Method to create the alerts visualization on 3D & 2d model for CCUS end-to-end operations on runtime

Abstract

A computer-implemented method is provided including: processing, by a computing device, operational data associated with interconnected assets included in a carbon capture, utilization, and sequestration (CCUS) value chain; generating a digital representation of the CCUS value chain based on processing the operational data; mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; setting a mode associated with displaying the digital representation, based on an alert included in the real-time alarm data and a type of the alert, wherein the mode includes a two- dimensional (2D) display mode or a three-dimensional (3D) display mode; displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.

Description

71CCS-511081-WO-1 (BHI0576PCT4)METHOD TO CREATE THE ALERTS VISUALIZATION ON 3D & 2D MODEL FOR ecus END-TO-END OPERATIONS ON RUNTIMECROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of an earlier filing date from U.S. Provisional Application Serial No. 63 / 694,516 filed September 13, 2024, the entire disclosure of which is incorporated herein by reference.BACKGROUND

[0002] In the resource recovery and fluid sequestration industries, some approaches for visualization of carbon capture, utilization, and storage (CCUS) operations fail to provide end users with immediate access to real-time operational data and alert data associated with the CCUS operations, and more specifically, for a CCUS value chain as a whole.BRIEF DESCRIPTION OF THE DRAWINGS

[0003] The following descriptions should not be considered limiting in any way. With reference to the accompanying drawings, like elements are numbered alike:

[0004] FIG. 1 illustrates a system supportive of in accordance with aspects of the present disclosure.

[0005] FIG. 2 illustrates an example dashboard generated, managed, and displayed by the system in association with managing Measurement, Monitoring and Verification (MMV) operations for CCUS sites in accordance with one or more embodiments of the present disclosure.

[0006] FIG. 3 illustrates an example of recorded log details which may be generated, managed, and displayed in accordance with one or more embodiments of the present disclosure.

[0007] FIG. 4 illustrates an example of a system in accordance with one or more embodiments of the present disclosure.

[0008] FIG. 5 illustrates an example graphical visualization of a digital representation generated and provided by the system in accordance with one or more embodiments of the present disclosure.

[0009] FIGS. 6 A through 6C illustrate example graphical visualizations of digital representations generated and provided by the system in accordance with one or more embodiments of the present disclosure.71CCS-511081-WO-1 (BHI0576PCT4)

[0010] FIG. 7 illustrates an example of graphical visualization of a digital representation generated and provided by the system in accordance with one or more embodiments of the present disclosure.

[0011] FIG. 8 depicts a block diagram of a processing system in accordance with one or more embodiments of the present disclosure.

[0012] FIG. 9 illustrates an example flowchart of a method in accordance with one or more embodiments of the present disclosure.SUMMARY

[0013] Embodiments of the present disclosure are directed to a computer- implemented method including: processing, by a computing device, operational data associated with interconnected assets included in a carbon capture, utilization, and sequestration (CCUS) value chain; generating a digital representation of the CCUS value chain based on processing the operational data; mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; setting a mode associated with displaying the digital representation, based on an alert included in the realtime alarm data and a type of the alert, wherein the mode includes a two-dimensional (2D) display mode or a three-dimensional (3D) display mode; displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.

[0014] Embodiments of the present disclosure are also directed to a system including: a computing device including a processor and a memory, wherein the memory includes instructions stored thereon that, when executed by the processor, cause the processor to perform operations including: processing operational data associated with interconnected assets included in a carbon capture, utilization, and sequestration (CCUS) value chain; generating a digital representation of the CCUS value chain based on processing the operational data; mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; setting a mode associated with displaying the digital representation, based on an alert included in the real-time alarm data and a type of the alert, wherein the mode includes a two-dimensional (2D) display mode or a three- dimensional (3D) display mode; displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.

[0015] Embodiments of the present disclosure are also directed to a computer program product including a computer readable storage medium having program instructions71CCS-511081-WO-1 (BHI0576PCT4) embodied therewith, the program instructions executable by a processor to cause the processor to perform operations including: processing, by a computing device, operational data associated with interconnected assets included in a carbon capture, utilization, and sequestration (CCUS) value chain; generating a digital representation of the CCUS value chain based on processing the operational data; mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; setting a mode associated with displaying the digital representation, based on an alert included in the realtime alarm data and a type of the alert, wherein the mode includes a two-dimensional (2D) display mode or a three-dimensional (3D) display mode; displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.

[0016] Further aspects supported by the present disclosure and features of example embodiments are illustrated in the accompanying drawings and / or described in the following description.DETAILED DESCRIPTION

[0017] A detailed description of one or more embodiments of the disclosed apparatus and method are presented herein by way of exemplification and not limitation with reference to the Figures.

[0018] FIG. 1 illustrates a system 100 supportive of managing measurement, monitoring and verification (MMV) operations for CCUS sites in accordance with aspects of the present disclosure. The system 100 provides an integrated asset model supportive of the real time monitoring of an end-to-end CCUS value chain 115.

[0019] It is to be understood herein that the example aspects described herein reference to the functions provided by systems (e.g., system 100, system 400 later described herein, and the like) in association with MMV operations are not limited thereto, and the example aspects and techniques may similarly be implemented in association with operations for an entire CCUS value chain 115, which includes capture, storage, transportation, and utilization.

[0020] As will be described herein, aspects of the system 100 overcome shortcomings associated with some approaches for managing MMV operations for CCUS sites. For example, in some other approaches, CCUS project operators do not have a mechanism to know the optimal operational parameters throughout a given CCUS value chain. Such approaches fail to provide real-time process feedback based on which a user may understand71CCS-511081-WO-1 (BHI0576PCT4) whether the operations associated with the CCUS value chain are running within safe and optimized limits. Rather, for example, such approaches relay on a manual process in which an operator applies the operator’s knowledge and experience to define the operating parameters. Such manual approaches for identifying issues and tuning the operational parameters correctly to optimize the process is time consuming and can be prone to error. In some cases, due to manual intervention by an operator, situations may arise in which integrity issues are not identified on time, which may lead to direct and indirect monetary losses.

[0021] The system 100 may include a digital platform system 105 (also referred to herein as a CCUS digital platform system), the CCUS value chain 115, modeling and simulation components 125, a machine learning engine 160, and a recommendation engine 175. In some aspects the digital platform system 105 may access data from any of the components (e.g., CCUS value chain 115, modeling and simulation components 125, a machine learning engine 160, and a recommendation engine 175), aggregate the data, forward the data, process the data, and / or provide additional data to any of the components in association with implementing features of the system 100 described herein.

[0022] As will be described herein, the system 100 supports a recommendation system 101 (a real-time digital recommendation system) for optimized and safe operations for the CCUS value chain 115. The recommendation system 101 may include the digital platform system 105, modeling and simulation components 125, machine learning engine 160, and the recommendation engine 175.

[0023] The recommendation system 101 is capable of providing real time recommendations for optimal operational parameters for the CCUS value chain 115. The recommendation system 101 may link simulation data 126 (modelled simulation data) with real-time operational data 116 for the CCUS value chain 115. Based on processing the simulation data 126 and the real-time operational data 116, the recommendation system 101 may provide optimized recommendations (e.g., recommendations 178, for example, real-time recommendations), example aspects of which are later described herein. In some aspects, the recommendation system 101 may function as a closed loop digital system, maintaining or updating operational parameters 176 associated with the CCUS value chain 115 based on the recommendations 178.

[0024] The modeling and simulation components 125 may include an inspection block 135, a feasibility study block 140, and an update block 145. The modeling and simulation components 125 may include a simulation environment 130 configured to simulate various assets 120.71CCS-511081-WO-1 (BHI0576PCT4)

[0025] The machine learning engine 160 may create an operating envelope for optimal operating parameters based on outputs from the modeling and simulation components 125, simulation data 128, and real data 118 (e.g., including real-time operational data 116). The machine learning engine 160 may include a flow assurance 161 module, a leak detection module 162, a corrosion monitoring module 163, a well / reservoir integrity module 164, a surface analytics 165, a pattern recognition / vectorization module 170. The recognition / vectorization module 170 may compare patterns associated with the simulation data 128 and the real data 118 and provide a reference identification 171 (alarms trend base reference identification) and / or analytics results 172 based on the comparison.

[0026] The machine learning engine 160 may include machine learning model(s) which may be trained and / or updated based on training data provided or accessed by any devices or systems described herein. The machine learning model(s) may be built and updated by a computing device (e.g., computing device implemented at digital platform system 105, a processor 821) based on the training data (also referred to herein as training data and feedback).

[0027] The machine learning model(s) may be provided in any number of formats or forms. In one or more embodiments, the operations described herein may implement machine learning and / or rule-based systems to generate a mixing instruction. In one or more embodiments, the machine learning engine 160 may include (e.g., for theoretical and empirical processes) rule-based systems using predefined rules to make decisions or perform tasks, which may operate based on if-then statements.

[0028] In one or more embodiments, the machine learning engine 160 may include natural language processing (NLP) techniques supportive of the interaction between computers and human language, enabling machines to understand, interpret, and generate human language (e.g., risk descriptions, risk remediation plans, risk mitigation plans, alerts, notifications, recommendations, and the like).

[0029] In one or more embodiments, the machine learning engine 160 may include computer vision techniques supportive of image processing, object recognition, and image segmentation. In an example, the computer vision techniques may support the integration of sensor data.

[0030] In one or more embodiments, the machine learning engine 160 may include data mining techniques supportive of discovering patterns and relationships in large datasets (e.g., from database and data pipeline 440 later described herein with reference to FIG. 4, from hard disk 823 later described herein with reference to FIG. 8, other data later described71CCS-511081-WO-1 (BHI0576PCT4) herein, and the like) and extract information. For example, the data mining techniques may support the discovery of interdependencies described herein such as, for example, interdependencies between real-time operational data 116 (e.g., sensor data), real data 118, simulation data 126, simulation data 128, analytics results 172, operational parameters 176, recommendations 178, operating envelopes, action items, notifications, user preferences, and the like.

[0031] The recommendation engine 175 may process the analytics results 172 and, based on the processing, may generate operational parameters 176 and recommendations 178.

[0032] In some aspects, the recommendation system 101 may be capable of performing any of the functions described herein in real-time or near real-time and autonomously (e.g., without any manual intervention). For example, the recommendation system 101 may provide recommendations 178 and / or update operational parameters 176 in real-time or near real-time. In another example, the recommendation system 101 may provide recommendations 178 and / or update operational parameters 176 autonomously, but is not limited thereto.

[0033] Compared to some other approaches, aspects of the recommendation system 101 and techniques described herein provide advantages such as, for example, real-time recommendations through a closed loop digital system that reduces turnaround time associated with setting or adjusting (e.g., optimizing) operational parameters 176 associated with the CCUS value chain 115 in association with maintaining safe operations for the CCUS value chain 115. Aspects of the recommendation system 101 and techniques described herein provide advantages such as, for example, increased accuracy and optimization compared to manual approaches. Operations are more accurate and optimized, as the recommendation system 101 may provide recommendations 178 and / or update operational parameters 176 without manual intervention by a user. Aspects of the recommendation system 101 and techniques described herein provide advantages such as, for example, increased operational efficiency of the CCUS value chain 115, and accordingly, increased monetary benefits resulting from the improved operational efficiency.

