Automatic labelling of data during directional drilling

Abstract

A method for performing directional drilling includes receiving a steering command to perform a directional drilling action with a downhole tool in a subsurface. The method also includes receiving first input data based upon and / or in response to the steering command. The method also includes modifying the steering command in response to the first input data to produce a first modified steering command to perform a first modified directional drilling action with the downhole tool. The method also includes receiving measured data related to the downhole tool while the first modified directional drilling action is being performed. The method also includes determining one or more outputs based upon the measured data. The one or more outputs are determined by a large language model (LLM) and / or generative artificial intelligence (Gen AI) model.

Description

Attorney Docket No.: IS24.1019-WO-PCTAUTOMATIC LABELLING OF DATA DURING DIRECTIONAL DRILLINGCross-Reference to Related Applications

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 693275, filed on September 11, 2024, which is incorporated by reference herein.Background

[0002] Due to the complexity of the wells being drilled today, there are risk and reward scenarios associated with the planning and execution of directional drilling. Being able to de-skill and deman the directional drilling process while ensuring efficiency and consistency can improve drilling operations. Therefore, what is needed is a system and method for automatic labelling of data during directional drilling, which may help to provide these benefits.Summary

[0003] A method for performing directional drilling is disclosed. The method includes receiving a steering command to perform a directional drilling action with a downhole tool in a subsurface. The method also includes receiving first input data based upon and / or in response to the steering command. The method also includes modifying the steering command in response to the first input data to produce a first modified steering command to perform a first modified directional drilling action with the downhole tool. The method also includes receiving measured data related to the downhole tool while the first modified directional drilling action is being performed. The method also includes determining one or more outputs based upon the measured data. The one or more outputs are determined by a large language model (LLM) and / or generative artificial intelligence (Gen Al) model.

[0004] A computing system is also disclosed. The computing system includes one or more processors and a memory system. The memory system includes 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. The operations include receiving a steering command to perform a directional drilling action with a downhole tool in a subsurface. The operations also include receiving first input data based upon and / or in response to the steering command. The operations also include modifying the steering command inAttorney Docket No.: IS24.1019-WO-PCT response to the first input data to produce a first modified steering command to perform a first modified directional drilling action with the downhole tool. The operations also include receiving measured data related to the downhole tool while the first modified directional drilling action is being performed. The operations also include determining one or more outputs based upon the measured data. The one or more outputs are determined by a large language model (LLM) and / or generative artificial intelligence (Gen Al) model.

[0005] A non-transitory computer-readable medium is also disclosed. The medium includes instructions that, when executed by one or more processors of a computing system, cause the computing system to perform operations. The operations include receiving a steering command to perform a directional drilling action with a downhole tool in a subsurface. The operations also include receiving first input data based upon and / or in response to the steering command. The operations also include modifying the steering command in response to the first input data to produce a first modified steering command to perform a first modified directional drilling action with the downhole tool. The operations also include receiving measured data related to the downhole tool while the first modified directional drilling action is being performed. The operations also include determining one or more outputs based upon the measured data. The one or more outputs are determined by a large language model (LLM) and / or generative artificial intelligence (Gen Al) model.

[0006] It will be appreciated that this summary is intended merely to introduce some aspects of the present methods, systems, and media, which are more fully described and / or claimed below. Accordingly, this summary is not intended to be limiting.Brief Description of the Drawings

[0007] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the present teachings and together with the description, serve to explain the principles of the present teachings. In the figures:

[0008] Figure 1 illustrates an example of a system that includes various management components to manage various aspects of a geologic environment, according to an embodiment.

[0009] Figure 2 illustrates a flowchart showing labelling decision making during a directional drilling job, according to an embodiment.Attorney Docket No.: IS24.1019-WO-PCT

[0010] Figure 3 illustrates an automated steering command capture during “commentary steering,” according to an embodiment.

[0011] Figure 4 illustrates a flowchart showing a chat hot interaction between a user and the system, according to an embodiment.

[0012] Figure 5 illustrates a schematic view of a downhole tool performing directional drilling in a subsurface, according to an embodiment.

[0013] Figure 6 illustrates a flowchart of a method for performing directional drilling, according to an embodiment.

