Integrated autonomous operation for injection-production analysis and parameter selection

Abstract

An integrated autonomous operating system integrally renders multiple scales of operations in digital form, including reservoirs, ground infrastructure, workflows, processes, and actual assets. The system provides an end-to-end digital twin connecting underground and production. The subsurface model identifies and monitors the water producing zone in order to make strategic decisions. The model uses an intelligent AI to provide an optimal water injection setpoint. The model provides data to a system that automatically controls throttle and valves to meet the setpoint, thus achieving fully integrated autonomous operation.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Patent Application No. 63 / 376,147, filed on September 19, 2022, entitled “Integrated Automatic Operations for Injection-Production Analysis and Parameter Selection,” the entire contents of which are incorporated herein by reference. Background Art

[0003] The oil and gas industry has various technologies for evaluating options / plans in an oil and gas environment and deciding parameters in a quantifiable manner. However, oilfield operations are often complex, and therefore such evaluation / enhancement technologies are often provided for individual tasks or even parts of tasks within individual domain silos. Due to the complexity of operations and the limitations of fragmented technologies, implementing an integrated system of autonomous solutions remains a particular challenge. Therefore, full-scale numerical modeling software and analytical modeling spreadsheets using real-time, digital monitoring and data collection are often employed. However, such solutions do not provide an integrated automated system.

[0004] Challenges to achieving such autonomous operational processing include: (1) lack of integration between various disciplines such as reservoir models, production systems, production facilities, and operational control; (2) isolated processing where each domain selects parameters within its domain constraints and lacks domain integration for operational decision making; (3) lack of feedback loops between tactical and operational tools, resulting in reactive rather than proactive operational decisions; and (4) lack of automation and integration between, for example, production monitoring and reservoir models. Summary of the invention

[0005] A system of one or more computers may be configured to perform specific operations or actions by installing software, firmware, hardware, or a combination thereof on the system, which in operation causes the system to perform actions. One or more computer programs may be configured to perform specific operations or actions by including instructions that, when executed by a data processing device, cause the device to perform actions. One general aspect includes a method for autonomously performing subsurface operations. The method also includes: determining real-time data associated with the underground operation; constructing a first model based at least on the real-time data, wherein the first model includes a first set of elements, wherein the first set of elements includes a first subset of features from the design of the underground operation; calculating a target for the underground operation using the first model; updating the first model based at least on the calculated target; setting an operation set point based at least on the calculated target; managing production based at least on the operation set point; constructing a second model based at least on the real-time data, wherein the second model includes a second set of elements, wherein the second set of elements includes a second subset of features from the design of the underground operation, wherein the first set of elements is smaller than the second set of elements; adjusting a preselected second set of elements to match historical data associated with the underground operation; optimizing the second set of elements for the underground operation; and determining an oilfield development plan associated with the underground operation based at least on the second model. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each of which is configured to perform the actions of the method.

[0006] Implementations may include one or more of the following features. The method may include: validating a first model, wherein the validation includes ensuring that the first model meets a threshold for performance. The method may also include: continuing to build the first model if the first model does not meet the threshold. The method may also include: using the first model to calculate a target for an underground operation if the first model meets the threshold. The method may also include: optimizing the calculated target for the underground operation. The method may also include: receiving electronic communications from a device associated with the underground operation. The electronic communications include real-time remote operations and asset information, the electronic communications include desired settings associated with the underground operation, the devices include edge and Internet of Things (IOT) devices, and the electronic communications are received by a platform that processes data from the edge and Internet of Things devices and from one or more processors. The method may also include: providing an operating set point to the platform as a desired setting. The method may include: designing a surface facility associated with the underground operation based at least on the second model, and determining an underground operation target based at least on the second model. The real-time data may include: pressure, virtual flow, and equipment status. Implementations of the technology may include hardware, methods or processes, or computer software on a computer-accessible medium.