[0034] In an example, components (e.g., digital platform system 105, modeling and simulation components 125, simulation environment 130, machine learning engine 160, recommendation engine 175, and the like) of the system 100 may be implemented in a cloud network to which components of the CCUS value chain 115 are connected. In some aspects, the integrated asset model may be implemented at a computing device (or multiple computing devices) included in the cloud network.71CCS-511081-WO-1 (BHI0576PCT4)

[0035] As will be described herein, the system 100 is capable of generating and providing a digital representation (e.g., integrated asset model 450 later described herein) of a CCUS value chain 115 with connected assets 120 included in the CCUS value chain 115. The digital representation may be referred to herein as a digital landscape or digital twin of the CCUS value chain 115. Further, embodiments of the present disclosure are not limited thereto a CCUS value chain 115 and the systems and techniques described herein may support management of any suitable end-to-end physical system including multiple connected assets 120.

[0036] The system 100 may include sensors (not illustrated) respectively associated with measuring performance of the connected assets 120. The sensors may provide measured data in real-time or based on other criteria (e.g., a temporal period, a trigger condition, or the like). In some aspects, the sensors may provide metrics associated with a performance parameter between different connected assets 120.

[0037] For example, the sensors may provide GHG / flue gas metrics or pipeline metrics (e.g., CO2 transportation metric). For example, the sensors may provide flow, temperature, and pressure data regarding the flow of CO2 between different connected assets 120 (e.g., between asset 120-b, asset 120-c, and / or asset 120-d). The sensors may provide metrics associated with transporting a product (e.g., CO2) associated with the CCUS value chain 115 between different connected assets 120. Similarly, for example, the system 100 may include other sensors capable of providing pipeline metrics (e.g., flow, temperature, and pressure data) regarding the flow of CO2 between other connected assets 120.

[0038] In another example, a sensor associated with an asset 120 (e.g., a well site) may provide sensor data associated with a well site. For example, the sensor may respectively provide pressure and temperature (PT) gauge electrical and optical data, distributed acoustic and temperature data, and surface metering data (e.g., associated with zone flow and wellhead protection (WHP)) associated with the well site.

[0039] In another example, a sensor may provide metrics related to the health of an asset 120 and case operations. For example, the sensor may provide pressure, volume, and temperature measurements associated with the asset 120. In an example, the sensor may measure timeseries tags real-time readings. The real-time readings may include different types of flow, volume, and temperature.

[0040] In another example, a sensor may provide data related to actual carbon capture by an asset 120 versus target metrics. For example, the sensor may provide pressure, volume, and temperature measurements associated with the asset 120. In an example, the sensor may71CCS-511081-WO-1 (BHI0576PCT4) measure timeseries tags real-time readings. The real-time readings may include different types of flow, volume, and temperature.

[0041] Embodiments of the present disclosure are not limited to the example assets 120, sensors, and measurements described with reference to the figures illustrated herein. For example, the CCUS value chain 115 may include more than 100,000 assets 120 of various asset types, and the system 100 is capable of performing features described herein in realtime. In an example, at the cloud level, the system 100 is capable of acquiring or sampling the data from computing devices (e.g., edge computing devices (not illustrated)) respectively associated with the connected assets 120, sensors respectively associated with the connected assets 120, and other sensors associated with the CCUS value chain 115.

[0042] The system 100 provides real-time recommendations, management, monitoring, and digital rendering of a full value chain from capture to sequestration. For example, the system 100 supports real-time monitoring, management, and digital rendering of CO2 flow throughout the entire CCUS value chain 115 from capture to sequestration, with all connected assets 120 throughout the entire CCUS value chain 115.

[0043] The system 100 provides automatic identification of alerts, alert locations, risks, and risk locations in the CCUS value chain 115. For example, the system 100 is capable of intelligently identifying alerts that lie within the CCUS value chain 115 based on real-time data monitoring of individual assets 120 connected through the system 100.

[0044] In some aspects, the system 100 may autonomously generate a warning signal along with recommendations, if any, to any upstream or downstream connected assets 120 included in the CCUS value chain 115. In some examples, the recommendations 178 may include corrective actions the system 100 has determined may (if implemented) eliminate a risk identified by the system 100, mitigate or reduce the impact of the risk, prevent future occurrences of the risk, and the like. In some examples, the recommendations may indicate a respective asset 120 (or assets 120) associated with the identified risk.

[0045] In some aspects, the system 100 may include any of a report, an identified risk, a recommendation, and a warning signal described herein in a digital representation (e.g., dashboard 200, integrated asset model 450, digital representation 500, digital representation 600, digital representation 601, digital representation 602, or digital representation 700 later described herein). Additionally, or alternatively, the system 100 provide any of a report, an identified risk, a recommendation, and a warning signal separately from the digital representation.71CCS-511081-WO-1 (BHI0576PCT4)

[0046] The system 100 connects individual assets 120 through the value chain 115 and is capable of identifying assets 120 within the CCUS value chain 115 which may be impacted or causing a given risk.

[0047] Although the example with reference to FIG. 1 is described with respect to a CCUS value chain 115, embodiments of the present disclosure are not limited thereto. The system 100 is capable of providing real-time monitoring and root cause identification for any value chain including interconnected assets 120.

[0048] FIGS. 2 and 3 illustrate example aspects of a dashboard 200 which may be generated by the system 100 for managing an MMV plan in accordance with one or more embodiments of the present disclosure. In accordance with one or more embodiments of the present disclosure, the system 100 is a digital system capable of managing MMV operations for CCUS sites.

[0049] FIG. 2 illustrates an example dashboard 200 generated, managed, and displayed by the system 100 in association with managing MMV operations for CCUS sites (e.g., connected assets 120). FIG. 3 illustrates an example 300 of recorded log details which may be generated, managed, and displayed by the system 100. In some examples, the system 100 may display the dashboard 200 and / or receive user inputs associated with the dashboard 200 via the user interface 110 of FIG. 1.

[0050] As will be described herein, aspects of the system 100 overcome shortcomings associated with some approaches for MMV in CCUS projects. In some cases, MMV may serve as a critical component for CCUS projects. The system 100 supports the development of an effective and efficient MMV plan to ensure the long-term integrity of a given connected asset 120 (e.g. a capture plant, a processing plant, a storage site, and the like). The system 100 supports effective and rapid access to MMV data, as providing such MMV data may be essential for regulatory compliance. The system 100 supports efficient and accurate creation and maintenance of MMV plans / schedules by a user.

[0051] In accordance with one or more embodiments of the present disclosure, the system 100 provides a digital solution that simplifies and shortens the amount of time associated with MMV plan maintenance. The system 100 provides a digital platform which supports user uploads of standard schedules for MMV into the digital platform. Via the digital platform, the system 100 provides a mechanism via which the user (or other users) may view and maintain a timeline 215 which is relatively easy to understand. In some aspects, via the digital platform and the dashboard 200, the system 100 provides the users with the capability to view, add, or update existing tests, statuses, or schedules associated71CCS-511081-WO-1 (BHI0576PCT4) with an MMV plan, for various stages (e.g., Pre-Injection, Injection, Closure) associated with the MMV plan. In some aspects, via the digital platform, the system 100 supports management of test results (e.g., manual user management of test results, autonomous management of test results). In some aspects, via the digital platform, the system 100 may autonomously (or semi-autonomously based on user inputs) associate metadata or documentation along with a given set of test results for reference.

[0052] In accordance with one or more embodiments of the present disclosure, via the platform and the dashboard 200, the system 100 provides a digital solution for effective and accurate management with relatively easy visualization of an MMV plan for individual sites (connected assets 120) and an overall project. In some aspects, the system 100 may accumulate data from different data sources (e.g., well logs) and automatically pull the test results / reports on the dashboard 200. The dashboard 200 may also be referred to herein as a MMV visualization. Other non-limiting examples of the data sources include real-time operational data 116 associated with the CCUS value chain 115 (e.g., sensor data which is associated with connected assets 120, flow valves, and the other components included in the CCUS value chain 115), simulation data 126, simulation data 128, analytics results 172, operational parameters 176, and recommendations 178 described with reference to FIG. 1.

[0053] The system 100 may provide and display various indicators 210 regarding a given MMV plan. In some aspects, the system 100 may autonomously generate reminder notifications regarding upcoming test plans (e.g., upcoming / planned) and output the notifications to users via the dashboard 200. In some aspects, the system 100 may autonomously generate an overdue notification for a missed test plan (e.g., an action item 220, for example, pulsed neutron log (PNL)) and output the notification to a user via the dashboard 200. In some aspects, the system 100 may autonomously generate a notification for an action item 220 for user review (e.g., a notification indicating that an action item 220, for example, ‘Wellhead Pressure & Temperature,’ needs attention) and output the notification to a user via the dashboard 200.

[0054] The example 300 illustrated at FIG. 3 is an example of log data which the system 100 may display in response to a user input selecting the ‘Overdue’ indicator 210 associated with the PNL. However, embodiments of the present disclosure are not limited thereto, and the system 100 may display log data for any action items 220 associated with the MMV plan.

[0055] The system 100 may maintain the reports in combination with other metadata or documents with action items 220 (e.g., scheduled tests, completed tests) for easy reference71CCS-511081-WO-1 (BHI0576PCT4) and compliance compared to some other approaches. For example, some other approaches merely implement a spreadsheet for record keeping and reporting data, for a single location (e.g. a single asset 120), thus failing to provide an effective and real-time approach for managing MMV operations for multiple connected assets 120 across a CCUS value chain 115 as described herein. The system 100 may support the addition of action items 220 (e.g., tests) and / or updating of existing action items 220 at the dashboard 200 via the digital platform.

[0056] Aspects of the system 100 and techniques described herein with reference to FIGS. 2 and 3 provide features which overcome shortcomings associated with some other approaches and provide various advantages. For example, the system 100 is capable of autonomously flagging anomalies (e.g., using one or more indicators 210) on the digital platform. Additionally, or alternatively, the system 100 may transmit notifications via a communication protocol (e.g., email, SMS, instant messaging, an audio alert, a haptic alert, or the like) and / or in-app notifications to a computing device accessible by a user.

[0057] The system 100 and techniques described herein may use and incorporate data from various integrated sources of the same type or different type (e.g., data sources described herein), and based on processing the data, the system 100 and techniques described herein may include automatically showcasing anomalies for various action item 220 (e.g., different tests).

[0058] In some aspects, the system 100 may generate and provide reminders and overdue notifications for action items 220 via the dashboard 200 and / or other notifications described herein, which supports effectively reducing or eliminating instances in which action items 220 are not fully completed, such that timelines are never missed.

[0059] In some examples, for a given action item 220, the system 100 may provide the information and notifications described herein to users (e.g., concerned users) associated with the given action item 220, while refraining from providing the information and notifications to users who are not associated with the given action items 220.

[0060] As described herein, via the dashboard 200, the system 100 may provide easily available reports for compliance and regulatory requirements. Aspects of the system 100 support controlling a MMV plan by fine grained access control as described herein, and such control features may protect data (e.g., action items 220, log data associated with action items 220) from unwanted views and updates, inadvertent updates, and the like. Accordingly, for example, aspects of managing an MMV plan provided by the system 100 and the dashboard71CCS-511081-WO-1 (BHI0576PCT4)200 may support effective and accurate maintenance of connected assets 120 of a CCUS value chain 115 (e.g., maintenance of site integrity).