[0014] Figure 7 illustrates a schematic view of a computing system for performing at least a portion of the method(s) described herein, according to an embodiment.Detailed Description

[0015] Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings and figures. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be apparent to one of ordinary skill in the art that the present disclosure may be practiced without these specific details. In other instances, well-known methods, procedures, components, circuits, and networks have not been described in detail so as not to unnecessarily obscure aspects of the embodiments.

[0016] It will also be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first object or step could be termed a second object or step, and, similarly, a second object or step could be termed a first object or step, without departing from the scope of the present disclosure. The first object or step, and the second object or step, are both, objects or steps, respectively, but they are not to be considered the same object or step.

[0017] The terminology used in the description herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used in this description and the appended claims, the singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and / or” as used herein refers to and encompasses any possible combinations of one or more of the associatedAttorney Docket No.: IS24.1019-WO-PCT listed items. It will be further understood that the terms “includes,” “including,” “comprises” and / or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. Further, as used herein, the term “if’ may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context.

[0018] Attention is now directed to processing procedures, methods, techniques, and workflows that are in accordance with some embodiments. Some operations in the processing procedures, methods, techniques, and workflows disclosed herein may be combined and / or the order of some operations may be changed.

[0019] System Overview

[0020] Figure 1 illustrates an example of a system 100 that includes various management components 110 to manage various aspects of a geologic environment 150 (e.g., an environment that includes a sedimentary basin, a reservoir 151, one or more faults 153-1, one or more geobodies 153-2, etc.). For example, the management components 110 may allow for direct or indirect management of sensing, drilling, injecting, extracting, etc., with respect to the geologic environment 150. In turn, further information about the geologic environment 150 may become available as feedback 160 (e.g., optionally as input to one or more of the management components 110).

[0021] In the example of Figure 1, the management components 110 include a seismic data component 112, an additional information component 114 (e.g., well / logging data), a processing component 116, a simulation component 120, an attribute component 130, an analysis / visualization component 142 and a workflow component 144. In operation, seismic data and other information provided per the components 112 and 114 may be input to the simulation component 120.

[0022] In an example embodiment, the simulation component 120 may rely on entities 122. Entities 122 may include earth entities or geological objects such as wells, surfaces, bodies, reservoirs, etc. In the system 100, the entities 122 can include virtual representations of actual physical entities that are reconstructed for purposes of simulation. The entities 122 may include entities based on data acquired via sensing, observation, etc. (e.g., the seismic data 112 and otherAttorney Docket No.: IS24.1019-WO-PCT information 114). An entity may be characterized by one or more properties (e.g., a geometrical pillar grid entity of an earth model may be characterized by a porosity property). Such properties may represent one or more measurements (e.g., acquired data), calculations, etc.

[0023] In an example embodiment, the 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 pre-defined classes to facilitate modeling and simulation. A commercially available example of an object-based framework is the MICROSOFT® .NET® framework (Redmond, Washington), which provides a set of extensible object classes. In the .NET® framework, an object class encapsulates a module of reusable code and associated data structures. Object classes can be used to instantiate object instances for use in by a program, script, etc. For example, borehole classes may define objects for representing boreholes based on well data.

[0024] In the example of Figure 1, the simulation component 120 may process information to conform to one or more attributes specified by the attribute component 130, which may include a library of attributes. Such processing may occur prior to input to the simulation component 120 (e g., consider the processing component 116). As an example, the simulation component 120 may perform operations on input information based on one or more attributes specified by the attribute component 130. In an example embodiment, the simulation component 120 may construct one or more models of the geologic environment 150, which may be relied on to simulate behavior of the geologic environment 150 (e.g., responsive to one or more acts, whether natural or artificial). In the example of Figure 1, the analysis / visualization component 142 may allow for interaction with a model or model-based results (e.g., simulation results, etc.). As an example, output from the simulation component 120 may be input to one or more other workflows, as indicated by a workflow component 144.