[0007] A general aspect includes a computing system for autonomously performing subsurface operations. The computing system also includes one or more processors; and the memory system may include one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations that may include: receiving an electronic communication from a device associated with the subsurface operation; determining real-time data based on the received electronic communication; constructing a first model based at least on the real-time data, wherein the first model includes a first set of elements, wherein the first set of elements includes a first subset of features from a design for the subsurface operation; validating the first model, wherein the validation includes ensuring that the first model meets a threshold for performance; if the first model meets the threshold, calculating a target for the subsurface operation using the first model; updating the first model based at least on the calculated target; setting an operation set point based at least on the calculated target. The system also includes providing the operation set point to a platform as a desired setting. The system also includes: managing production based at least on the operation set point; constructing a second model based at least on the real-time data; adjusting a preselected second set of elements to match historical data associated with the subsurface operation; optimizing the second set of elements for the subsurface operation. The system also includes determining a field development plan associated with the subsurface operation based at least on the second model. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the method. Implementations of the technology may include hardware, methods or processes, or computer software on a computer accessible medium. Another general aspect includes a non-transitory computer readable medium storing instructions for autonomously performing subsurface operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate the present teachings and, together with the described embodiments, serve to explain the principles of the present teachings. In the drawings:

[0009] Figure 1 An example of a system including various management components for managing various aspects of a geological environment is shown according to an embodiment.

[0010] Figure 2 An integrated autonomous operations analysis and parameter selection framework according to an embodiment is shown.

[0011] Figure 3 An integrated autonomous operations use case for waterflood analysis and parameter selection according to an embodiment is shown.

[0012] Figure 4A , Figure 4B and Figure 4C is a flow chart of an exemplary method according to the present disclosure.

[0013] Figure 5 A schematic diagram of a computing system according to an embodiment is shown. DETAILED DESCRIPTION

[0014] Reference will now be made in detail to the embodiments, examples of which are shown in the accompanying drawings. In the following detailed description, many specific details are set forth to provide a deeper understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that the present invention may be practiced without these specific details. In other examples, known methods, procedures, components, circuits, and networks are not described in detail to avoid unnecessarily obscuring aspects of the embodiments.

[0015] It should also be understood that, although the terms first, second, etc. can be used to describe various elements in this article, these elements should not be limited to these terms. These terms are only used to distinguish one element from another element. For example, without departing from the scope of the present disclosure, the first object or step can be referred to as the second object or step, and similarly, the second object or step can be referred to as the first object or step. The first object or step and the second object or step are both objects or steps, respectively, but they should not be considered as the same object or step.

[0016] The terms used in this specification are for the purpose of describing a specific embodiment and are not intended to be limiting. As used in this specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "said" are also intended to include plural forms. It will also be understood that the term "and / or" as used herein refers to and covers any possible combination of one or more of the associated listed items. It will also be understood that the term "includes, including, comprises and / or comprising" specifies the presence of the features, integers, steps, operations, elements and / or parts when used in this specification, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or their groups. In addition, as used herein, the term "if" can be interpreted as meaning "at the time of", "after..." or "in response to determination" or "in response to detection", which depends on the background.

[0017] Attention is now directed to processes, methods, techniques, and workflows according to some embodiments.Some operations in the processes, methods, techniques, and workflows disclosed herein may be combined and / or the order of some operations may be changed.

[0018] Figure 1An example of a system 100 is shown that includes various management components 110 for managing various aspects of a geological environment 150 (e.g., an environment including a sedimentary basin, a reservoir 151, one or more faults 153-1, one or more geological bodies 153-2, etc.). For example, the management components 110 may allow for direct or indirect management of sensing, drilling, injection, extraction, etc., regarding the geological environment 150. In turn, additional information regarding the geological environment 150 may become available as feedback 160 (e.g., optionally as input to one or more of the management components 110).

[0019] exist Figure 1 In the example of FIG. 1 , the management component 110 includes a seismic data component 112, an additional information component 114 (e.g., well / log data), a processing component 116, a simulation component 120, a property component 130, an analysis / visualization component 142, and a workflow component 144. In operation, the seismic data and other information provided by components 112 and 114 may be input to the simulation component 120.

[0020] In an example embodiment, simulation component 120 may rely on entity 122. Entity 122 may include earth entities or geological objects, such as wells, ground, bodies, reservoirs, etc. In system 100, entity 122 may include a virtual representation of an actual physical entity reconstructed for the purpose of simulation. Entity 122 may include an entity based on data collected via sensing, observation, etc. (e.g., seismic data 112 and / or other information 114). An entity may be characterized by one or more properties (e.g., a geometric pillar grid entity of an earth model may be characterized by a porosity property). Such properties may represent one or more measurements (e.g., collected data), calculations, etc.