[0061] FIG. 4 illustrates an example of a system 400 in accordance with one or more embodiments of the present disclosure. The system 400 may include aspects of the system 100 of FIG. 1, and repeated descriptions of like elements are omitted for brevity.

[0062] According to one or more embodiments of the present disclosure, the system 400 may automatically identify and propagate alert notifications on a real-time basis to concerned users in CCUS operations.

[0063] As will be described herein, aspects of the system 400 overcome shortcomings associated with some approaches for alert notification in CCUS operations. For example, some approaches are limited in ability related to updating end users with timely and actionable insights associated with CCUS operations, and more specifically, for a CCUS value chain 415 as a whole. Such approaches fail to provide real-time notification that is related to system performance, operations, alarms and risk for the entirety of the CCUS value chain 415 (e.g., at every included connected asset 420, at stages which connect different assets 420). The assets 420 may also be referred to herein as connected assets or interconnected assets.

[0064] Accordingly, for example, a failure to provide real-time notifications effectively (e.g., failing to provide notifications, delays in providing notifications) may result in delays in managing hazards or action items associated with the alerts, which may negatively alter prompt decision-making and potentially impact project efficiencies, timelines, and regulatory compliance. In accordance with one or more embodiments of the present disclosure, the system 400 provides a real-time notification system which supports immediate updates of a given asset 420 (e.g., 420-a) with one or more propagated assets 420 (e.g., 420-b, 420-d, or the like) which is included in the CCUS value chain 415 and directly or indirectly associated with the given asset 420, and further, accurate root cause analysis in the CCUS value chain 415. For example, the system 400 provides a real-time notification system which may ensure immediate updates of direct equipment's / assets with the propagated assets that connects the CCUS value chain 415 such that accurate root cause may be performed while inspection.

[0065] The CCUS value chain 415 may include any quantity of emitters, carbon capture plants, compressors, pipelines, and carbon storage plants, and it not limited to the emitter 420-a, carbon capture plant 420-b, compressor 420-c, pipeline 420-d, and carbon storage plant 420-e illustrated in FIG. 4.71CCS-511081-WO-1 (BHI0576PCT4)

[0066] The system 400 may provide notifications which indicate updates (e.g., risk, failures, and the like) for a given asset 420, corresponding root causes in the CCUS value chain 415, and actions for resolving the root causes.

[0067] The simulation data 426 may include aspects of simulation data 126 or simulation data 128 described herein. The system 400 may include a notification service 430, a user management service 435, a database and data pipeline 440.

[0068] The system 400 may include an integrated asset model 450, a digital risk management module 455, an alert rule configuration module 460, and an alerts management engine 465.

[0069] The system 400 may include a propagation notification service 485. The system 400 may implement analytics algorithms 480 in association with techniques described herein. Executing the analytics algorithms 480 may include generating training data 445 based on processing data provided by the propagation notification service 485.

[0070] The propagation notification service 485 may generate a data analysis 488 of data streams connected to an interconnected asset 420 (e.g., a well) for which an actual alert was generated. The propagation notification service 485 may be configured to provide notifications 486 and identify issues (at 490) based on processing an alert, a notification, results 481 provided by analytics algorithms 480, and other data provided by components of the system 400.

[0071] In accordance with one or more embodiments of the present disclosure, the design of the system 400 enables the data integration from multiple sources. For example, the system 400 may integrate data from edge to cloud, for example, from assets (e.g., carbon capture plants 420-b, compressors 420-c, pipelines 420-d, carbon storage plants 420-e (for example, storage sites, wells, reservoirs), and the like) of the CCUS value chain 415 on a real-time basis. The system 400 provides a unified digital platform which provides a comprehensive view of a CCUS process. The system 400 supports, via the digital platform, configuration (e.g., user configuration via the system 400) of the rules on alerts, risk, and operations associated with the CCUS value chain 415 and associated connected assets 420.

[0072] In some aspects, as an alert or risk is generated by the system 400, immediate asset connections are inspected by a backend software service provided by the system 400 to view and analyze real-time data associated with the alert or risk for anomalies. In response to identifying that the alert or risk exists (e.g., based on a comparison of the alert or risk against the real-time data), the system 400 may send an appropriate notification to the configured users 495 (e.g., user 495-a, user 495-b, other users 495 (not illustrated)) in the systems.71CCS-511081-WO-1 (BHI0576PCT4)

[0073] The system 400 includes an event driven architecture configured to trigger the notifications based on predefined and analysis-based rules and conditions, which may ensure quick and timely notification for all relevant users (e.g., users associated with a given alert or risk and / or affected asset 420) via a communication protocol (e.g., email, SMS, instant messaging, an audio alert, a haptic alert, or the like).

[0074] The software service provided by the 400 is stitched with the analytics algorithms 480 (e.g., which, in some examples, integrates machine learning algorithms or machine learning models) via real-time data and simulation data to predict potential issues and optimize timing associated with providing notifications to users. Accordingly, for example, based on a given alert generated by the alerts management engine 465 and / or alert generation module 470 and a corresponding notification (e.g., a notification 476 and / or notification 486), user 495-a and / or user 495-b may provide analysis feedback.

[0075] In accordance with one or more embodiments of the present disclosure, the system 400 may provide a notification of automatically identified connected assets 420 from an immediate asset 420 on which an alert rule is applied, and the system 400 may generate a further alert on the same asset 420. For example, the system 400 may automatically identify connected assets 420 from an immediate asset 420 on which an alert rule is applied, provide a notification of the automatically identified connected assets 420 in response to the alert rule being triggered, and the system 400 may generate a further alert on the same immediate asset 420 (and in some aspects, generate a further alert on the connected assets 420) in response to the alert rule being triggered.

[0076] For example, an alert rule 461 may be provided by the alert rule configuration module 460 (also referred to herein as alert rule configurator). Non-limiting examples of the rules include generating an alert associated with an asset 420, based on whether a value of an operational parameter of the asset 420 fails to satisfy a target criteria (e.g., is below a threshold value for the operational parameter, is above the threshold value). An example rule includes generating an alert in response to detecting that a measured pressure value at the compressor 420-c exceeds a threshold pressure value. An example rule includes generating an alert in response to detecting that a measured temperature at a well exceeds a threshold temperature. An example rules includes generating an alert in response to detecting that a measured inlet flow rate at a carbon capture plant 420-b exceeds a target inlet flow rate. An example rules includes generating an alert in response to detecting that pressure in a well is equal to a threshold value (e.g., 2000 pounds per square inch (PSI)) or higher for 1 hour.71CCS-511081-WO-1 (BHI0576PCT4)

[0077] The alerts management engine 465 and / or alert generation module 470 may generate an alert associated with an immediate asset 420 (e.g., a well) based on applying the alert rule to real-time data 416 provided via the CCUS system 405 (also referred to herein as a CCUS cloud). That is, the alert generation module 470 provides features for automatic alert rule creation 456 based on identifying data stream readings of propagated assets 420 of the CCUS value chain 415. Based on the alert, the notification module 475 may send or display the notification 476 to the user 495-a via a computing device associated with the user 495-a. The CCUS system 405 may be part of a digital platform system (e.g., digital platform system 105 described herein).

[0078] As an example, the alert generation module 470 may generate an alert associated with a well based on real-time data associated with the CCUS value chain 415 and an alert rule associated with the CCUS value chain 415. The system 400 may use analytics algorithms 480 to analyze the alert generated by the alert generation module 470 and provide analysis feedback. For example, based on the analysis, the system 400 may determine that the actual health of the well is as expected (e.g., normal health, well integrity satisfies a target well integrity), but the outlet flow rate from the compressor 420-c (and / or the pipeline 420-d) which provides CO2 to the well exceeds a threshold flow rate. Accordingly, for example, the system 400 may provide, in the notification 476, an indication that the generated alert associated with the well was triggered due to the outlet flow rate from the compressor 420-c or the pipeline 420-d.

[0079] In another example, the system 400 may determine that an issue (and accordingly, a generated alert) associated with a reservoir of the CCUS value chain 415 is due to an injection rate at the wellhead failing to satisfy a target injection rate.

[0080] In another example, the system 400 may determine that an issue (and accordingly, a generated alert) associated with a pipeline 420-d of the CCUS value chain 415 is due to a non-uniform flow rate or a relatively slow flow rate at a compressor 420-c coupled to the pipeline 420-d, and the system 400 may further determine that a performance issue associated with a compressor included at the compressor 420-c is due to a mechanical issue (e.g., a faulty compressor head).

[0081] In another example, the system 400 may configure respective rules associated with the metric amount of CO2 to be captured by the carbon capture plant 420-b, transported by the pipeline 420-d, and sequestered at the carbon storage plant 420-e. The system 400 may generate an alert based on the rules and respective measured amounts of CO2 as captured by71CCS-511081-WO-1 (BHI0576PCT4) the carbon capture plant 420-b, transported by the pipeline 420-d, and sequestered at the carbon storage plant 420-e.

[0082] The system 400 may generate an alert and provide a notification for an example case in which the measured amount of CO2 as sequestered at the carbon storage plant 420-e is less than a target amount of CO2, along with an indication that the generated alert was triggered due to a performance issue associated with the pipeline 420-d. For example, the system 400 may determine from analyzing the measured amounts of CO2 within the CCUS value chain 415 that the amount of CO2 transported by the pipeline 420-d is less than a target amount, and the system 400 may identify that a portion of the pipeline 420-d has a leak which is causing the issue.

[0083] Further, for example, the notification module 475 may send the same notification 476 to the propagation notification service 485. Based on processing the notification 476 and results 481 provided by analytics algorithms 480, the propagation notification service 485 may generate and send (or display) a notification 486 to the user 495- b via a computing device associated with the user 495-b. For example, the propagation notification service 485 may provide, in a notification 486, an indication of an issue at an asset in the CCUS value chain 415 which has resulted in a generated alert. For example, the notification may include an indication of an issue at a given asset (e.g., a reduced amount of CO2 captured by a carbon capture plant 420-b), respective assets (e.g., carbon storage plant 420-e) impacted by the issue, and respective performance affected by the issue (e.g., a reduced effective amount of CO2 captured at the carbon storage plant 420-e).

[0084] Accordingly, for example, the system 400 supports notifying multiple relevant users 495 based on a single alert rule, which may support effective management of the entire operations of the CCUS value chain 415 as a whole. The system 400 provides an advanced alerts event driven architecture for timely and responsive actionable notifications. Aspects of the architecture and algorithms supported by the system 400 support a relatively small amount of time (e.g., a total duration of a few seconds or less) for identifying the propagating asset for its notification. For example, based on a single alert rule which is triggered for a given asset 420 (e.g., carbon storage plant 420-e), the system 400 may identify one or more propagating assets 420 (e.g., emitter 420-a) associated with the asset 420 and the triggering of the rule and provide an actionable notification to users 495 respectively associated with the given asset 420 and the propagating assets 420, within a relatively small amount of time (e.g., a total duration of a few seconds or less).71CCS-511081-WO-1 (BHI0576PCT4)

[0085] In some embodiments, the system 400 is capable of visualizing alarm origins in real-time. For example, in addition to KPI values, the system 400 may provide real-time visualization which may aid users in visualizing a sequestration flow. Such information may provide valuable context to an entire CCUS value chain 415 and allow the user to visualize what issues and risks currently (or could potentially) create barriers to successful operation of the CCUS value chain 415.

