Method for inferring human-equipment interaction

Abstract

A method for detecting human-equipment interaction. The method includes receiving at least one image from at least one optical device disposed within a defined work space. At least one human or piece of equipment may be detected at a first position within the work space. A movement of the human and / or the equipment may then be tracked within the work space. A description of the tracked movement of the human and / or equipment may then be generated. An assessment based on the generated description may then be generated, the assessment having an estimated determination whether the human and / or equipment adhered to a set of predetermined instructions and / or safety protocols, wherein the assessment comprises a generated recommendation for additional data. The method may also include performing an action such as a wellsite action or other facility related action in response to the generated assessment.

Description

Attorney Docket No.: IS24.0400-WO-PCTMETHOD FOR INFERRING HUMAN-EQUIPMENT INTERACTIONCross-Reference to Related Applications

[0001] This patent application claims priority to U.S. Provisional Patent Application No. 63 / 693,253, filed on September 11, 2024, which is incorporated by reference.Background

[0002] Current vision analytics algorithms may depend heavily on detection and classification models along with tracking and business logic in order to understand an event. Results from vision analytics algorithms may lack context, however, leading to uncertainty on the part of the user.

[0003] What is needed is a new approach for detection and classification, which may help a system understand a certain event or action. The method should be capable of generating textual descriptions, which may be analyzed by another foundational model to further understand the detected interaction and increase scene understanding. The method should also be generic and capable of being extended to many multimodal scenarios.Summary

[0004] A method for detecting human-equipment interaction is provided. The method includes receiving a plurality of images from at least one optical device disposed within a defined work space, detecting the presence of an object within the images, tracking a movement of the object based upon the images, generating a description of the tracked movement of the object, generating an assessment based on the generated description, and displaying the assessment on a display associated with a user.

[0005] Also provided is a computing system having one or more processors and a memory system having 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 plurality of images from at least one optical device disposed within a defined work space, detecting the presence of an object within the images, tracking a movement of the object based upon the images, generating a description of the tracked movement of the object, generating an assessment based on the generated description, and displaying the assessment on a display associated with a user.Attorney Docket No.: IS24.0400-WO-PCT

[0006] Also provided is 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 include receiving a plurality of images from at least one optical device disposed within a defined work space, detecting the presence of an object within the images, tracking a movement of the object based upon the images, generating a description of the tracked movement of the object, generating an assessment based on the generated description, and displaying the assessment on a display associated with a user.

[0007] 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

[0008] 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:

[0009] 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.

[0010] Figure 2 illustrates a representative diagram of a sequence of outputs generated by a method for inferring human-equipment interactions, according to an embodiment.

[0011] Figure 3 illustrates a flowchart of a method for inferring human-equipment interactions, according to an embodiment.

[0012] Figure 4 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

[0013] 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 invention. However, it will be apparent to one of ordinary skill in the art that the invention may be practiced without these specific details. In other instances, well-known methods, procedures, components,Attorney Docket No.: IS24.0400-WO-PCT circuits, and networks have not been described in detail so as not to unnecessarily obscure aspects of the embodiments.

[0014] 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.

[0015] 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 associated 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.

[0016] 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.System Overview

[0017] 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 geologicAttorney Docket No.: IS24.0400-WO-PCT environment 150. Tn turn, further information about the geologic environment 1 0 may become available as feedback 160 (e.g., optionally as input to one or more of the management components 110).

[0018] 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.

[0019] 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 may 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 other 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.

[0020] 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 may 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.

[0021] 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 theAttorney Docket No.: IS24.0400-WO-PCT 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.

[0022] 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 ).

[0023] 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 may 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.

[0024] 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.

[0025] 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 andAttorney Docket No.: IS24.0400-WO-PCT 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.

[0026] 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 may 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) may 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.).

[0027] 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.).

[0028] 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 may include a framework for model building and visualization.Attorney Docket No.: IS24.0400-WO-PCT

[0029] 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.

[0030] 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 may display their data while the user interfaces 188 may provide a common look and feel for application user interface components.

[0031] As an example, the domain objects 182 may 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 a property object provides log information as well as version information and display information (e.g., to display the well as part of a model).

[0032] 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 may be accessed and restored using the model simulation layer 180, which may recreate instances of the relevant domain objects.