[0021] In an example embodiment, simulation component 120 may operate in conjunction with a software framework such as an object-based framework. In such a framework, entities may include entities based on predefined classes to facilitate modeling and simulation. Commercial examples of object-based frameworks are Framework (Redmond, Washington), an object-based framework that provides a set of extensible object classes. In the framework, object classes encapsulate modules of reusable code and associated data structures. Object classes can be used to instantiate object instances for use by programs, scripts, etc. For example, the borehole class can define an object for representing a borehole based on well data.

[0022] exist Figure 1In an example, simulation component 120 can process information to conform to one or more attributes specified by attribute component 130, which can include an attribute library. Such processing can occur prior to input to simulation component 120 (e.g., consider processing component 116). As an example, simulation component 120 can perform operations on input information based on one or more attributes specified by attribute component 130. In an example embodiment, simulation component 120 can construct one or more models of geological environment 150, which can be relied upon to simulate the behavior of geological environment 150 (e.g., in response to one or more behaviors, whether natural or artificial). Figure 1 In the example of , the analysis / visualization component 142 can allow interaction with the model or model-based results (e.g., simulation results, etc.). As an example, the output from the simulation component 120 can be input into one or more other workflows, as indicated by the workflow component 144.

[0023] As an example, the analog component 120 may include a TM Reservoir Simulator (Schlumberger Limited, Houston Texas), INTERSECT TM One or more features of a simulator such as a reservoir simulator (Schlumberger Limited, Houston Texas). As an example, a simulation component, a simulator, etc. may include features for implementing one or more gridless techniques (e.g., for solving one or more equations, etc.). As an example, one or more reservoirs may be simulated with respect to one or more enhanced recovery techniques (e.g., considering thermal processes such as SAGD, etc.).

[0024] In an example embodiment, the management component 110 may include, for example, Features of commercially available frameworks such as the Earthquake to Simulation software framework (Schlumberger Limited, Houston, TX). The framework provides components that allow optimization of exploration and production operations. The framework includes a seismic-to-simulation software component that can output information for improving reservoir performance, such as by increasing asset team productivity. Using such a framework, various professionals (e.g., geophysicists, geologists, and reservoir engineers) can develop collaborative workflows and integrate operations to streamline processes. Such a framework can be considered an application and can be considered a data-driven application (e.g., where data is input for the purpose of modeling, simulation, etc.).

[0025] In an example embodiment, various aspects of the management component 110 may include add-ons or plug-ins that operate according to the specifications of the framework environment. The commercially available framework environment (Schlumberger Limited, Houston, Texas) allows add-ons (or plug-ins) to be integrated into Framework workflow. Framework environment utilization Tools (Microsoft Corporation, Redmond, Washington), and provide a stable user-friendly interface for efficient development. In an example embodiment, the various components can be implemented as add-ons (or plug-ins) that conform to the specifications of the framework environment and operate according to the specifications of the framework environment (e.g., according to application programming interface (API) specifications, etc.).

[0026] Figure 1 Also shown is an example of a framework 170, which includes a model simulation layer 180 and a framework service layer 190, a framework core layer 195, and a module layer 175. The framework 170 may include commercially available framework, in which the model simulation layer 180 is hosted Applications are commercially available with Model-centric software packages. In an example implementation, Software can be thought of as data-driven applications. The software may include a framework for model building and visualization.

[0027] As an example, a framework may include features for implementing one or more grid generation techniques. For example, a framework may include an input component for receiving information from an interpretation of seismic data, based at least in part on one or more attributes of seismic data, well log data, image data, etc. Such a framework may include a grid generation component that processes the input information, optionally in conjunction with other information, to generate a grid.

[0028] exist Figure 1 In the example of , model simulation layer 180 can provide domain objects 182, act as a data source 184, provide rendering 186, and provide various user interfaces 188. Rendering 186 can provide a graphical environment in which an application can display its data, while user interface 188 can provide a common look and feel for application user interface components.

[0029] As an example, domain objects 182 may include entity objects, property objects, and optionally other objects. Entity objects may be used to geometrically represent wells, ground, bodies, reservoirs, etc., while property objects may be used to provide property values ​​as well as data versions and display parameters. For example, an entity object may represent a well, where the property object provides well logging information as well as version information and display information (e.g., displaying the well as part of a model).