[0086] Aspects of the system 400 and techniques described herein provide features which overcome shortcomings associated with some other approaches and provide various advantages. For example, the system 100 is capable of real-time understanding of the health of all assets 420 which are connected to an asset 420 (e.g., a well) on which an alert or risk rule condition is applied.

[0087] In some aspects, notifications (e.g., notification 476, notification 486, and the like) provided by the system 400 may include abstract information about a respective issue. Based on the abstract information, the system 400 enables an end user to navigate to the exact issue (e.g., root cause, root asset 420 associated with the issue) by persisting the context received in the notifications.

[0088] Accordingly, for example, aspects of the system 400 support effective optimization of project operations and OPEX by an end user. The system 400 and techniques described herein support implementations which prioritize safety culture for a project with timely real-time notifications. The system 400 and techniques described herein assist end users to make improved decisions by accessing real-time data (e.g., real-time data 416) and providing customizable notifications for efficient management of CCUS operations.

[0089] In accordance with one or more embodiments of the present disclosure, the system 400 provides a workflow 497 supportive of automatically identifying and propagating alert notifications on a real-time basis to concerned users in CCUS operations. The workflow 497 as described herein includes risk detection, risk planning, remediation and mitigation, issue resolution and root cause analysis (RCA), and providing recommendations.

[0090] In an example implementation, the system 400 may process operational data associated with the assets 420 which are included in the CCUS value chain 415. The operational data may be the real-time data 416 described herein.

[0091] The system 400 may generate a digital representation (e.g., integrated asset model 450, digital twin) of the CCUS value chain 415 based on processing the operational data.71CCS-511081-WO-1 (BHI0576PCT4)

[0092] In an example, the system 400 may identify a performance anomaly associated with carbon storage plant 420-e based on the processing of the operational data. The identification may be implemented, for example, by the CCUS system 405, the analytics algorithms 480, the alerts management engine 465 and / or alert generation module 470, but is not limited thereto.

[0093] The system 400 may generate, by the alert generation module 470, an alert 471 associated with the carbon storage plant 420-e based on identifying the performance anomaly.

[0094] The system 400 may inspect, in response to identifying the alert 471 , a portion of the operational data corresponding to when the alert 471 associated with the carbon storage plant 420-e was generated. The inspection may be implemented, for example, by the CCUS system 405, the analytics algorithms 480, the alerts management engine 465 and / or alert generation module 470, but is not limited thereto.

[0095] The system 400 may inspect of the portion of the operational data, for example, using techniques described with reference to data analysis 488.

[0096] The system 400 may determine, based on the inspecting of the portion of the operational data, that a performance anomaly associated with the carbon storage plant 420-e is causing the alert 471. The system 400 may further determine, based on the inspecting of the portion of the operational data, that a second performance anomaly with a carbon capture plant 420-b interconnected with the carbon storage plant 420-e is causing the performance anomaly associated with the carbon storage plant 420-e. The carbon capture plant 420-b, for example, may be feeding captured CO2 to the carbon storage plant 420-e for storage. Expressed another way, the system 400 may determine that the second performance anomaly with a carbon capture plant 420-b is the root cause of the performance anomaly associated with the carbon storage plant 420-e.

[0097] The system 400 may provide, via the digital representation, a set of notifications based on an alert rule configured for the alert 471 and the carbon storage plant 420-e. Particularly, for example, the alert rule may be configured for the alert 471 with respect to alert type and severity associated with the alert 471.

[0098] For example, the system 400 (e.g., by notification module 475) may provide a notification 476 for user 495-a in response to identifying the alert 471 associated with the carbon storage plant 420-e. Further, the system 400 (e.g., by propagation notification service 485) may provide a notification 486 for user 495-b in response to the alert 471 and based on71CCS-511081-WO-1 (BHI0576PCT4) the alert rule. The notification 486 may be with respect to the carbon capture plant 420-b being identified from among the assets 420 as contributing to the alert 471.

[0099] The system 400 may configure the notifications (e.g., notification 476, notification 486) to be provided based on severity level of the alert 471. For example, the system 400 may determine the severity level of the alert 471 based on the performance anomaly associated with the carbon storage plant 420-e.

[0100] In an example, the performance anomaly associated with the carbon storage plant 420-e may be a measured pressure at the carbon storage plant 420-e exceeding a particular threshold pressure value. A case in which the measured pressure is greater than a first threshold value may equate to relatively low severity level, a case in which the measured pressure is greater than a second threshold value (which is higher than the first threshold value) may equate to relatively moderate severity level, and a case in which the measured pressure is greater than a third threshold value (which is higher than the second threshold value) may equate to relatively high severity level.

[0101] Based on the severity level, the system 400 may provide a first control action in the notification 476 to the carbon storage plant 420-e or refrain from providing the first control action. The first control action may be associated with managing the carbon storage plant 420-e. For example, the first control action may be a corrective action to reduce CO2 flow into a reservoir at the carbon storage plant 420-e. In an example, the system 400 may provide the notification 476 for all severity levels (e.g., low severity level, moderate severity level, high severity level), and the system 400 may further provide the first control action for cases of the moderate severity level or higher. Additionally, or alternatively, for the case of the high severity level, the system 400 may provide a further instruction (e.g., evacuate the premises).

[0102] Further based on the severity level, the system 400 may provide a second control action in the notification 486 or refrain from providing the second control action. The second control action may be associated with managing the carbon capture plant 420-b. For example, the second control action may be a corrective action to stop the flow of CO2 from the carbon capture plant 420-b to the compressor 420-c, reduce the flow of CO2 from the carbon capture plant 420-b to the compressor 420-c, and / or redirect the flow of CO2 to a different compressor 420-c of the CCUS value chain 415. In an example, the system 400 may provide the notification 486 for all severity levels (e.g., low severity level, moderate severity level, high severity level) associated with the carbon storage plant 420-e, and the system 400 may further provide the second control action for cases of the moderate severity71CCS-511081-WO-1 (BHI0576PCT4) level or higher. Additionally, or alternatively, for the case of the high severity level, the system 400 may provide a further instruction (e.g., evacuate the premises).

[0103] The system 400 (e.g., by propagation notification service 485) may provide further notifications 486 (not illustrated) for other users based on the alert rule. For example, the system 400 may provide a further notification 486 for a user 495-c (not illustrated) in response to the alert 471 and based on the alert rule. In an example, the further notification 486 may be with respect to a further asset 420 (e.g., compressor 402-c, pipeline 420-d) being identified from among the assets 420 as being impacted by or causing one or more of: the performance anomaly associated with carbon storage plant 420-e or the second performance anomaly with the carbon capture plant 420-b.

[0104] In an example case with respect to FIG. 4, the notification 476 may include an indication that the first performance anomaly associated with the carbon storage plant 420-e is caused by the second performance anomaly associated with the carbon capture plant 420-b and an indication of the alert 471 associated with the carbon storage plant 420-e. The notification 486 may include an indication that the first performance anomaly associated with the carbon storage plant 420-e is caused by the second performance anomaly associated with the carbon capture plant 420-b and an indication of the alert 471 associated with the carbon storage plant 420-e.

[0105] Further in the example case, the further notification 486 (not illustrated) may include the indication of the alert 471 associated with the carbon storage plant 420-e and an indication that a third performance anomaly associated with the further asset 420 (e.g., compressor 402-c, pipeline 420-d) is caused by one or more of the first performance anomaly associated with the carbon storage plant 420-e or the second performance anomaly associated with the carbon capture plant 420-b. Alternatively or additionally in the example case, the further notification 486 (not illustrated) may include the indication of the alert 471 associated with the carbon storage plant 420-e and an indication that a third performance anomaly associated with the further asset 420 (e.g., compressor 402- c, pipeline 420-d) is causing one or more of the first performance anomaly associated with the carbon storage plant 420-e or the second performance anomaly associated with the carbon capture plant 420-b.

[0106] Accordingly, for example, the system 400 may determine, for each of the carbon storage plant 420-e, the carbon capture plant 420-b, and, if applicable, the further asset 420 (e.g., compressor 402-c, pipeline 420-d), whether to perform a respective corrective action with respect to the alert 471 which was generated with respect to the carbon storage71CCS-511081-WO-1 (BHI0576PCT4) plant 420-e. The system 400 may determine, for each of the carbon storage plant 420-e, the carbon capture plant 420-b, and if applicable, the further asset 420, a notification type based on whether to perform the respective corrective action. The system 400 may provide the set of notifications according to the determined notification types.

[0107] For example, a first notification type of the notification 476 may include the indication of the alert 471 associated with the carbon storage plant 420-e and the indication that the first performance anomaly associated with the carbon storage plant 420-e is caused by the second performance anomaly associated with the carbon capture plant 420-b, without further information. A second notification type of the notification 476 may include the same information as provided for the first notification type, along with an indication of a corrective action to reduce CO2 flow into a reservoir at the carbon storage plant 420-e. A third notification type may include the same information as provided for the first notification type or for the second notification type, along with a further instruction (e.g., evacuate the premises) as described herein.

[0108] In line with the described example, a first notification type of the notification 486 may include the indication of the alert 471 associated with the carbon storage plant 420-e and the indication that the first performance anomaly associated with the carbon storage plant 420-e is caused by the second performance anomaly associated with the carbon capture plant 420-b, without further information. A second notification type of the notification 486 may include the same information as provided for the first notification type, along with an indication of a corrective action to stop the flow of CO2 from the carbon capture plant 420-b to the compressor 420-c, reduce the flow of CO2 from the carbon capture plant 420-b to the compressor 420-c, and / or redirect the flow of CO2 to a different compressor 420-c of the CCUS value chain 415. A third notification type may include the same information as provided for the first notification type or for the second notification type, along with a further instruction (e.g., evacuate the premises) as described herein.

[0109] As has been described herein, the system 400 may provide respective notifications to target users respectively associated with the interconnected assets 420 included in the CCUS value chain 415, based on a single alert rule applied to one of the assets 420.

[0110] With respect to the determining of corrective actions, the determining of notification types, and the providing of notifications by the system 400 as described herein, the system 400 may notify all parties which are recommended by the system 400 to take action. For example, based on the corrective actions and / or notification types, the user 495-a71CCS-511081-WO-1 (BHI0576PCT4) associated with the carbon storage plant 420-e may reduce C02 flow into the reservoir at the carbon storage plant 420-e, the user 495 -b associated with the carbon capture plant 420-b may control associated with equipment to stop capturing and providing CO2, and a user associated with a further asset 420 (e.g., compressor 402-c, pipeline 420-d) which is interconnected with the carbon storage plant 420-e and / or the carbon capture plant 420-b may continue as-is without performing further actions.

[0111] As has been described herein, based on the corrective action and / or notification type, the techniques described herein may include applying one or more strategies or rules. In an example of the strategies and rules, for a case in which pressure at a particular asset 420 is greater than a threshold 1 (e.g., relatively low), the system 400 may notify all users associated with the interconnected assets 420. for a case in which the pressure is greater than a threshold 2, the system 400 may notify all users associated with the interconnected assets 420 of the and provide instructions to one or more users (associated with one or more of the interconnected assets 420) to take a control action. For a case in which the pressure is greater than a threshold 3 (e.g., severe, high), the system 400 may notify all users associated with the interconnected assets 420 and provide instructions to all users to evacuate.