[0033] 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. OtherAttorney Docket No.: IS24.0400-WO-PCT 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.).

[0034] 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 equipment 157 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.

[0035] 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.).Method for Inferring Human-Equipment InteractionsAttorney Docket No.: IS24.0400-WO-PCT

[0036] According to certain embodiments, multiple logics or algorithms may be run on a video or a series of images captured by one or more cameras or optical devices disposed or installed in a work space or other defined area. The one or more cameras may be communicated or otherwise coupled to the system 100 seen in Figure 1, for example the processing unit 116. The work space may be any area in which humans and various forms of equipment may be in frequent close proximity to each other, for example factories, oil rigs or refineries, warehouses, or any other industrial facility.

[0037] Figure 2 illustrates a sequence of outputs provided by a method 200 for inferring humanequipment interactions. According to certain embodiments, the presence of a human and / or equipment may be detected within the defined work space using object detection methodologies such as but not limited to object detection models. In certain embodiments, the equipment may be a stand-alone object or a component to a larger machine or product. In certain embodiments, the equipment may be relatively small and capable of being handheld by the human, or the equipment may be relatively large, for example a crane or forklift which requires the human to traverse under a suspended load. The human and / or the equipment may have its position within the work space tracked over a period or interval of time using temporal stitching techniques such as for example using a Kalman filter. In certain embodiments, multiple humans and / or pieces of equipment may be detected and tracked within the work space. The method 200 may generate a list 202 which includes an initial position or coordinate 204 for each human, object, or piece of equipment 206 detected within the work space. For example, as seen in Figure 2, a first person is detected at a first position xl, yl, x2, y2, while a second person is detected at first position x3, y3, x4, y4, and a first equipment is detected at first position x5, y5, x6, y6. The motion or position of the object(s) 206 may then be tracked over a time interval 208, for example over a frame as captured by the optical device. The list 202 is then updated according to the movements of the object(s) 206 at the end of the time interval 208, for example with the first person being at a second position xl’, yl’, x2’, y2’, while the second person is detected at a second position x3’, y3’, x4’, y4’, and the first equipment being detected at a second position x5’, y5’, x6’, y6’ . The process may be repeated over a plurality of time intervals 208 with the updated position of the object(s) being added to the list 202 after each subsequent time interval 208. According to certain embodiments, each time interval 208 may further be associated with a timestamp 210. In certain embodiments, a probability score 212 is generated and added to the list 202 for each time interval 208, the probability score 212Attorney Docket No.: IS24.0400-WO-PCT representing a level of certainty of that specific object 206 being located at the detected position 204.

[0038] According to certain embodiments, the data associated with each time interval may be run through, for example, a first large language model or a foundational model 220 which in turn may generate a corresponding description 214. The first large language or foundational model 220 may include a retrieval augmented generation (RAG) model, supervised fine tuning (SFT), langchain tools, or a combination thereof, according to certain embodiments. The descriptions 214 may be displayed within a table 216 that is a part of a graphical interface that is displayed for a screen that is part of the system 100 as seen in Figure 1. In certain embodiments, the description 214 may be a textual description which describes the action(s) taking place within each time interval 208. For example, based on the number of objects 206 detected in the work space, the proximity of the objects 206 to one another, and / or the position of the objects 206 relative to the work space among other factors, the method 200 may populate each of the time intervals 208 with a generated description 214 such as “Person 1 approaches the tong from the left side”, “Person 2 joins Person 1 near the tong”, or “The tong is now rotating the drill pipe under Person l’s operation” at each appropriate time interval. According to certain embodiments, each description 214 may be associated with a timestamp 218 corresponding to each time interval.

[0039] According to certain embodiments, the results of the table 216 and / or the descriptions 214 may be run through a second large language or foundational model 222 which in turn may generate an assessment 224 as seen in Figure 2. The second large language or foundational model may include a retrieval augmented generation (RAG) model, relational frame theory (RFT), langchain tools, or a combination thereof, according to certain embodiments. The assessment 224 may include a textual description presented to a user through a graphical interface, according to certain embodiments. The assessment 224 may incorporate the events within each of the descriptions 214 so as to provide a single narrative summary of the actions performed by or to the objects 206. The assessment 224 may include a report or summary of whether or how well the objects 206 adhered to a predetermined set of rules or guidelines, for example a set of safety guidelines for detected Person 1 or 2 to properly or safely operate on or around the detected equipment. According to certain embodiments, the assessment 224 may include a request for additional data or information in order to provide further analysis thereon.Attorney Docket No.: IS24.0400-WO-PCT