[0025] As an example, the simulation component 120 may include one or more features of a simulator such as the ECLIPSE™ reservoir simulator (SLB, Houston Texas), the INTERSECT™ reservoir simulator (SLB, Houston Texas), etc. As an example, a simulation component, a simulator, etc. may include features to implement one or more meshless techniques (e.g., to solve one or more equations, etc.). As an example, a reservoir or reservoirs may be simulated with respect to one or more enhanced recovery techniques (e.g., consider a thermal process such as SAGD, etc ).Attorney Docket No.: IS24.1019-WO-PCT

[0026] As an example, the simulation component 120 may include one or more features of a simulator such as SYMMETRY™ software (SLB, Houston, Texas). More particularly, SYMMETRY™ may process workflows in a single integrated environment with accurate thermodynamic fluid representation and consistent modeling across multiple disciplines including process, production, and HSE. The simulator integrates steady-state and transient (e.g., dynamic) analyses that can be tailored for each domain. This approach enables users to optimize processes in upstream, midstream, and downstream sectors while maximizing profits and minimizing capital expenditures. It may also help reduce emissions, energy consumption, and waste.

[0027] As an example, the simulation component 120 may include one or more features of a simulator such as PIPESIM™ (SLB, Houston, Texas). More particularly, PIPESIM™ is steadystate multiphase flow simulator that incorporates the three areas of flow modeling: multiphase flow, heat transfer and fluid behavior.

[0028] As an example, the simulation component 120 may include one or more features of a simulator such as OLGA™ (SLB, Houston, Texas). More particularly, OLGA™ is a dynamic multiphase flow simulator that models transient flow (e.g., time-dependent behaviors) to maximize production potential. Transient modeling is a component for feasibility studies and field development design. Dynamic simulation is useful in deep water and is used in both offshore and onshore developments to investigate transient behavior in pipelines and wellbores. Transient simulation with the OLGA™ simulator provides an added dimension to steady-state analysis by predicting system dynamics, such as time-varying changes in flow rates, fluid compositions, temperature, solids deposition, and operational changes.

[0029] In an example embodiment, the management components 110 may include features of a commercially available framework such as the PETREL® seismic to simulation software framework (SLB, Houston, Texas). The PETREL® framework provides components that allow for optimization of exploration and development operations. The PETREL® framework includes seismic to simulation software components that can output information for use in increasing reservoir performance, for example, by improving asset team productivity. Through use of 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 may be considered an application and may be considered a data-driven application (e.g., where data is input for purposes of modeling, simulating, etc.).Attorney Docket No.: IS24.1019-WO-PCT

[0030] In an example embodiment, various aspects of the management components 110 may include add-ons or plug-ins that operate according to specifications of a framework environment. For example, a commercially available framework environment marketed as the OCEAN® framework environment (SLB, Houston, Texas) allows for integration of add-ons (or plug-ins) into a PETREL® framework workflow. The OCEAN® framework environment leverages .NET® tools (Microsoft Corporation, Redmond, Washington) and offers stable, user-friendly interfaces for efficient development. In an example embodiment, various components may be implemented as add-ons (or plug-ins) that conform to and operate according to specifications of a framework environment (e.g., according to application programming interface (API) specifications, etc.).

[0031] Figure 1 also shows an example of a framework 170 that includes a model simulation layer 180 along with a framework services layer 190, a framework core layer 195 and a modules layer 175. The framework 170 may include the commercially available OCEAN® framework where the model simulation layer 180 is the commercially available PETREL® model-centric software package that hosts OCEAN® framework applications. In an example embodiment, the PETREL® software may be considered a data-driven application. The PETREL® software can include a framework for model building and visualization.

[0032] As an example, a framework may include features for implementing one or more mesh generation techniques. For example, a framework may include an input component for receipt of information from interpretation of seismic data, one or more attributes based at least in part on seismic data, log data, image data, etc. Such a framework may include a mesh generation component that processes input information, optionally in conjunction with other information, to generate a mesh.

[0033] In the example of Figure 1, the model simulation layer 180 may provide domain objects 182, act as a data source 184, provide for rendering 186 and provide for various user interfaces 188. Rendering 186 may provide a graphical environment in which applications can display their data while the user interfaces 188 may provide a common look and feel for application user interface components.

[0034] As an example, the domain objects 182 can include entity objects, property objects and optionally other objects. Entity objects may be used to geometrically represent wells, surfaces, 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 aAttorney Docket No.: IS24.1019-WO-PCT property object provides log information as well as version information and display information (e.g., to display the well as part of a model).

[0035] In the example of Figure 1, data may be stored in one or more data sources (or data stores, generally physical data storage devices), which may be at the same or different physical sites and accessible via one or more networks. The model simulation layer 180 may be configured to model projects. As such, a particular project may be stored where stored project information may include inputs, models, results and cases. Thus, upon completion of a modeling session, a user may store a project. At a later time, the project can be accessed and restored using the model simulation layer 180, which can recreate instances of the relevant domain objects.