[0030] exist Figure 1 In the example of , data can be stored in one or more data sources (or data stores, typically physical data storage devices), which can be located at the same or different physical sites and can be accessed via one or more networks. The model simulation layer 180 can be configured to model a project. Therefore, a specific project can be stored, where the stored project information can include inputs, models, results, and cases. Therefore, when a modeling session is completed, the user can store the project. Later, the project can be accessed and restored using the model simulation layer 180, which can recreate instances of related domain objects.

[0031] exist Figure 1 In the example of, the geological environment 150 may include layers (e.g., strata) that include a reservoir 151 and one or more other features, such as a fault 153-1, a geological body 153-2, and the like. As an example, the geological environment 150 may be equipped with any of a variety of sensors, detectors, actuators, and the like. For example, equipment 152 may include communication circuits to receive and transmit information about one or more networks 155. Such information may include information associated with downhole equipment 154, which may be equipment for collecting information, assisting in resource extraction, and the like. Other equipment 156 may be located remote from the well site and include sensing, detection, transmission, or other circuits. Such equipment may include storage and communication circuits for storing and transmitting data, instructions, and the like. As an example, one or more satellites may be provided for purposes of communication, data collection, and the like. For example, Figure 1 A satellite is shown in communication with a network 155 that may be configured for communications, noting that the satellite may additionally or alternatively include circuitry for imaging (eg, spatial, spectral, temporal, radiometric, etc.).

[0032] Figure 1The geological environment 150 is also shown as optionally including equipment 157 and 158 associated with a well, the well including a substantially horizontal portion that may intersect one or more fractures 159. For example, consider a well in a shale formation, the shale formation may include natural fractures, artificial fractures (e.g., hydraulic fractures), or a combination of natural fractures and artificial fractures. As an example, a laterally extending reservoir may be drilled. In such an example, there may be lateral changes in properties, stresses, etc., where an assessment of such changes may help plan, operate, etc. to develop a laterally extending reservoir (e.g., via fracturing, injection, extraction, etc.). As an example, equipment 157 and / or 158 may include components, one or more systems, etc., for fracturing, seismic sensing, seismic data analysis, assessment of one or more fractures, etc.

[0033] As described above, the system 100 can be used to execute one or more workflows. A workflow can be a process that includes several work steps. The work steps can operate on data, for example, create new data, update existing data, etc. As an example, a workflow can operate on one or more inputs and create one or more results, for example, based on one or more algorithms. As an example, the system can include a workflow editor for creating, editing, executing, etc. a workflow. In such an example, the workflow editor can provide a selection of one or more predefined work steps, one or more custom work steps, etc. As an example, a workflow can be a workflow that can be executed in a certain manner. A workflow implemented in software, for example, the workflow operates on seismic data, one or more seismic attributes, etc. As an example, a workflow may be available in A process implemented in a framework. As an example, a workflow may include one or more work steps that access modules such as plug-ins (eg, external executable code, etc.).

[0034] Embodiments of the present disclosure can provide an integrated autonomous operating system, such as a system that renders operations of multiple scales in digital form as a whole, including reservoirs, surface infrastructure, workflows, processes, and real assets. Overall, the system provides an end-to-end digital twin that connects the subsurface and production. The system uses a field development plan (FDP) model to define analysis and enhancement plans under constraints, and uses a subsurface model to identify and monitor water-producing areas in order to make strategic decisions. The tactical system uses an intelligent AI model to provide optimal water injection set points. In some embodiments, the model provides data to a system that automatically controls throttles and valves to meet set points, thereby achieving fully integrated autonomous operation.

[0035] At least some embodiments may include a decision support system. For example, a decision support system may integrate functionality from several different areas. Such areas may include, for example, asset management, monitoring and diagnostics, opportunity management, reservoir modeling, and field analysis and enhancement. The integration of these areas may create an autonomous system for injection and production parameter selection.

[0036] The decision support system focuses on injection and production parameter selection in the tactical and operational decision space, and can continuously monitor reservoir conditions and enhance injection to desired reservoir areas to improve (e.g., increase) production. The system can utilize data-driven and artificial intelligence (AI) models that automatically calculate and provide new set points for control systems of throttles, valves, or other equipment, such as creating automatic closed-loop operational feedback.