[0040] According to certain embodiments, a user may then perform an action in response to viewing the provided assessment 224. In certain embodiments, the action may include generating or transmitting a signal that instructs or causes an action to occur, wherein the action comprises a physical action, and wherein the physical action may include but are not limited to maintaining the equipment, repairing the equipment, activating one or more warnings or alarms within the work space, or providing operational or safety training to the humans detected within the work space.Exemplary Method

[0041] Figure 3 illustrates a flowchart of a method 300 for inferring human-equipment interactions. The method includes receiving at least one image from at least one optical device disposed within a defined work space, as at 302.

[0042] According to certain embodiments, at least one human or at least one piece of equipment is detected at a first position within the image of the work space received from the optical device, as at 304. The position of the human and / or the equipment may be detected over a first time interval.

[0043] According to certain embodiments, a movement of the detected human and / or the equipment may be tracked within the work space, as at 306. The movement of the human and / or the equipment may be tracked over a plurality of time intervals that are subsequent to the first time interval.

[0044] The method 300 may also include generating a description of the tracked movement of the human and / or equipment, as at 308. According to certain embodiments, the description may be a textual description and may describe at least one act that has been performed by the human within the work space, at least one action performed by the equipment, and / or at least one interaction between the human and the equipment. In certain embodiments, a description may be generated for each of the plurality of time intervals. According to certain embodiments, each description may be generated using a large language model and / or a foundation model.

[0045] The method 300 may also include generating an assessment based on the generated description, as at 310. According to certain embodiments, the assessment may include an estimated determination whether the human and / or the equipment adhered to or followed a set of predetermined instructions and / or safety protocols. The assessment may also include a generatedAttorney Docket No.: IS24.0400-WO-PCT recommendation for additional data. According to certain embodiments, the assessment may be generated using a large language model and / or a foundation model

[0046] The method 300 may also include performing an action such as a wellsite action or other facility related action in response to the generated assessment, as at 312. The facility action may include generating or transmitting a signal that instructs or causes an action to occur. The facility action may include a physical action. The physical action may include but is not limited to maintaining the equipment, repairing the equipment, activating one or more warnings or alarms within the work space, providing operational or safety training to the humans detected within the work space, or a combination thereof.Exemplary Computing System

[0047] In some embodiments, the methods of the present disclosure may be executed by a computing system. Figure 4 illustrates an example of such a computing system 400, in accordance with some embodiments. The computing system 400 may include a computer or computer system 401A, which may be an individual computer system 401A or an arrangement of distributed computer systems. The computer system 401A includes one or more analysis modules 402 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 402 executes independently, or in coordination with, one or more processors 404, which is (or are) connected to one or more storage media 406. The processor(s) 404 is (or are) also connected to a network interface 407 to allow the computer system 401 A to communicate over a data network 409 with one or more additional computer systems and / or computing systems, such as 40 IB, 401C, and / or 401D (note that computer systems 401B, 401C and / or 401D may or may not share the same architecture as computer system 401A, and may be located in different physical locations, e.g., computer systems 401A and 401B may be located in a processing facility, while in communication with one or more computer systems such as 401 C and / or 40 ID that are located in one or more data centers, and / or located in varying countries on different continents).

[0048] A processor may include a microprocessor, microcontroller, processor module or subsystem, programmable integrated circuit, programmable gate array, or another control or computing device.Attorney Docket No.: IS24.0400-WO-PCT

[0049] In some embodiments, computing system 400 contains one or more artificial intelligence module(s) 408. In the example of computing system 400, computer system 401 A includes the Al module 408. In some embodiments, a single Al module may be used to perform some aspects of one or more embodiments of the methods disclosed herein. In other embodiments, a plurality of Al modules may be used to perform some aspects of methods herein.

[0050] The storage media 406 may be implemented as one or more computer-readable or machine-readable storage media. Note that while in the example embodiment of Figure 4 storage media 406 is depicted as within computer system 401A, in some embodiments, storage media 406 may be distributed within and / or across multiple internal and / or external enclosures of computing system 401 A and / or additional computing systems. Storage media 406 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 flash 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.