[0112] The system 400 supports modifying or generating the alert rule (e.g., via alert rule configuration module 460 and a user interface provided by the system 400) based on one or more user criteria, and the system 400 may provide notifications as described herein based on the alert rule. The system 400 supports user customizable alert rules.

[0113] FIG. 5 illustrates an example graphical visualization of a digital representation 500 generated and provided by the system 400 in accordance with one or more embodiments of the present disclosure. FIG. 5 illustrates various interconnected assets 420 of the CCUS value chain 415 and alerts 571 associated with the assets.

[0114] FIGS. 6A through 6C illustrate example graphical visualizations of a digital representation 600, a digital representation 601, and a digital representation 602 generated provided by the system 400 in accordance with one or more embodiments of the present disclosure. FIGS. 6A through 6C illustrates various interconnected assets 620 (corresponding to various assets 420 of the CCUS value chain 415), sensors 625 (corresponding to various sensors 425 associated with the assets 420), and alerts 671 associated with the assets 620.

[0115] FIG. 6A illustrates an example of asset information 630 which the system 400 may provide with respect to each of the assets 620. In the example of FIG. 6A,71CCS-511081-WO-1 (BHI0576PCT4) the system 400 may display asset information 630 for a given asset 620 in response to a user input (e.g., a user input via a user interface, a user input via a link provided in a notification described herein) or based on detecting an alert associated with the asset 620. For example, the asset information 630 may indicate name of the asset 620, information 631, alert information 632, risk information 634, and recommendation information 636 associated with the asset 620, the alerts, and the risk.

[0116] FIG. 6B illustrates another example of asset information 630 which the system 400 may provide with respect to each of the assets 620. In the example of FIG. 6B, the system 400 may display asset information 630 for a given asset 620 in response to a user input (e.g., a user input via a user interface, a user input via a link provided in a notification described herein) or based on detecting an alert associated with the asset 620. For example, the asset information 630 may indicate name of the asset 620, asset type, number of sensors associated with measuring performance of the asset 620, position details (e.g., depth), region where the asset 620 is located, coordinates of the asset 620, alert information 632 (e.g., number of alerts, based on severity level), risk information 634 (e.g., number of risks, based on severity level), and MMV testing information 638 (e.g., number of injections tests, number of pre-inj ection tests, and the like).

[0117] With reference to FIGS. 5, 6B, and 6C, the system 400 may further display an indication of CO2 flow, including direction and flow rate, through the various assets 620-d (e.g., pipeline sections).

[0118] FIG. 7 illustrates an example graphical visualization of a digital representation 700 generated and provided by the system 400 in accordance with one or more embodiments of the present disclosure.

[0119] Each digital representation (e.g., digital representation 500, digital representation 600, digital representation 601, digital representation 602, digital representation 700) generated by the system 400 is a real-time digital twin of the CCUS value chain 415 and included assets 420. The system 400 may generate the digital representations using various integrated asset models 450. In some aspects, the integrated asset models 450 may include physics-based models which support a comprehensive monitoring, management, and alert solution. In some examples, the system 400 may provide local and remote visualization tools for users to view real-time operational updates associated with the CCUS value chain 415. In some examples, the system 400 may provide the real-time operational updates based on real-time data 416 (e.g., sensor data) provided by sensors 425 associated71CCS-511081-WO-1 (BHI0576PCT4) with the CCUS value chain 415. For example, the sensors 425 may provide measurements associated with operational parameters of the connected assets 420.

[0120] Via the digital representations described herein, the system 400 may provide a digital landscape representative of the CCUS value chain 415. For example, the digital representations provide a visualization of an end-to-end digital landscape of the CCUS value chain 415 and the included connected assets 420. The system 400 may display the digital representation via a user interface (e.g., user interface 110).

[0121] In an example, each of the digital representations may include a representation of connected assets 420. With reference back to FIG. 4, the included connected assets 420 may include an emitter 420-a, a carbon capture plant 420-b, a compressor 420-c, a pipeline 420-d, a carbon storage plant 420-e (also referred to herein as a storage site associated with a reservoir or a well), and the like). Other non-limiting examples of the included connected assets 420 may include a direct air capture plant, a chilled ammonia plant, a compact carbon capture plant, a utilization plant, a liquefaction plant, a ship terminal, a microseismic station, a monitoring well, an injection well, an H2 plant, a steel plant, a coal power plant, a mixed salt process plant, a well pad distribution plant, and the like.

[0122] According to one or more embodiments of the present disclosure, the system 400 may automatically identify and propagate alert notifications on a real-time basis to users 495 in CCUS operations associated with the CCUS value chain 415. In some aspects, the system 400 may propagate the alert notifications via a digital representation (e.g., digital representation 500, digital representation 600, digital representation 700) of the CCUS value chain 415. In some aspects, the alert notifications may include information as provided by alerts 471, notifications 476, and notifications 486 described herein, or other information associated with the CCUS value chain 415.

[0123] As will be described herein, aspects of the system 400 overcome shortcomings associated with some approaches for management, monitoring, and viewing of CCUS operations. For example, some other CCUS operations lack an integrated and intuitive alarm visualization system within both 3D and 2D models, resulting in delayed detection and response to critical issues. The system 400 provides an integrated and intuitive alarm visualization system within both 3D models (e.g., as illustrated at FIGS. 5 and 7) and 2D models (e.g., as illustrated at FIG. 6A, FIG. 6B, and FIG. 6C), which supports an increased effectiveness and reduced time associated with detecting and responding to critical issues (e.g., alerts based on target performance criteria).71CCS-511081-WO-1 (BHI0576PCT4)

[0124] The system 400 provides a comprehensive alarm visualization system that integrates real-time alert data into the 3D and 2D models. In some aspects, via one or more digital representations described herein, the system 400 provides clear representation of the severity and status of alarms, facilitates immediate access to detailed information, and enhances the overall effectiveness of monitoring and decision-making. Via the digital representations, the system 400 provides an interactive, user-friendly alarm management feature that improves situational awareness, accelerates response times, and supports effective optimization (e.g., in combination with user input) of the operational efficiency of a CCUS system (e.g., CCUS value chain 415).

[0125] In accordance with one or more embodiments of the present disclosure, the system 400 provides a comprehensive alarm visualization system that integrates real-time alarm data (e.g., as provided by alerts management engine 465 and / or alert generation module 470) into 3D and 2D models of CCUS operations to enhance monitoring, situational awareness, and decision-making, which supports effective predictive maintenance of assets 420. The techniques described herein include stitching the integration of software architecture which includes database management systems (e.g., database and data pipeline 440) configured to store real-time data 416 provided by edge devices (e.g., sensor devices associated with CCUS value chain 415 and assets 420) and an interface which enables user definition of custom alert rules (e.g., via alert rule configuration module 460 and a user interface provided by the system 400) and user review or modification of alert rules as generated by the system 400.

[0126] In an example, based on a relevant alert triggered by an alert engine (e.g., alerts management engine 465, alert generation module 470) of the system 400, the system 400 may map the alert to a system viewer provided by an application implemented by the system 400.

[0127] In some examples, the system 400 may generate or display the alert(s) based on one or more criteria. For example, with reference to FIGS. 5 and 6A through 6C, the system 400 may be implemented such that the system 400 displays an alert (e.g., an alert 571, an alert 671) (a pop up alert) with a notification via each time a user opens a corresponding 3D model or 2D model for detailed analysis. In some aspects, the system 400 may generate and display information which distinguishes propagated alerts associated with a given asset 420 from other connected assets 420 included in the CCUS value chain 415.

[0128] In accordance with one or more embodiments of the present disclosure, the system 400 supports a graphical unified visualization in which 3D and 2D visualizations71CCS-511081-WO-1 (BHI0576PCT4) are integrated into a single, comprehensive system and provides a holistic view of the CCUS infrastructure. The system 400 provides functionality enabling users to switch between detailed spatial representations (e.g., digital representation 500, digital representation 700) and schematic diagrams (e.g., digital representation 600) seamlessly through the entire project structure on demand. In some embodiments, the system 400 may display both a detailed spatial representation and a schematic diagram simultaneously.

[0129] The system 400 supports the real-time synchronization of the sensor data (e.g., real-time data 416) and may generate, in real-time or near real-time, an alert based on rules defined across both 3D and 2D platforms. Accordingly, for example, aspects of the real-time synchronization and alert generation by the system 400 support increased consistency and accuracy, enhancing the user experience and operational efficiency.

[0130] The system 400 is robust at least in part due to its integration of machine learning algorithms which analyze real-time data (e.g., real-time data 416) and historical data (e.g., provided from database and data pipeline 440) for predictive maintenance and early warning signs. The predictive maintenance and early warning signs provided by the system 400 introduce a proactive approach to alarm management.

[0131] The system 400 provides a software interface providing selectable on- demand viewing options (e.g., 3D model, 2D model, or 3D and 2D model simultaneously). The system 400 provides capabilities to view alerts (e.g., an alert 571, an alert 671) with all respective details in an intuitive manner in real-time or near real-time.

[0132] In some embodiments, in response to generating an alert (e.g., by alerts management engine 465 and / or alert generation module 470), the system 400 may generate and send (or display) a notification (e.g., notification 476, notification 486) to a user 495 via a computing device associated with the user 495.

[0133] In an example, the notification may include a link to open a 3D model and / or 2D model. For example, the system 400 may display alert 571 via the 3D model (digital representation 500), and / or the system 400 may display alert 671 via the 2D model (e.g., digital representation 600). The displaying of alerts via the 3D model and / or 2D model may support effective user understanding of the location of the alerts and assets impacted by the alerts, and accordingly, seamless operations on the field.

[0134] Example implementations are provided that support creating alerts visualization on 3D and 2D models for CCUS end-to-end operations at runtime is now further described with reference to FIGS. 4, 5, and 6 A through 6C. The example implementations are71CCS-511081-WO-1 (BHI0576PCT4) described with reference to systems described herein (e.g., system 100, system 400). For the present example, the system 400 of FIG. 4 is referenced.

[0135] The system 400 is configured to process operational data associated with the interconnected assets 420 included in the CCUS value chain 415. The operational data may include real-time operational data 416 obtained by one or more sensors 425 associated with the interconnected assets 420.

[0136] The system 400 is configured to generate a digital representation (e.g., integrated asset model 450, digital representation 500, digital representation 600, digital representation 601, digital representation 602) of the CCUS value chain 415 based on processing the operational data.

[0137] The system 400 is configured to map real-time alarm data associated with the CCUS value chain 415 to the digital representation of the CCUS value chain 415. For example, the system 400 may generate the real-time alarm data and an alert 471 based applying an alert rule (as described with reference to alert rule configuration module 460 and alerts management engine 465) to the real-time operational data 416.

[0138] The system 400 is configured to set a mode associated with displaying the digital representation, based on the alert 471 as included in the real-time alarm data and a type of the alert 471. For example, the system 400 may set the mode based on details of the alert 471. In some cases, the system 400 may set the mode based on multiple alerts 471 included in the real-time alarm data, respective types of the alerts 471 , and respective details of the alerts 471.