[0037] The system may include various workflows that cover multiple tasks and create intelligent, actionable insights to automatically control the injection system to increase production. Integrated autonomous injection-production balance is a complex process that may require the integration of various domains. It can be applied to many secondary and tertiary oil recovery mechanisms such as water injection, gas injection, chemical injection, etc. The system can be used to enhance oil recovery. Such improvements can be achieved through "void replacement", which may refer to injection to maintain reservoir pressure at the desired operating level and / or by diverting hydrocarbons to production wells.

[0038] Figure 2 An example of water injection is shown, where multiple domain technologies are incorporated to achieve an integrated autonomous water injection operation. However, the same concepts can be applied to other injection scenarios, such as gas injection, chemical injection, and steam injection.

[0039] The system starts with a field development plan 201, where strategic decisions are defined, and a techno-economic analysis is performed on asset management decisions 203. The production data is fed into a database and managed by software platforms such as the Tool extraction to perform data-driven diagnostics and hybrid data-physics-driven models for opportunity management decisions 207.

[0040] The production data of the relevant time can be updated by automatic model updating tools (e.g., INTERS and / or ) is fed to the reservoir modeling tool 209 and used for tactical decision making. This combination of techniques (machine learning, hybrid and potential failure mode analysis) has the potential to operate together with the numerical reservoir model 209 that also uses potential failure mode analysis and provide the best data-driven and model-driven approach for operational decision support and will be used for oil field enhancement decisions 211. The results of this hybrid model (such as new set points and target injection rates) are passed to The system can be implemented in oilfield operations. The edge / IOT system can be used to automatically control throttles and valves to meet set points, thus achieving fully integrated autonomous operations. The results can be used by conventional oilfield development planning systems to analyze new tactical development plans and strategic development plans.

[0041] Reference now Figure 3 , the logic of the autonomous water injection management system includes processes, workflows, and advisory systems operating on strategic, tactical, and operational decision spaces. The figure also shows an automatic closed-loop operational feedback system 305 between the operational decision space and the tactical decision space. It also emphasizes how strategic models and decision systems, which play a key role in developing long-term strategies, provide feedback for tactical decisions. According to the example, Figure 4A and Figure 4B A workflow illustrating the application of this method is shown in .

[0042] exist Figure 3 In the embodiment, production and / or injection data 303 and completion location information from, for example, but not limited to, a database 315 are used to build and calibrate a machine learning-assisted hybrid model 307 / 309. Once the model is calibrated, it can be used in a workflow. There are a variety of conditions that can trigger an update 305 / 317 of the model to better reflect the measured real-world conditions. The performance of the oil field and wells can be monitored and set points can be found to improve performance or recommend remedial actions. Decision support in this embodiment is enhanced through multi-domain integration, that is, an integrated approach to parameter analysis and selection is taken, rather than an isolated approach, and automated insights are provided for proactive operational responses, thereby providing opportunities for fully autonomous operations.

[0043] Figure 4A and Figure 4B A flow chart of a method 400 for autonomously performing subsurface operations according to an embodiment is shown. An illustrative order for the method 400 is provided below; however, one or more portions of the method 400 may be performed in a different order, performed simultaneously, repeated, or omitted.

[0044] The method 400 may include receiving electronic communications from devices associated with the underground operation, as at 402. The electronic communications may include real-time remote operation and asset information. The electronic communications may include desired settings associated with the underground operation. The devices may include edge and Internet of Things (IoT) devices. The electronic communications may be received by a platform that processes data from edge and IoT devices and from one or more processors.

[0045] The method may also include determining real-time data from the received communication, as at 404. The real-time data may include pressure, virtual flow, equipment status, or a combination thereof.

[0046] Method 400 may also include building a first model based at least on the real-time data, as at 406. The first model may include a first set of elements. The first set of elements may include a first subset of features from a subsurface operation design. The design may include a field development plan, surface facilities, subsurface operation objectives, or a combination thereof.

[0047] Method 400 may also include validating the first model, as at 408. Validation may include ensuring that the first model meets a performance threshold.

[0048] Method 400 may also include continuing to construct the first model if the first model does not satisfy the threshold, as at 410 .

[0049] The method 400 may also include calculating a target for a subsurface operation using the first model if the first model satisfies the threshold, as at 412. The target may include a production target and / or an injection target.