[0036] In the example of Figure 1, the geologic environment 150 may include layers (e.g., stratification) that include a reservoir 151 and one or more other features such as the fault 153-1, the geobody 153-2, etc. As an example, the geologic environment 150 may be outfitted with any of a variety of sensors, detectors, actuators, etc. For example, equipment 152 may include communication circuitry to receive and to transmit information with respect to one or more networks 155. Such information may include information associated with downhole equipment 154, which may be equipment to acquire information, to assist with resource recovery, etc. Other equipment 156 may be located remote from a well site and include sensing, detecting, emitting or other circuitry. Such equipment may include storage and communication circuitry to store and to communicate data, instructions, etc. As an example, one or more satellites may be provided for purposes of communications, data acquisition, etc. For example, Figure 1 shows a satellite in communication with the network 155 that may be configured for communications, noting that the satellite may additionally or instead include circuitry for imagery (e.g., spatial, spectral, temporal, radiometric, etc.).

[0037] Figure 1 also shows the geologic environment 150 as optionally including equipment 157 and 158 associated with a well that includes a substantially horizontal portion that may intersect with one or more fractures 159. For example, consider a well in a shale formation that may include natural fractures, artificial fractures (e.g., hydraulic fractures) or a combination of natural and artificial fractures. As an example, a well may be drilled for a reservoir that is laterally extensive. In such an example, lateral variations in properties, stresses, etc. may exist where an assessment of such variations may assist with planning, operations, etc. to develop a laterally extensive reservoir (e.g., via fracturing, injecting, extracting, etc ). As an example, the equipmentAttorney Docket No.: IS24.1019-WO-PCT157 and / or 158 may include components, a system, systems, etc. for fracturing, seismic sensing, analysis of seismic data, assessment of one or more fractures, etc.

[0038] As mentioned, the system 100 may be used to perform one or more workflows. A workflow may be a process that includes a number of worksteps. A workstep may operate on data, for example, to create new data, to update existing data, etc. As an example, a may operate on one or more inputs and create one or more results, for example, based on one or more algorithms. As an example, a system may include a workflow editor for creation, editing, executing, etc. of a workflow. In such an example, the workflow editor may provide for selection of one or more predefined worksteps, one or more customized worksteps, etc. As an example, a workflow may be a workflow implementable in the PETREL® software, for example, that operates on seismic data, seismic attribute(s), etc. As an example, a workflow may be a process implementable in the OCEAN® framework. As an example, a workflow may include one or more worksteps that access a module such as a plug-in (e g., external executable code, etc.).Automatic Labelling of Data During Directional Drilling

[0039] The present disclosure includes an automated method that uses a combination of voice capture, image capture, plots, numerical displays, and / or chatbots to capture the reasons behind steering decisions and / or the acknowledgement that the proper steering decision was made by a machine. More particularly, the method may capture the reasons behind steering decisions while performing directional drilling (DD). The method may also record, store, and reuse the reasons behind steering decisions during directional drilling. The steering decisions may be performed directly by a machine or through a human.

[0040] The autonomous directional drilling program includes automated directional drilling advisor software that provides, in real-time, optimal decision-making ability for directional drilling. After developing the workflow for motors, the directional drilling advisor may now extend its capability to provide trajectory, command, and / or downlink recommendations for any power drive rotary steerable system (RSS) tool. This may allow the directional drilling advisor to cover any type of well from start to end by automatically providing, at each survey point, the next sequence of steering actions and also adjusting those decisions on-the-fly with actions to change the course of the well.Attorney Docket No.: IS24.1019-WO-PCT

[0041] One of the challenges for being able to develop a robust, fit-for-purpose autonomous directional drilling workflow is to capture systematically the return of experience from very proficient experienced users able to make accurate and optimized steering decisions and drill directional wells very efficiently. Figure 2 illustrates a flowchart showing labelling decision making during a directional drilling job, according to an embodiment. At each decision point, identified by either an autonomous system or a human user, there may be one or more scenarios:1. Human derived action: during the human derived action, the user may trigger (e.g., by calling automatically the DD name) the voice and / or video recording, talk about the main reasons why this action was preferred, and point to the issues related to autonomous system decision, if any. Because the voice can enable action from the system, the user can directly dictate the command he / she wants, and the system will execute these commands.2. Autonomous system derived action: the human / system may trigger the voice and / or video recording and highlight the engine modules that have accurate calculations and also explain why he / she thinks that the autonomous system is making the right decision.3. Autonomous system updated steering action: Each time there is an update in the steering sequences, the voice / video recording may prompt the user to give an opinion on the latest updates.