[0139] The mode may be a two-dimensional (2D) display mode or a three- dimensional (3D) display mode. In some examples, the 2D mode may include a 2D schematic representation of the CCUS value chain 415 (as illustrated at FIG. 6B and FIG. 6C) or a 2D block diagram representation of the CCUS value chain 415 (as illustrated at FIG. 6A). In some aspects, the 3D mode may include a spatial representation of the CCUS value chain 415 (as illustrated at FIG. 5).

[0140] The system 400 is configured to display a graphical visualization of the digital representation according the mode. For example, the system 400 may display a 3D graphical visualization (as illustrated at FIG. 5) or 2D graphical visualizations (as illustrated at FIG. 6 A through FIG. 6C).

[0141] The graphical visualization may include graphical representations of the interconnected assets 420 and graphical representations of individual equipment components respectively associated with the interconnected assets 420.71CCS-511081-WO-1 (BHI0576PCT4)

[0142] The system 400 may display alerts 471 via the graphical visualizations. For example, the system 400 may display alerts 571 as illustrated at FIG. 5 or display alerts 671 as illustrated at FIG. 6A through FIG. 6C. In determining the visualization mode based on an alert 471 and a type of the alert 471 , the system 400 accordingly displays a digital representation of the CCUS value chain 415 based on a visualization mode more effective for understanding the problem / fault.

[0143] In some aspects, each alert 471 may include an indication of an interconnected asset 420 which is associated with the alert 471. For example, in FIG. 5, the system 400 may display alerts 571 relatively adjacent to interconnected assets represented in the graphical visualization of the digital representation 500. In FIG. 6A through FIG. 6C, the system 400 may display alerts 671 relatively adjacent to interconnected assets 620 represented in the graphical visualization of the digital representation 600.

[0144] Additionally, or alternatively, an alert 471 may be associated with an equipment component associated with the interconnected asset 420, and the alert 471 may include an indication of the equipment component. For example, in FIG. 6B, alert 671-d may indicate a flow measurement issue associated with an equipment component located at asset 620-al (e.g., H2 plant), alert 671-e may indicate a stream quality issue associated with an equipment component located at asset 620-b4 (e.g., mixed salt process plant), alert 671-f may indicate a pressure or temperature issue associated with an equipment component located at asset 620-b2 (e.g., chilled ammonia process plant), and alert 671-h may indicate a flow measurement issue associated with an equipment component located at asset 620-c4 (e.g., compressor).

[0145] Embodiments of the present disclosure are not limited thereto, and with the alerts 671, the system 400 may provide additional or alternative detailed information such as, for example, pressure information (e.g., changes in pressure, pressure spikes / drops, pressure falling outside a target temperature envelope, pressure exceeding a threshold value, or the like), temperature information (e.g., changes in temperature, temperature spikes / drops, temperature falling outside a target temperature envelope, temperature exceeding a threshold value, or the like), and injection rate information (e.g., uniformity of injection rate, injection rate falling outside a target range, injection rate exceeding a threshold value, or the like).

[0146] In an example of additional or alternative detailed information, the system 400 may display temporal information associated with when a given alert 671 was generated. In some aspects, the system 400 may display operational data of an interconnected asset 620 associated with the alert 671 with respect to the temporal information, and the71CCS-511081-WO-1 (BHI0576PCT4) operational data may include a performance anomaly associated with the interconnected asset 620.

[0147] For example, with reference to FIG. 6A, the system 400 may display temporal information associated with when alert 671-c was generated, and the system 400 may display operational data and a performance anomaly of an interconnected asset 620-e4 (e.g., injection well west 1) with respect to the temporal information and the alert 671-c. In another example, with reference to FIG. 6C, the system 400 may display temporal information associated with when alert 671-n was generated, and the system 400 may display operational data and a performance anomaly of an interconnected asset 620-c4 (e.g., compressor) with respect to the temporal information and the alert 671-n.

[0148] As has been described herein, the system 400 may display, based on the mapping of the real-time alarm data described herein, alert indicators 672 at graphical representations of interconnected assets 420 represented in the graphical visualizations and at graphical representations of equipment components associated with the interconnected assets 420.

[0149] For a given alert 471 corresponding to an interconnected asset 420, The system 400 may provide a notification (e.g., a notification 476, a notification 486, but not limited thereto) associated with the alert 471. The notification may include a link for accessing a graphical visualization of a digital representation, according to a display mode (e.g., 2D or 3D) determined by the system 400 as described herein. The system 400 may display the graphical visualization according the mode (e.g., a graphical visualization as illustrated at FIG. 5 or FIGS. 6 A through 6C) based on processing the user input. In response to receiving and processing a user input associated with the notification, the system 400 may display the graphical visualization according the mode.

[0150] In some embodiments, the system 400 may set the mode associated with displaying the digital representation using machine learning techniques. For example, the system 400 may process the operational data and the real-time alarm data using a machine learning model. The machine learning model may include aspects of the machine learning engine 160 described herein. In some aspects, the machine learning model may implement a portion of the analytics algorithms 480 described herein. In some aspects, the machine learning model may be implemented at CCUS system 405 or machine learning engine 160.

[0151] In an example, the operational data associated with the interconnected assets 420 may include both real-time operational data 416 (as obtained by one or more sensors 425 associated with the interconnected assets 420) and historical operational data71CCS-511081-WO-1 (BHI0576PCT4) associated with the interconnected assets 420. The system 400 may set the mode based on processing, using the machine learning model, the real-time alarm data and one or more of the real-time operational data 416 and the historical operational data. For example, the machine learning model is trained to generate and display a 2D model or 3D model of the CCUS value chain 415 based on the alerts 471. The integration of machine learning algorithms to analyze real-time and historical data supports effective predictive maintenance and identification of early warning signs of failures or performance issues associated with the CCUS value chain 415, thereby providing a proactive approach to alarm management, alerting users of failures or performance issues, and providing a graphical visualization which facilitates effective user understanding of such failures or performance issues.

[0152] The system 400 may modify the mode associated with displaying the digital representation based on a user input. For example, the system 400 provides a user configurable graphical unified visualization which comprehensively provides a holistic view of the CCUS infrastructure of the CCUS value chain 415, enabling users to switch between detailed spatial representations and schematic diagrams seamlessly through the entire project structure of a CCUS project on demand.

[0153] In an example, with reference to FIG. 5 and FIG. 6A through FIG. 6C, the system 400 may provide the same alert 471 for any of the display modes (e.g., 2D schematic, 2D block diagram, 3D spatial layout) at locations corresponding to integrated assets 420 which are associated with the alert 471. Accordingly, for example, the system 400 provides display modes which may be tailored for users of a particular technical expertise (e.g., a business supervisor, an engineer operator, an engineering supervisor or manager, or the like).

[0154] For example, for a business supervisor having less technical background than an engineer, the system 400 may display the graphical visualization of the digital representation 500 of FIG. 5 with alerts 571 , but without specific details of each alert 571. Through the graphical visualization and the display of the alerts 571, the business supervisor may be able to identify locations of each alert 571 and interconnected assets associated with the alerts 571, and the business supervisor may notify respective parties (e.g., engineer operators, engineering supervisors, or the like) of the alerts and assign the parties for remediating issues associated with the alerts 571. The system 400 may also be configured to autonomously notify the parties and assign the parties with respect to remediating issues.

[0155] The system 400 may support filtering the display of interconnected assets 420 from a respective graphical visualization. For example, the system 400 may apply71CCS-511081-WO-1 (BHI0576PCT4) a display filter against respective asset types of the interconnected assets 420 based on user input (e.g., user selection). That is, the system 400 is configured to display the graphical visualization based on a target asset type indicated in a user input. Additionally, or alternatively, the system 400 may apply the display filter based on whether an alert 471 is associated with an interconnected asset 420 of a particular type.

[0156] For example, the system 400 may identify an interconnected asset 420 associated with the alert 471 from among the interconnected assets 420, based on the mapping of the real-time alarm data associated with the CCUS value chain 415 to the digital representation of the CCUS value chain 415. The system 400 may determine an asset type of the interconnected asset 420. The system 400 may apply the display filter associated with displaying the graphical visualization based on determining the determined asset type.

[0157] With reference to In an example, the system 400 may detect an alert 671 associated with an asset 620-cl (e.g., compressor plant). The system 400 may display a graphical visualization as in FIG. 6 A through 6C (or similarly, as in FIG. 5), in which graphical representations of assets 620 which are compressor plants or associated with compressor plants (e.g., asset 620-cl (compressor plant), asset 620-c2 (compressor 1), asset 620-c3 (compressor 2)) are displayed while assets 620 of a different type (e.g., asset 620-bl (direct air capture plant), asset 620-dl (pipeline DAC section 1), and the like) are hidden or displayed differently, thereby applying a display filter to a subset of the interconnected assets 620. For example, the system 400 may refrain from displaying the assets 620 of a type different from compressors.

[0158] In another example, the system 400 may display a graphical visualization of the entirety of the CCUS value chain 615 and all interconnected assets 620, in which graphical representations of assets 620 which are compressor plants or associated with compressor plants are displayed using color, bold, highlighting, or the like while displaying the assets 620 of a different type are grayscale (i.e., greyed out).

[0159] In another example, the system 400 may display a graphical visualization of the entirety of the CCUS value chain 615 and all interconnected assets 620, in which respective identifiers of assets 620 which are compressor plants or associated with compressor plants are displayed while respective identifiers of assets 620 of a different type are hidden.

[0160] In another example, the system 400 may detect an alert 471 associated with compressor 420-c and pipelines 420-d. The system 400 may display graphical representations of assets 620 which are compressors (e.g., asset 620-cl (compressor plant),71CCS-511081-WO-1 (BHI0576PCT4) asset 620-c2 (compressor 1), asset 620-c3 (compressor 2), or the like) and pipelines (e.g., asset 620-d5, asset 620-d6, asset 620-d2, asset 620-d7, or the like) using color, bold, highlighting, respective identifiers, or the like while displaying the assets 620 of a different type differently (e.g., greyed out, no identifiers, or the like).

[0161] In some aspects, the system 400 may display relative severity levels of the alerts 471 via the graphical visualizations. For example, referring to FIG. 6C, the system 400 may display indicators 672 (e.g., circles, but not limited to) to indicate that alert 671-n and alert 671-p have relatively higher severity levels compared to alert 671-m and alert 671- o.

[0162] In some embodiments, the system 400 may provide control actions associated with alerts 471, via the graphical visualizations. For example, referring to FIG. 6B, in response to a user input (e.g., a mouse click, a touch input, hovering a mouse pointer) associated with alert 671-g, the system 400 may provide control actions at the asset 620-c4 (e.g., compressor) for addressing the alert 671-g.