[0050] The method 400 may also include optimizing the calculated objective of the subsurface operation, as at 414 .

[0051] The method 400 may also include updating the first model based at least on the optimized computational objective, as at 416 .

[0052] Method 400 may also include setting an operating set point based at least on the optimized calculated objective, as at 418 .

[0053] The method 400 may also include providing the operating set point to the platform as a desired setting, as at 420 .

[0054] The method 400 may also include managing production based at least on the operating set point, as at 422 .

[0055] The method 400 may also include constructing a second model based at least on the real-time data, as at 424. The second model may include a second set of elements. The second set of elements may include a second subset of features from the design of the underground operation. The first set of elements may be smaller than the second set of elements.

[0056] Method 400 may also include adjusting the pre-selected set of the second elements to match historical data associated with the subterranean operation, as at 426 .

[0057] The method 400 may also include optimizing the second set of elements for subsurface operations, as at 428 .

[0058] The method 400 may also include determining a field development scenario associated with the subsurface operation based at least on the second model, as at 430. The field development scenario may include the number of assets, asset types, asset locations, field production levels of assets, results of drilling of evaluation wells, or a combination thereof. The determination may include performing a technical analysis on the subsurface operation and performing an economic analysis on the subsurface operation.

[0059] Method 400 may also include designing surface facilities associated with the underground operation based at least on the second model, as at 432. The surface facilities may include above-ground appurtenances, structures, equipment, storage fixtures, processing fixtures, or combinations thereof.

[0060] The method 400 may also include determining a subsurface operational target based at least on the second model, as at 434. The subsurface operational target may include a target category, a target location, a target shape, a target boundary, a target feature, or a combination thereof associated with the subsurface operational target. The target feature may include a target borehole, a target category, a target coordinate system, or a combination thereof.

[0061] The method 400 also includes performing a wellsite action, as at 436. The wellsite action may be performed based on the second model, the (e.g., optimized) second set of elements, the field development plan, or a combination thereof. The wellsite action may be or include generating and / or transmitting a signal (e.g., using a computing system) that causes a physical action to occur at the wellsite. The wellsite action may also or alternatively include performing a physical action at the wellsite. The physical action may be or include selecting where to drill a well, drilling a well, changing the weight and / or torque of a drill bit for drilling a well, changing the drilling trajectory of a well, changing the concentration and / or flow rate of a fluid pumped into a well, and the like.

[0062] In some embodiments, the methods of the present disclosure may be performed by a computing system. Figure 5An example of such a computing system 500 is shown according to some embodiments. The computing system 500 may include a computer or computer system 501A, which may be a separate computer system 501A or an arrangement of distributed computer systems. According to some embodiments, the computer system 501A includes one or more data receiving and processing modules 502, which are configured to perform various tasks, such as one or more methods disclosed herein. To perform these various tasks, the data receiving and processing modules 502 execute independently or in coordination with one or more processors 504, which are connected to one or more storage media 506. The one or more processors 504 are also connected to a network interface 507 to allow the computer system 501A to communicate with one or more additional computer systems and / or computing systems (such as 501B, 501C and / or 501D) via a data network 509 (it should be noted that computer systems 501B, 501C and / or 501D may or may not share the same architecture as computer system 501A and may be located in different physical locations, for example, computer systems 501A and 501B may be located in a processing facility while communicating with one or more computer systems (such as 501C and / or 501D) located in one or more data centers and / or in different countries on different continents).

[0063] A processor may include a microprocessor, a microcontroller, a processor module or subsystem, a programmable integrated circuit, a programmable gate array, or another control or computing device.

[0064] The storage medium 506 may be implemented as one or more computer-readable or machine-readable storage media. Figure 5 In the example embodiment of the storage medium 506 is depicted as being within the computer system 501A, but in some embodiments, the storage medium 506 can be distributed within and / or across multiple internal and / or external enclosures of the computing system 501A and / or additional computing systems. The storage medium 506 may include one or more different forms of memory, including semiconductor memory devices, such as dynamic or static random access memory (DRAM or SRAM), erasable and programmable read-only memory (EPROM), electrically erasable and programmable read-only memory (EEPROM), and flash memory; magnetic disks, such as fixed disks, floppy disks, and removable disks; other magnetic media, including magnetic tape, optical media (such as compact disks (CDs) or digital video disks (DVDs), disk or other type of optical storage medium); or other type of storage device. It should be noted that the instructions discussed above may be provided on one computer-readable or machine-readable storage medium, or may be provided on multiple computer-readable or machine-readable storage media distributed in a large system that may have multiple nodes. Such one or more computer-readable or machine-readable storage media are considered to be part of an article (or product). An article or product may refer to a single component or multiple components of any manufacture. One or more storage media may be located in the machine running the machine-readable instructions, or at a remote site from which the machine-readable instructions can be downloaded over a network for execution.