[0042] Once the voice and / or video recording is completed, the system may automatically record the following information:TimeDepth- Current steering parameters including hole bottom, yield, tool face (TF) offset, neutral build, neutral walkSteering mode- Mode specific parameters for either motor steering or RSS steering (see example in Figure3)Snapshot of drilling parameters along with their averages in the last stand or 100 ft or so Last previous steering command(s) (e.g., as a function of distance and / or depth) Current hole bottom location- Distance and orientation with respect to the original plan Tool health statusAttorney Docket No.: IS24.1019-WO-PCTTelemetry statusSteering trajectory context- Active target(s)ConstraintsAnticollision risk status

[0043] Figure 3 illustrates an automated steering command capture during “commentary steering,” according to an embodiment. Once the “Commentary steering” information has been captured for the entire well, the voice and video captured may be automatically processed in a structured manner to obtain the following:Comprehensive statistics on autonomous steering such as percentage of autonomous steering,Reasons for human intervention statistics including main modules causing human intervention, and- A correlation study on the link between human steering interventions and drilling parameters, steering modes, telemetry service outputs, and / or the factors listed above.

[0044] The capture of unstructured data may then be structured and / or analyzed by a large language model (LLM) or generative artificial intelligence (Gen Al) to extract reasoning, thus enabling in the future the fine tuning of specialized LLM for guiding people on decision making.

[0045] For engaging with the system and triggering the recording, it may be voice-enabled and / or click-enabled. For voice-enabled, the user may call the name of the automatic directional drilling. Possible names include:DD Connect- Neuro Connect- Neuro voice- Neuro BotDD Bot

[0046] Figure 4 illustrates a flowchart showing a chat bot interaction between a user and the system, according to an embodiment. A user can use the system to perform the following:Send steering action commands- Give general comments on behavior of the systemAsk the system questions related to directional drillingAttorney Docket No.: IS24.1019-WO-PCTAsk questions related to tool specifications, software, firmware, current states, particular manuals- Ask for explanation on system derived decisions

[0047] Thus, the method described herein may be used to: extract steering statistics using “commentary steering”- learn and map out the human behavior during directional drilling applications automatically assess autonomous steering performance- extract steering statistics by correlating steering module performance with human intervention capture steering decisions related to particular fields, clients, formation, preferences, etc.- automatically identify flaws on an autonomous directional drilling job capture unstructured data and structuring them using the LLM automatically start a voice or video recording when a steering decision point is reached- interact with a system via chatbot voice-enabled

[0048] Figure 5 illustrates a schematic view of a downhole tool 500 performing using directional drilling to form a wellbore 505 in a subsurface 510, according to an embodiment. The downhole tool 500 may perform a first directional drilling action at location 515 that transitions the wellbore 505 from a first trajectory 520 to a second trajectory 525. The downhole tool 500 may also perform a second directional drilling action at location 530 that transitions the wellbore 505 from the second trajectory 525 to a third trajectory 535.

[0049] Figure 6 illustrates a flowchart of a method 600 for performing directional drilling, according to an embodiment. More particularly, the method 600 may be used to automatically label data during directional drilling in a subsurface. For example, labelling the data may include identifying steering command changes and / or highlighting the exact depth that each of those command changes occur. It may also or instead include identifying steering response changes and labelling the time that each occurs or any other event that might be detected, planned, or unplanned. An illustrative order of the method 600 is provided below; however, one or more portions of the method 600 may be performed in a different order, simultaneously, repeated, or omitted.

[0050] The method 600 may include receiving a steering command to perform a directional drilling action with the downhole tool 500 in a subsurface formation, as at 605. The steering command may include a tool face (TF) and / or steering ratio (SR). The steering command mayAttorney Docket No.: IS24.1019-WO-PCT include first reasons why the directional drilling action is selected. The first reasons may include recommending the TF, the SR, a target inclination and / or a target azimuth or a turn percentage to follow, or a combination thereof. The steering command may be received from one of a user and / or a computing system. The steering command may include a voice capture, an image capture, a video capture, a numerical display, a log, a plot, a text, a chatbot, or a combination thereof that explains a basis for the first reasons.