[0163] In an example case with reference to FIG. 6B, the alert 671-g at the asset 620-c4 may be associated with a performance issue at the asset 620-c4, and further, the performance issue at the asset 620-c4 may be due to a performance issue at another of the assets 620 and / or impact performance at another of the assets 620. For example, the performance issue at the asset 620-c4 (e.g., compressor) may be interrelated with performance issues at the asset 620-al (e.g., H2 plant), the asset 620-d5 (e.g., pipeline H2 section 1), the asset 620-b4 (e.g., mixed salt process plant), the asset 620-d6 (e.g., pipeline MSP section 1), the asset 620-b2 (e.g., chilled ammonia process plant), and the asset 620-e9 (e.g., monitoring well west 4), which a user may identify based on the alerts 671 displayed by the system 400. The system 400 may provide control actions for the asset 620-c4 (e.g., compressor) and any of the asset 620-al (e.g., H2 plant), the asset 620-d5 (e.g., pipeline H2 section 1), the asset 620-b4 (e.g., mixed salt process plant), the asset 620-d6 (e.g., pipeline MSP section 1), the asset 620-b2 (e.g., chilled ammonia process plant), or the asset 620-e9 (e.g., monitoring well west 4).

[0164] Accordingly, for example, the system 400 may provide alerts 671 (and control actions) as applicable for an interconnected asset 620 which is contributing to a performance anomaly associated with another interconnected asset 620. Additionally, or alternatively, the system 400 may provide alerts 671 (and control actions) as applicable for an interconnected asset 620 which is impacted by a performance anomaly associated with another interconnected asset 620.71CCS-511081-WO-1 (BHI0576PCT4)

[0165] Referring back to FIG. 6C, in some aspects, the system 400 may display the indicators 672 described herein to differentiate whether an interconnected asset 620 is contributing to a performance anomaly associated with another interconnected asset 620. For example, the system 400 may display indicators 672 to indicate that performance anomalies associated with asset 620-c4 and / or asset 620-e6 are contributing to performance anomalies associated with asset 620-b4, asset 620-e, and / or asset 620-d7.

[0166] Aspects of the system 400 and techniques described herein provide features which overcome shortcomings associated with some other approaches and provide various advantages. For example, the creation of the digital representations (alerts visualization) by the system 100 as described herein supports improved response time, improved and more informed decision making, increased operational efficiency, enhanced communication & collaboration among users, advanced predictive maintenance, and increased safety.

[0167] According to one or more embodiments of the present disclosure, the system 400 may create the interactive 3D model for CCUS end-to-end operations at runtime.

[0168] As will be described herein, aspects of the system 400 overcome shortcomings associated with some approaches for modeling associated with CCUS operations. For example, although some approaches for modeling a CCUS infrastructure in 3D may include modeling assets such as, for example, emitters, capture plants, pipelines, compressors, and storage sites, the approaches fail to address the integration and optimization of the assets as a whole.

[0169] The systems and techniques described herein provide a solution which ties together alerts and risks associated with a CCUS value chain 415, as determined using on a digital replication (i.e., interconnected asset model 45 (digital twin), and provides the alerts and risks via a multi-dimensional graphical visualization of the digital replication.

[0170] Aspects of the system 400 provide a robust 3D model which improves the simulation and real-time operational dynamics and spatial interactions among the assets. The system 400 and techniques described herein provide advanced modelling techniques that enable improved visualization and analysis of a CCUS value chain 415 (CCUS systems), leading to optimized efficiency, reduce operational costs, and improved carbon capture and storage outcomes.

[0171] In accordance with one or more embodiments of the present disclosure, the system 400 and techniques described herein encompass advanced real-time software with simulation that integrates with the 3D model to simulate operational scenarios, system71CCS-511081-WO-1 (BHI0576PCT4) dynamics, alerts, and risks. By providing visual representations of simulated operational scenarios, system dynamics, alerts, and risks (and / or actual real-time operational scenarios, system dynamics, alerts, and risks), the system 400 provides tools equipping a user with an improved understanding of the interactions between components and opportunities for identifying optimization opportunities.

[0172] In some aspects the system 400 and techniques described herein may support displaying or visualizing, via the digital representation 700, information such as, for example, statuses associated with a monitoring system (e.g., functioning, not functioning, monitoring, not monitoring, or the like) corresponding to a given interconnected asset. In some examples, the information may include a status (e.g., functional, not functioning, or the like) associated with a given well (e.g., an injection well, a monitoring well, or the like). In some examples, the information may include a performance status (e.g., performance below threshold, performance above threshold, or the like) associated with a given interconnected asset.

[0173] The system 400 and techniques described herein support the real-time data integration on the 3D model to highlight anomalies that lie within an entire system (e.g., CCUS value chain 415), and by incorporating real-time data into the 3D model, the 3D model has improved accuracy and an increased reflection of actual performance. Non-limiting examples of incorporating real-time data may include linking the 3D model with sensors and monitoring systems that provide live data on operational conditions. This designed 3D model in accordance with example aspects of the present disclosure improves the user interface of the 3D model, facilitating a higher effectiveness associated with interaction and analysis of the 3D model and the system (e.g., CCUS value chain 415).

[0174] In accordance with one or more embodiments of the present disclosure, the system 400 may integrate the 3D model as designed with real-time data within the application to dynamically visualize the project hierarchy based on the counts of assets in terms of nodes and node connections. The 3D model helps end users understand the issue propagation by connected assets seamlessly via visualization. Embodiments of the present disclosure support complete customization of the 3D model based on end user’s specifications and criteria.

[0175] The 3D model completely supports the CO2 flow and analysis via simulation techniques, such as, for example, dynamic fluid flow within the model. Accordingly, for example, such simulation techniques and analysis support prediction of system behavior under differential conditions. The 3D model is completely updatable via71CCS-511081-WO-1 (BHI0576PCT4) interactions via a user interface (e.g., user interface 110), which supports effective planning of an operations strategy by a user.

[0176] Aspects of the system 400 and techniques described herein provide features which overcome shortcomings associated with some other approaches and provide various advantages. For example, the system 400 is capable of upgraded modelling techniques compared to other approaches. As described herein, the system 400 incorporates sophisticated modelling techniques, such as, for example, computational fluid dynamics (CFD) and finite element analysis (FEA), to simulate and analyze complex interactions within a CCUS system (e.g., CCUS value chain 415). These modeling techniques support improved optimization of the design and operation of various components. The 3D model supports development and testing of different operational scenarios within the 3D model to identify the most efficient configurations and operational strategies. The system 400 supports relatively fast rendering speeds via a modeling application and viewer software which promotes annotations for user notes with preferences capabilities.

[0177] In accordance with one or more embodiments of the present disclosure, the systems and techniques described herein may support features for switching between displaying a given view (e.g., dashboard 200, recording log of example 300, digital representation 500, digital representation 600, digital representation 700) and / or displaying any combination of view simultaneously, based on a user input or other criteria.

[0178] It is understood that embodiments of the present disclosure are capable of being implemented in conjunction with any suitable type of computing environment now known or later developed. For example, FIG. 8 depicts a block diagram of a processing system 800, which can be used for implementing the techniques described herein. For example, aspects described herein of the systems described herein (e.g., system 100, system 400) may be implemented by the processing system 800.

[0179] In examples, processing system 800 has one or more central processing units (processors) 821a, 821b, 821c, etc. (collectively or generically referred to as processor(s) 821 and / or as processing device(s)). In aspects of the present disclosure, each processor 821 can include a reduced instruction set computer (RISC) microprocessor. Processors 821 are coupled to system memory (e.g., random access memory (RAM) 824) and various other components via a system bus 833. Read only memory (ROM) 822 is coupled to system bus 33 and can include a basic input / output system (BIOS), which controls certain basic functions of processing system 800.71CCS-511081-WO-1 (BHI0576PCT4)

[0180] Further illustrated are an input / output (I / O) adapter 827 and a communications adapter 826 coupled to system bus 833. I / O adapter 827 can be a small computer system interface (SCSI) adapter that communicates with a hard disk 823 and / or a tape storage drive 825 or any other similar component. I / O adapter 827, hard disk 823, and tape storage drive 825 are collectively referred to herein as mass storage 834. Operating system 840 for execution on processing system 800 can be stored in mass storage 834. A network adapter 826 interconnects system bus 833 with an outside network 836 enabling processing system 800 to communicate with other such systems.

[0181] A display (e.g., a display monitor) 835 is connected to system bus 833 by display adaptor 832, which can include a graphics adapter to improve the performance of graphics intensive applications and a video controller. In one aspect of the present disclosure, adapters 826, 827, and / or 832 can be connected to one or more I / O busses that are connected to system bus 833 via an intermediate bus bridge (not shown). Suitable I / O buses for connecting peripheral devices such as hard disk controllers, network adapters, and graphics adapters typically include common protocols, such as the Peripheral Component Interconnect (PCI). Additional input / output devices are shown as connected to system bus 833 via user interface adapter 828 and display adapter 832. A keyboard 829, mouse 830, and speaker 831 can be interconnected to system bus 833 via user interface adapter 828, which can include, for example, a Super I / O chip integrating multiple device adapters into a single integrated circuit.

[0182] In some aspects of the present disclosure, processing system 800 includes a graphics processing unit 837. Graphics processing unit 837 is a specialized electronic circuit designed to manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display. In general, graphics processing unit 837 is very efficient at manipulating computer graphics and image processing and has a highly parallel structure that makes it more effective than general-purpose CPUs for algorithms where processing of large blocks of data is done in parallel.

[0183] Thus, as configured herein, processing system 800 includes processing capability in the form of processors 821, storage capability including system memory (e.g., RAM 824), and mass storage 834, input means such as keyboard 829 and mouse 830, and output capability including speaker 831 and display 835. In some aspects of the present disclosure, a portion of system memory (e.g., RAM 824) and mass storage 834 collectively store an operating system 840 to coordinate the functions of the various components shown in processing system 800.71CCS-511081-WO-1 (BHI0576PCT4)

[0184] Embodiments of the present disclosure support computer implemented methods of real-time monitoring and root cause identification performed by the system 100 and processing system 800 described herein. In some aspects, the methods may be implemented by an integrated asset model supportive of real time monitoring of a CCUS value chain as described herein.

[0185] FIG. 9 illustrates an example flowchart of a method 900 in accordance with one or more embodiments of the present disclosure. The method 900 may be implemented by the example aspects of a system (e.g., system 100, system 400, system 800) as described herein.

[0186] At block 905, the method 900 includes processing, by a computing device, operational data associated with interconnected assets included in a CCUS value chain.

[0187] In some aspects, the operational data includes real-time operational data obtained by one or more sensors associated with the interconnected assets; and the computer-implemented method further includes generating the real-time alarm data and the alert based applying an alert rule to the real-time operational data.

[0188] At block 910, the method 900 includes generating a digital representation of the CCUS value chain based on processing the operational data.

[0189] At block 915, the method 900 includes mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain.

[0190] At block 920, the method 900 includes setting a mode associated with displaying the digital representation, based on an alert included in the real-time alarm data and a type of the alert, where the mode includes a 2D display mode or a 3D display mode.

[0191] In some aspects, the alert includes an indication of one or more of: an interconnected asset which is associated with the alert and included among the interconnected assets; and an equipment component included among a set of equipment components associated with the interconnected asset, where the alert is associated with the equipment component.

[0192] In some aspects, the 2D mode includes a schematic representation of the CCUS value chain; and the 3D mode includes a spatial representation of the CCUS value chain.

[0193] At block 925, the method 900 includes displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.71CCS-511081-WO-1 (BHI0576PCT4)

[0194] In some aspects, the method 900 may include providing a notification associated with the alert corresponding to an interconnected asset of the interconnected assets, where the notification includes a link associated with displaying the graphical visualization; and processing a user input associated with the notification, where displaying the graphical visualization according the mode is based on processing the user input.