[0065] In some embodiments, computing system 500 includes one or more subsurface operation modules 508. In the example of computing system 500, computer system 501A includes subsurface operation module 508. In some embodiments, a single subsurface operation module can be used to perform some aspects of one or more embodiments of the methods disclosed herein. In other embodiments, multiple subsurface operation modules can be used to perform some aspects of the methods herein.

[0066] It should be understood that computing system 500 is only one example of a computing system, and computing system 500 may have more or fewer components than shown, may be combined Figure 5 Additional components not depicted in the example embodiment of FIG. 5 and / or computing system 500 may have Figure 5 Different configurations or arrangements of the components depicted in . Figure 5 The various components shown in the drawings may be implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and / or application specific integrated circuits.

[0067] In addition, the steps in the processing method described herein can be implemented by running one or more functional modules in an information processing device (such as a general-purpose processor or a dedicated chip (such as an ASIC, FPGA, PLD or other suitable device). These modules, combinations of these modules and / or their combination with general hardware are included in the scope of the present disclosure.

[0068] The computational interpretation, model, and / or other interpretation aids may be optimized in an iterative manner; this concept may be applicable to the methods discussed herein. This may include the use of a feedback loop that is based on an algorithm (such as on a computing device (e.g., computing system 500, Figure 5 ) and / or by manual control of a user who can make a determination as to whether a given step, action, template, model, or set of curves is sufficient to accurately evaluate the subsurface three-dimensional geological construct under consideration.

[0069] For the purpose of explanation, the foregoing description has been described with reference to specific embodiments. However, the above illustrative discussion is not intended to be exhaustive or limited to the precise form disclosed. In view of the above teachings, there may be many modifications and changes. In addition, the order of the elements of the method described herein can be rearranged, and / or two or more elements can occur simultaneously. The embodiments are selected and described in order to best explain the principles of the present disclosure and their practical application, so that other technical personnel in the field can best utilize the disclosed embodiments and various embodiments with various modifications suitable for the intended specific use. In the following claims, for U.S. patent applications, Section 112, paragraph 6, will not be cited unless the phrase "device for..." is used.

Claims

1. A method for autonomously performing underground operations, the method comprising: determining real-time data associated with the subsurface operation; constructing a first model based at least on the real-time data, wherein the first model includes a first set of elements, wherein the first set of elements includes a first subset of features from a design of the subterranean operation; calculating a target for the subsurface operation using the first model; setting an operating set point based at least on the calculated target; managing production based at least on the operating set point; constructing a second model based at least on the real-time data, wherein the second model includes a second set of elements, wherein the second set of elements includes a second subset of features from the design of the subterranean operation, wherein the first set of elements is smaller than the second set of elements; adjusting a preselected set of said second elements to match historical data associated with said underground operation; optimizing said second set of elements of said subsurface operation; as well as A field development plan associated with the subsurface operation is determined based at least on the second model.

2. The method of claim 1, further comprising: The first model is validated, wherein the validation includes ensuring that the first model meets a performance threshold.

3. The method according to claim 1 or 2, further comprising: If the first model does not meet the threshold, continue to build the first model.

4. The method of any one of claims 1 to 3, further comprising: If the first model satisfies the threshold, a target for the subsurface operation is calculated using the first model.

5. The method according to any one of claims 1 to 4, further comprising: The calculated objective of optimizing the subsurface operation.

6. The method according to any one of claims 1 to 5, further comprising: An electronic communication is received from a device associated with the underground operation.

7. A method as described in any one of claims 1 to 6, wherein the electronic communications include real-time remote operations and asset information, the electronic communications include desired settings associated with the underground operations, the devices include edge and Internet of Things (IOT) devices, and the electronic communications are received by a platform that processes data from the edge and the IOT devices and from one or more processors.