[0051] The method 600 may also include receiving first input data based upon and / or in response to the steering command, as at 610. The first input data may be received from the other of the user and the computing system. The first input data may be received before or after the directional drilling action is performed. The first input data may include second reasons why the directional drilling action should be modified. The second reasons may include the additional and / or different reasons than the first reasons. More particularly, the second reasons may conflict with the first reasons. In an example, the second reasons may include following a different trajectory, sending different steering commands including the TF and / or SR, selecting a different mode of operation of the downhole tool, or a combination thereof.

[0052] The method 600 may also include modifying the steering command in response to the first input data to produce a first modified steering command, as at 615. The steering command may be modified before or after the directional drilling action is performed. The steering command may be modified in response to the second reasons that are additional and / or different than the first reasons. The first modified steering command modifies the directional drilling action to produce a first modified directional drilling action. An example of this is shown in Figure 5 where the first modified directional drilling action occurs at location 515, which transitions the wellbore 505 from the first trajectory 520 to the second trajectory 525.

[0053] The method 600 may also include receiving measured data related to the downhole tool 500 while the directional drilling action and / or the first modified directional drilling action is / are being performed, as at 620. The measured data may be unstructured. The measured data may include a time; a depth; current steering parameters including hole bottom, yield, tool face offset, neutral build, neutral walk, or a combination thereof; mode-specific parameters for motor-steering or rotary steerable system (RSS)-steering; drilling parameters; previous steering commands; a current hole bottom location; a distance and / or an orientation with respect to an original drillingAttorney Docket No.: IS24.1019-WO-PCT plan; a health status of the downhole tool; a telemetry status; a steering trajectory; an active target; a constraint; an anti-collision risk status; or a combination thereof.

[0054] The method 600 may also include determining one or more outputs based upon the measured data, as at 625. The one or more outputs may be determined by a large language model (LLM) and / or generative artificial intelligence (Gen Al) model. The one or more outputs may include statistics about autonomous steering of the downhole tool 500, reasons for human intervention to steer the downhole tool 500, links between the measured data and the human intervention, or a combination thereof. The one or more outputs may also or instead include differences between the first input data and the measured data. The one or more outputs may also or instead include a status of the downhole tool 500 before and / or after modifying the steering command. The status may include a deviation from a drilling plan; a tortuosity; a number of the actions to modify the steering command and / or the directional drilling action; and / or responses of the downhole tool to modifying the steering command and / or the directional drilling action. The one or more outputs may also or instead include real-time histograms showing the first modified steering command and the measured data. The one or more outputs may also or instead include automated alarms and / or corrective actions in response to the measured data exceeding a threshold.

[0055] The method 600 may also include displaying the one or more outputs, as at 630.

[0056] The method 600 may also include generating a prompt to communicate with the user in response to the one or more outputs, as at 635.

[0057] The method 600 may also include receiving second input data from the user based upon or in response to the prompt, as at 640.

[0058] The method 600 may also include modifying the first modified steering command based upon the one or more outputs and the second input data to produce a second modified steering command, as at 645. In one embodiment, this may include generating and / or transmitting a signal that recommends, instructs, or causes the first modified steering command and / or the directional drilling action to be modified. In another embodiment, this may include physically modifying the directional drilling action. The second modified steering command modifies the directional drilling action to produce a second modified directional drilling action. An example of this is shown in Figure 5 where the second modified directional drilling action occurs at location 530, which transitions the wellbore 505 from the second trajectory 525 to the third trajectory 535. The second modified directional drilling action may include modifying the TF, modifying the SR,Attorney Docket No.: IS24.1019-WO-PCT modifying the target inclination and / or target azimuth, modifying the weight and / or torque on the drill bit, or a combination thereof.Exemplary Computing System

