and wherein calculating fluid flow includes calculating fluid flow while the data is streamed simultaneously from the plurality of sensors, and optionally, wherein calculating fluid flow of the fluid flowing through the location includes calculating fluid flow through the location before the data is stored on a storage medium, and wherein calculating updated fluid flow of fluid flowing through the location includes calculating the fluid flow of the fluid flowing through the location before the updated data is stored on the storage medium, and optionally, wherein, in response to receiving the new data, the method further comprising:
determining a change in a parameter of the plurality of parameters over a period of time; And
dynamic recalibration of the model in real time based on the change in the parameter over the time period, and optionally,
wherein, in response to receiving the new data, the method further comprising:
determining a change in a characteristic of fluid flow over a period of time; And
dynamic recalibration of the model in real time based on the change in the fluid flow characteristic over the time period. The computer-implemented method of claim 1 further comprising:
determining whether a model is within a threshold range; And
in response to a determination that the output is not within a threshold range, dynamically recalibrating the model to fit the model within the threshold range. The computer-implemented method of claim 1 further comprising:
determining whether a model is within a threshold range; And
in response to a determination that the output is not within a threshold range, requesting a manual recalibration of the model. A computer-implemented method according to claim 1, wherein the data and the new data include data indicative of at least one of a flow rate, a pressure and a pressure derivative over time at the location level. The computer-implemented method of claim 1 further comprising:
determining a change in a coefficient of the model; And
in response to a determination that the change is greater than a threshold value, dynamically recalibrating the model in real time. The computer-implemented method of claim 1 further comprising:
projecting a first flow rate at a wellhead based on the model;
determining a second flow rate which is measured at the wellhead;
comparing the first flow rate and the second flow rate; And
in response to a determination that the first flow rate and the second flow rate vary by more than a threshold;
dynamic recalibration of the model in real time; And
calculating an updated fluid flow of the fluid flowing through the well location based on the recalibrated model. The computer-implemented method of claim 1 further comprising:
projecting a first pressure at a wellhead based on the model;
determining a second pressure which is measured at the wellhead; And
in response to a determination that the first pressure and the second pressure vary by more than a threshold;
dynamic recalibration of the model in real time; And
calculating an updated fluid flow of the fluid flowing through the well location based on the recalibrated model. The computer-implemented method of claim 1 further comprising:
analyzing the data and the data previously received from the plurality of sensors for a pattern associated with fluid flow of the fluid;
determining a change in pattern associated with fluid flow; And
in response to a determination that the change in the pattern is greater than a threshold, dynamically adjusting the pattern in real time. The computer-implemented method of claim 1 further comprising:
determining a flow direction of the fluid flowing through the well location based on the model; And
in response to receiving new data:
dynamic recalibration of the model in real time based on new data; And
determining the flow direction of fluid flowing through the well location based on the recalibrated model; and optionally, further comprising:
predicting fluid flow of the fluid during a threshold time period based on the model; And
in response to receiving the new data, predicting fluid flow of the fluid over the threshold time period based on the new data, and optionally, wherein the properties of one or more material components of the wells are parameters of the plurality of parameters, and wherein filling the model of the well with the data includes filling the model of the well based on the properties of the one or more hardware components. The computer-implemented method of claim 1 further comprising:
after recalibrating the model, comparing the model with a digital twin of the well;
in response to determining that a property of the model and a corresponding property of the digital twin vary by a threshold range, updating the digital twin based on the model. The computer-implemented method of claim 1, wherein calculating the fluid flow includes calculating a flow rate of a hydrocarbon resource at the location, and wherein calculating the flow Updated Fluid Flow includes calculating the updated flow rate of the hydrocarbon resource at the location. The computer-implemented method of claim 1 further comprising:
calculating a fluid flow map of fluid flow through a section of the well; And
in response to receiving new streaming data from the one or more sensors of the plurality of sensors:
calculating an updated fluid flow map of fluid flow through the well section. Real-time well operations system, including:
a storage medium; And
one or more processors configured to:
receive streamed data simultaneously from a plurality of sensors disposed in a well;
populate a model of the well with the data, wherein the model includes a plurality of parameters that are inputs to the model, and wherein each of the plurality of parameters is associated with data streamed from a well sensor the plurality of sensors;
calculating a fluid flow of a fluid flowing through a location of the well based on the model; And
in response to receiving new streaming data from one or more of the plurality of sensors:
dynamically recalibrate the model in real time based on new data; And
calculate an updated fluid flow of the fluid flowing through the well location based on the recalibrated model. The real-time well operations system of claim 14, wherein the one or more processors are further configured to:
determining a change in a parameter of the plurality of parameters over a period of time; And
dynamically recalibrate the model in real time based on the change in the parameter over the time period.