8. The method according to any one of claims 1 to 7, further comprising: The operating set point is provided to the platform as the desired setting.

9. The method according to any one of claims 1 to 8, further comprising: designing surface facilities associated with the underground operations based at least on the second model; as well as A subsurface operating objective is determined based at least on the second model.

10. The method according to any one of claims 1 to 9, wherein the real-time data comprises: Pressure, virtual flow and equipment status.

11. A computing system for autonomously performing subterranean operations, the computing system comprising: one or more processors; as well as a memory system comprising one or more non-transitory computer-readable media storing instructions that, when executed by at least one of the one or more processors, cause the computing system to perform operations comprising: receiving electronic communications from a device associated with the underground operation; determining real-time data based on said received electronic communications; constructing a first model based at least on the real-time data, wherein the first model includes a first set of elements, wherein the first set of elements includes a first subset of features from a design of the subterranean operation; validating the first model, wherein the validating comprises ensuring that the first model meets a performance threshold; calculating a target for the subsurface operation using the first model if the first model satisfies the threshold; updating the first model based at least on the calculated target; setting an operating set point based at least on the calculated target; providing the operating set point to the platform as a desired setting; managing production based at least on the operating set point; constructing a second model based at least on the real-time data; adjusting a preselected set of said second elements to match historical data associated with said underground operation; optimizing a second set of elements of the subsurface operation; and A field development plan associated with the subsurface operation is determined based at least on the second model.

12. The computing system of claim 11, further comprising: designing surface facilities associated with the underground operations based at least on the second model; as well as A subsurface operating objective is determined based at least on the second model.

13. A computing system as described in any of claims 11 or 12, wherein the electronic communications include real-time remote operation and asset information, the electronic communications include desired settings associated with the underground operations, the devices include edge and Internet of Things (IOT) devices, and the electronic communications are received by a platform that processes data from the edge and the IOT devices and from the one or more processors.

14. The computing system of any one of claims 11 to 13, further comprising: If the first model does not meet the threshold, continue to build the first model.

15. A non-transitory computer-readable medium storing instructions for autonomously performing subsurface operations, the instructions, when executed by one or more processors of a computing system, causing the computing system to perform operations comprising: receiving electronic communications from devices associated with the underground operation, wherein the electronic communications include real-time remote operations and asset information, wherein the electronic communications include desired settings associated with the underground operation, wherein the devices include edge and Internet of Things (IOT) devices, wherein the electronic communications are received by a platform that processes data from the edge and IOT devices and from one or more processors; determining real-time data based on the received communications, wherein the real-time data includes pressure, virtual flow, and equipment status; constructing a first model based at least on the real-time data, wherein the first model includes a first set of elements, wherein the first set of elements includes a first subset of features from a design for the subsurface operation, wherein the design includes a first development scenario, a surface facility, and a subsurface operation objective; validating the first model, wherein the validating comprises ensuring that the first model meets a performance threshold; If the first model does not meet the threshold, continue to build the first model; calculating targets for the subsurface operation using the first model if the first model satisfies the threshold, wherein the targets include a production target target and an injection target; optimizing said calculated objective of said subsurface operation; updating the first model based at least on the optimized computational objective; setting an operating set point based at least on the optimized calculated objective; providing the operating set point to the platform as the desired setting; managing production based at least on the operating set point; constructing a second model based at least on the real-time data, wherein the second model includes a second set of elements, wherein the second set of elements includes a second subset of features from the design of the subterranean operation, wherein the first set of elements is smaller than the second set of elements; adjusting a preselected set of said second elements to match historical data associated with said underground operation; optimizing said second set of elements of said subsurface operation; determining the field development scenario associated with the subsurface operation based at least on the second model, wherein the field development scenario includes a number of assets, a type of assets, a location of the assets, a field production level of the assets, and results of drilling of an appraisal well, wherein the determining includes performing a technical analysis of the subsurface operation and performing an economic analysis of the subsurface operation; designing the surface facilities associated with the underground operation based at least on the second model, wherein the surface facilities include above-ground appurtenances, structures, equipment, storage fixtures, and processing fixtures; as well as The underground operational target is determined based at least on the second model, wherein the underground operational target includes a target category, a target location, a target shape, a target boundary, and target features associated with the underground operational target, wherein the target features include a target borehole, the target category, and a target coordinate system.

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