[0059] In some embodiments, the methods of the present disclosure may be executed by a computing system. Figure 7 illustrates an example of such a computing system 700, in accordance with some embodiments. The computing system 700 may include a computer or computer system 701A, which may be an individual computer system 701A or an arrangement of distributed computer systems. The computer system 701A includes one or more analysis modules 702 that are configured to perform various tasks according to some embodiments, such as one or more methods disclosed herein. To perform these various tasks, the analysis module 702 executes independently, or in coordination with, one or more processors 704, which is (or are) connected to one or more storage media 706. The processor(s) 704 is (or are) also connected to a network interface 707 to allow the computer system 701A to communicate over a data network 709 with one or more additional computer systems and / or computing systems, such as 70 IB, 701C, and / or 70 ID (note that computer systems 70 IB, 701C and / or 70 ID may or may not share the same architecture as computer system 701A, and may be located in different physical locations, e.g., computer systems 701 A and 701B may be located in a processing facility, while in communication with one or more computer systems such as 701 C and / or 70 ID that are located in one or more data centers, and / or located in varying countries on different continents).

[0060] A processor may include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.

[0061] The storage media 706 may be implemented as one or more computer-readable or machine-readable storage media. Note that while in the example embodiment of Figure 7 storage media 706 is depicted as within computer system 701A, in some embodiments, storage media 706 may be distributed within and / or across multiple internal and / or external enclosures of computing system 701A and / or additional computing systems. Storage media 706 may include one or more different forms of memory including semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flashAttorney Docket No.: IS24.1019-WO-PCT memories, magnetic disks such as fixed, floppy and removable disks, other magnetic media including tape, optical media such as compact disks (CDs) or digital video disks (DVDs), BLURAY® disks, or other types of optical storage, or other types of storage devices. Note 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 having possibly plural nodes. Such computer-readable or machine-readable storage medium or media is (are) considered to be part of an article (or article of manufacture). An article or article of manufacture may refer to any manufactured single component or multiple components. The storage medium or media may be located either in the machine running the machine-readable instructions, or located at a remote site from which machine-readable instructions may be downloaded over a network for execution.

[0062] In some embodiments, computing system 700 contains one or more method execution module(s) 708. In the example of computing system 700, computer system 701A includes the method execution module 708. In some embodiments, a single method execution module may be used to perform some aspects of one or more embodiments of the methods disclosed herein. In other embodiments, a plurality of method execution modules may be used to perform some aspects of methods herein.

[0063] It should be appreciated that computing system 700 is merely one example of a computing system, and that computing system 700 may have more or fewer components than shown, may combine additional components not depicted in the example embodiment of Figure 7, and / or computing system 700 may have a different configuration or arrangement of the components depicted in Figure 7. The various components shown in Figure 7 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.

[0064] Further, the steps in the processing methods described herein may be implemented by running one or more functional modules in information processing apparatus such as general purpose processors or application specific chips, such as ASICs, FPGAs, PLDs, or other appropriate devices. These modules, combinations of these modules, and / or their combination with general hardware are included within the scope of the present disclosure.

[0065] Computational interpretations, models, and / or other interpretation aids may be refined in an iterative fashion; this concept is applicable to the methods discussed herein. This may includeAttomev Docket No.: IS24.1019-WO-PCT use of feedback loops executed on an algorithmic basis, such as at a computing device (e.g., computing system 700, Figure 7), and / or through manual control by a user who may make determinations regarding whether a given step, action, template, model, or set of curves has become sufficiently accurate for the evaluation of the subsurface three-dimensional geologic formation under consideration.

[0066] The foregoing description, for purposes of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or limiting to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. Moreover, the order in which the elements of the methods described herein are illustrated and described may be re-arranged, and / or two or more elements may occur simultaneously. The embodiments were chosen and described in order to best explain the principles of the disclosure and its practical applications, to thereby enable others skilled in the art to best utilize the disclosed embodiments and various embodiments with various modifications as are suited to the particular use contemplated.

Claims

Attorney Docket No.: IS24.1019-WO-PCTCLAIMSWhat is claimed is:

1. A method for performing directional drilling, the method comprising: receiving a steering command to perform a directional drilling action with a downhole tool in a subsurface; receiving first input data based upon and / or in response to the steering command; modifying the steering command in response to the first input data to produce a first modified steering command to perform a first modified directional drilling action with the downhole tool; receiving measured data related to the downhole tool while the first modified directional drilling action is being performed; and determining one or more outputs based upon the measured data, wherein the one or more outputs are determined by a large language model (LLM) and / or generative artificial intelligence (Gen Al) model.

2. The method of claim 1, wherein the steering command and / or the first modified steering command comprise a tool face (TF) and / or steering ratio (SR).