[0051] It should be appreciated that computing system 400 is merely one example of a computing system, and that computing system 400 may have more or fewer components than shown, may combine additional components not depicted in the example embodiment of Figure 4, and / or computing system 400 may have a different configuration or arrangement of the components depicted in Figure 4. The various components shown in Figure 4 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.Attorney Docket No.: IS24.0400-WO-PCT

[0052] 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.

[0053] 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 include use of feedback loops executed on an algorithmic basis, such as at a computing device (e.g., computing system 400, Figure 4), 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.

[0054] The foregoing description, for purpose 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 illustrate 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.: IS24.0400-WO-PCTCLAIMSWhat is claimed is:

1. A method for detecting human-equipment interaction, the method comprising: receiving a plurality of images from at least one optical device disposed within a defined work space; detecting a presence of an object within the images; tracking a movement of the object based upon the images; generating a description of the tracked movement of the object; and generating an assessment based on the generated description.

2. The method of claim 1, wherein detecting the presence of the object within the images comprises detecting the presence of a human, equipment, or a combination thereof within the defined work space.

3. The method of claim 1, wherein detecting the presence of the object within the images comprises detecting the object over a first time interval.

4. The method of claim 3, wherein detecting the object over the first time interval comprises: assigning the object a first position within the defined work space at a beginning of the first time interval; and assigning the object a second position within the defined work space at an end of the first time interval.

5. The method of claim 4, wherein detecting the object over the first time interval comprises generating a probability score corresponding to the object being located at the first position at the beginning of the first time interval and at the second position at the end of the first time interval.

6. The method of claim 1, wherein detecting the presence of the object within the images comprises:Attorney Docket No.: IS24.0400-WO-PCT detecting the object over a plurality of time intervals; and adding each of the time intervals to a generated list.

7. The method of claim 6, further comprising adding a description to the list for each of the added time intervals, wherein the description corresponds to at least one act involving the object within the defined work space for each respective time interval.

8. The method of claim 7, wherein the description for each time interval comprises a description of at least one act performed by a human within the defined work space, at least one action performed by equipment within the defined work space, at least one interaction between the human and the equipment within the defined work space, or a combination thereof.

9. The method of claim 7, wherein the description is a textual description.

10. The method of claim 7, wherein the description is generated using a large language model and / or a foundation model.

11. The method of claim 1, further comprising performing a facility action in response to the generated assessment.

12. 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 plurality of images from at least one optical device disposed within a defined work space; detecting a presence of an object within the images; tracking a movement of the object based upon the images; generating a description of the tracked movement of the object; generating an assessment based on the generated description; andAttorney Docket No.: IS24.0400-WO-PCT displaying the assessment on a display associated with a user.

13. The computing system of claim 12, wherein the tracking the movement of the obj ect based upon the images comprises tracking movement of the object over a plurality of time intervals.

14. The computing system of claim 13, wherein the operations further comprise assigning a time stamp to each time interval.

15. The computing system of claim 13, wherein tracking movement of the object over the plurality of time intervals comprises tracking a location of the object within the defined work space.

16. The computing system of claim 15, wherein tracking the location of the object comprises assigning a set of coordinates for the object for each of the time intervals.

17. The computing system of claim 11, wherein generating the assessment comprises determining whether a human and / or equipment within the defined work space adhered to a set of predetermined instructions and / or safety protocols.

18. The computing system of claim 12, wherein generating the assessment comprises generating a recommendation for additional data.

19. The computing system of claim 12, wherein the operations further comprise performing a facility action in response to the generated assessment, wherein the facility action comprises generating or transmitting a signal that instructs or causes an action to occur, wherein the facility action comprises a physical action, wherein the physical action comprises maintaining the equipment, repairing the equipment, activating one or more warnings or alarms within the work space, providing operational or safety training to the humans detected within the work space, or a combination thereof.Attorney Docket No.: IS24.0400-WO-PCT20. 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 plurality of images from at least one optical device disposed within a defined work space; detecting a presence of an object within the images; tracking a movement of the object based upon the images; generating a description of the tracked movement of the object; generating an assessment based on the generated description; and displaying the assessment on a display associated with a user.

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