3. The method of claim 1 , wherein the steering command is received from one of a user and / or a computing system, and wherein the first input data is received from the one of the user and the computing system.

4. The method of claim 1, wherein the steering command comprises first reasons why the directional drilling action is selected.

5. The method of claim 4, wherein the first reasons comprise a target inclination, a target azimuth, or a turn percentage to follow.

6. The method of claim 4, wherein the first input data comprises second reasons why the directional drilling action should be modified.Attorney Docket No.: IS24.1019-WO-PCT7. The method of claim 6, wherein the second reasons conflict with the first reasons.

8. The method of claim 6, wherein the second reasons comprise additional and / or different reasons than the first reasons.

9. The method of claim 8, wherein the steering command is modified in response to the second reasons that are additional and / or different than the first reasons.

10. The method of claim 9, wherein the second reasons comprise following a different trajectory, sending different steering commands including a tool face (TF) and / or steering ratio (SR), selecting a different mode of operation of the downhole tool, or a combination thereof.

11. A computing system, comprising: one or more processors; and 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, the operations comprising: receiving a steering command to perform a directional drilling action with a downhole tool in a subsurface; receiving first input data based upon and / or in response to the steering command; modifying the steering command in response to the first input data to produce a first modified steering command to perform a first modified directional drilling action with the downhole tool; receiving measured data related to the downhole tool while the first modified directional drilling action is being performed; and determining one or more outputs based upon the measured data, wherein the one or more outputs are determined by a large language model (LLM) and / or generative artificial intelligence (Gen Al) model.Attorney Docket No.: IS24.1019-WO-PCT12. The computing system of claim 11 , wherein the first input data is received before the downhole tool performs the directional drilling action, and wherein the downhole tool performs the first modified directional drilling action.

13. The computing system of claim 11, wherein the first input data is received after the downhole tool performs the directional drilling action.

14. The computing system of claim 11, wherein the steering command is modified before the downhole tool performs the directional drilling action, and wherein the downhole tool performs the first modified directional drilling action.

15. The computing system of claim 11, wherein the steering command is modified after the downhole tool performs the directional drilling action.

16. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing system, cause the computing system to perform operations, the operations comprising: receiving a steering command to perform a directional drilling action with a downhole tool in a subsurface; receiving first input data based upon and / or in response to the steering command; modifying the steering command in response to the first input data to produce a first modified steering command to perform a first modified directional drilling action with the downhole tool; receiving measured data related to the downhole tool while the first modified directional drilling action is being performed; and determining one or more outputs based upon the measured data, wherein the one or more outputs are determined by a large language model (LLM) and / or generative artificial intelligence (Gen Al) model.

17. The non-transitory computer-readable medium of claim 16, wherein the measured data comprises:Attorney Docket No.: IS24.1019-WO-PCT a time; a depth; current steering parameters including hole bottom, yield, tool face offset, neutral build, neutral walk, or a combination thereof; mode-specific parameters for motor-steering or rotary steerable system (RSS)-steering; drilling parameters; previous steering commands; a current hole bottom location; a distance and an orientation with respect to an original drilling plan; a health status; a telemetry status; a steering trajectory; an active target; a constraint; and an anti-collision risk status.

18. The non-transitory computer-readable medium of claim 17, wherein the one or more outputs comprise: statistics about autonomous steering of the downhole tool, reasons for human intervention to steer the downhole tool, and links between the measured data and the human intervention; differences between the first input data and the measured data; a status of the downhole tool before and after modifying the steering command; real-time histograms showing the first modified steering command and the measured data; and automated alarms and corrective actions in response to the measured data exceeding a threshold.

19. The non-transitory computer-readable medium of claim 18, wherein the status comprises: deviation from a drilling plan; a tortuosity;Attorney Docket No.: IS24.1019-WO-PCT a number of the actions needed to modify the steering command and the directional drilling action; and responses of the downhole tool to modifying the steering command and the directional drilling action.

20. The non-transitory computer-readable medium of claim 19, wherein the operations further comprise: generating a prompt to communicate with a user in response to the one or more outputs; receiving second input data from the user based upon or in response to the prompt; and modifying the first modified steering command based upon the one or more outputs and the second input data to produce a second modified steering command, and wherein the second modified steering command modifies the directional drilling action to produce a second modified directional drilling action.

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