[0195] In some aspects, the method 900 may include processing, by a machine learning model, one or more of: the operational data, where the operational data includes: real-time operational data obtained by one or more sensors associated with the interconnected assets; and historical operational data associated with the interconnected assets; and the realtime alarm data, where setting the mode is based on processing the one or more of the operational data and the real-time alarm data by the machine learning model.

[0196] In some aspects, the method 900 may include modifying the mode based on a user input.

[0197] In some aspects, the method 900 may include displaying a second alert via the graphical visualization, where the second alert indicates: a second interconnected asset which is contributing to a performance anomaly associated with the interconnected asset; and a second performance anomaly associated with the second interconnected asset.

[0198] In some aspects, the method 900 may include displaying a third alert via the graphical visualization, where the third alert indicates: a third interconnected asset which is impacted by one or more of the performance anomaly associated with the interconnected asset and the second performance anomaly associated with the second interconnected asset; and a third performance anomaly associated with the second interconnected asset.

[0199] In some aspects, the graphical visualization may include graphical representations of the interconnected assets; and the computer- implemented method further includes displaying, based on the mapping of the real-time alarm data, an alert indicator at one or more of: a graphical representation of an interconnected asset represented in the graphical visualization; and a graphical representation of an equipment component associated with the interconnected asset.

[0200] In some aspects, displaying the graphical visualization may include displaying, in the graphical visualization, based on applying a display filter against respective asset types of the interconnected assets, at least one of: a subset of the interconnected assets; and respective identifiers of the subset of the interconnected assets.71CCS-511081-WO-1 (BHI0576PCT4)

[0201] In some aspects, applying the display filter associated with displaying the graphical visualization is based on a target asset type indicated in a user input.

[0202] In some aspects, the method 900 may include identifying an interconnected asset associated with the alert from among the interconnected assets, based on the mapping of the real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; and determining an asset type of the interconnected asset, where applying the display filter associated with displaying the graphical visualization is based on determining the asset type of the interconnected asset.

[0203] In some aspects, the method 900 may include displaying a severity level of the alert; and providing one or more control actions associated with the alert, where the one or more control actions are further associated with one or more of: an interconnected asset associated with the alert; a second interconnected asset causing the alert; and a third interconnected asset impacted by the alert.

[0204] In some aspects, the method 900 may include displaying temporal information associated with the alert; and displaying operational data of an interconnected asset associated with the alert with respect to the temporal information, where the operational data includes a performance anomaly associated with the interconnected asset.

[0205] In some aspects, the method 900 may include setting the mode based on: a second alert provided by an interconnected asset included among the interconnected assets; and a type of the second alert; and displaying the second alert via the graphical visualization.

[0206] In the descriptions of the flowcharts herein, the operations may be performed in a different order than the order shown, or the operations may be performed in different orders or at different times. Certain operations may also be left out of the flowcharts, one or more operations may be repeated, or other operations may be added to the flowcharts.

[0207] Set forth below are some embodiments of the foregoing disclosure:

[0208] Embodiment 1. A computer-implemented method comprising: processing, by a computing device, operational data associated with interconnected assets comprised in a carbon capture, utilization, and sequestration (CCUS) value chain; generating a digital representation of the CCUS value chain based on processing the operational data; mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; setting a mode associated with displaying the digital representation, based on an alert comprised in the real-time alarm data and a type of the alert,71CCS-511081-WO-1 (BHI0576PCT4) wherein the mode comprises a two-dimensional (2D) display mode or a three-dimensional (3D) display mode; displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.

[0209] Embodiment 2. The computer-implemented method according to any prior embodiment, wherein: the operational data comprises real-time operational data obtained by one or more sensors associated with the interconnected assets; and the computer- implemented method further comprises generating the real-time alarm data and the alert based applying an alert rule to the real-time operational data.

[0210] Embodiment 3. The computer-implemented method according to any prior embodiment, further comprising: providing a notification associated with the alert corresponding to an interconnected asset of the interconnected assets, wherein the notification comprises a link associated with displaying the graphical visualization; and processing a user input associated with the notification, wherein displaying the graphical visualization according the mode is based on processing the user input.

[0211] Embodiment 4. The computer-implemented method according to any prior embodiment, further comprising processing, by a machine learning model, one or more of: the operational data, wherein the operational data comprises: real-time operational data obtained by one or more sensors associated with the interconnected assets; and historical operational data associated with the interconnected assets; and the real-time alarm data, wherein setting the mode is based on processing the one or more of the operational data and the real-time alarm data by the machine learning model.

[0212] Embodiment 5. The computer-implemented method according to any prior embodiment, further comprising modifying the mode based on a user input.

[0213] Embodiment 6. The computer-implemented method according to any prior embodiment, wherein the alert comprises an indication of one or more of: an interconnected asset which is associated with the alert and comprised among the interconnected assets; and an equipment component comprised among a set of equipment components associated with the interconnected asset, wherein the alert is associated with the equipment component.

[0214] Embodiment 7. The computer-implemented method according to any prior embodiment, further comprising displaying a second alert via the graphical visualization, wherein the second alert indicates: a second interconnected asset which is contributing to a performance anomaly associated with the interconnected asset; and a second performance anomaly associated with the second interconnected asset.71CCS-511081-WO-1 (BHI0576PCT4)

[0215] Embodiment 8. The computer-implemented method according to any prior embodiment, further comprising displaying a third alert via the graphical visualization, wherein the third alert indicates: a third interconnected asset which is impacted by one or more of the performance anomaly associated with the interconnected asset and the second performance anomaly associated with the second interconnected asset; and a third performance anomaly associated with the second interconnected asset.

[0216] Embodiment 9. The computer-implemented method according to any prior embodiment, wherein: the 2D mode comprises a schematic representation of the CCUS value chain; and the 3D mode comprises a spatial representation of the CCUS value chain.

[0217] Embodiment 10. The computer-implemented method according to any prior embodiment, wherein: the graphical visualization comprises graphical representations of the interconnected assets; and the computer-implemented method further comprises displaying, based on the mapping of the real-time alarm data, an alert indicator at one or more of: a graphical representation of an interconnected asset represented in the graphical visualization; and a graphical representation of an equipment component associated with the interconnected asset.

[0218] Embodiment 11. The computer-implemented method according to any prior embodiment, wherein displaying the graphical visualization comprises displaying, in the graphical visualization, based on applying a display filter against respective asset types of the interconnected assets, at least one of: a subset of the interconnected assets; and respective identifiers of the subset of the interconnected assets.

[0219] Embodiment 12. The computer-implemented method according to any prior embodiment, wherein applying the display filter associated with displaying the graphical visualization is based on a target asset type indicated in a user input.

[0220] Embodiment 13. The computer-implemented method according to any prior embodiment, further comprising: identifying an interconnected asset associated with the alert from among the interconnected assets, based on the mapping of the real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; and determining an asset type of the interconnected asset, wherein applying the display filter associated with displaying the graphical visualization is based on determining the asset type of the interconnected asset.

[0221] Embodiment 14. The computer-implemented method according to any prior embodiment, further comprising: displaying a severity level of the alert; and providing one or more control actions associated with the alert, wherein the one or more control actions71CCS-511081-WO-1 (BHI0576PCT4) are further associated with one or more of: an interconnected asset associated with the alert; a second interconnected asset causing the alert; and a third interconnected asset impacted by the alert.

[0222] Embodiment 15. The computer-implemented method according to any prior embodiment, further comprising: displaying temporal information associated with the alert; and displaying operational data of an interconnected asset associated with the alert with respect to the temporal information, wherein the operational data comprises a performance anomaly associated with the interconnected asset.

[0223] Embodiment 16. The computer-implemented method according to any prior embodiment, further comprising: setting the mode based on: a second alert provided by an interconnected asset comprised among the interconnected assets; and a type of the second alert; and displaying the second alert via the graphical visualization.

[0224] Embodiment 17. A system comprising: a computing device comprising a processor and a memory, wherein the memory comprises instructions stored thereon that, when executed by the processor, cause the processor to perform operations comprising: processing operational data associated with interconnected assets comprised in a carbon capture, utilization, and sequestration (CCUS) value chain; generating a digital representation of the CCUS value chain based on processing the operational data; mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; setting a mode associated with displaying the digital representation, based on an alert comprised in the real-time alarm data and a type of the alert, wherein the mode comprises a two-dimensional (2D) display mode or a three-dimensional (3D) display mode; displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.

[0225] Embodiment 18. The system according to any prior embodiment, wherein: the operational data comprises real-time operational data obtained by one or more sensors associated with the interconnected assets; and the instructions, when executed by the processor, further cause the processor to perform operations comprising generating the realtime alarm data and the alert based applying an alert rule to the real-time operational data.

[0226] Embodiment 19. The system according to any prior embodiment, wherein the instructions, when executed by the processor, further cause the processor to perform operations comprising: providing a notification associated with the alert corresponding to an interconnected asset of the interconnected assets, wherein the notification comprises a link associated with displaying the graphical visualization; and processing a user71CCS-511081-WO-1 (BHI0576PCT4) input associated with the notification, wherein displaying the graphical visualization according the mode is based on processing the user input.

[0227] Embodiment 20. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform operations comprising: processing, by a computing device, operational data associated with interconnected assets comprised in a carbon capture, utilization, and sequestration (CCUS) value chain; generating a digital representation of the CCUS value chain based on processing the operational data; mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; setting a mode associated with displaying the digital representation, based on an alert comprised in the real-time alarm data and a type of the alert, wherein the mode comprises a two-dimensional (2D) display mode or a three- dimensional (3D) display mode; displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.

[0228] The use of the terms “a” and “an” and “the” and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. Further, it should be noted that the terms “first,” “second,” and the like herein do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The terms “about”, “substantially” and “generally” are intended to include the degree of error associated with measurement of the particular quantity based upon the equipment available at the time of filing the application. For example, “about” and / or “substantially” and / or “generally” can include a range of ± 8% of a given value.

[0229] The teachings of the present disclosure may be used in a variety of well operations. These operations may involve using one or more treatment agents to treat a formation, the fluids resident in a formation, a borehole, and / or equipment in the borehole, such as production tubing. The treatment agents may be in the form of liquids, gases, solids, semi-solids, and mixtures thereof. Illustrative treatment agents include, but are not limited to, fracturing fluids, acids, steam, water, brine, anti-corrosion agents, cement, permeability modifiers, drilling muds, emulsifiers, demulsifiers, tracers, flow improvers etc. Illustrative well operations include, but are not limited to, hydraulic fracturing, stimulation, tracer injection, cleaning, acidizing, steam injection, water flooding, cementing, etc.CCS-511081-WO-1 (BHI0576PCT4) a. While the invention has been described with reference to an exemplary embodiment or embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed as the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the claims. Also, in the drawings and the description, there have been disclosed exemplary embodiments of the invention and, although specific terms may have been employed, they are unless otherwise stated used in a generic and descriptive sense only and not for purposes of limitation, the scope of the invention therefore not being so limited.

Claims

71CCS-511081-WO-1 (BHI0576PCT4)CLAIMSWhat is claimed is:

1. A computer-implemented method characterized by: processing, by a computing device, operational data (116) associated with interconnected assets (120) characterized by a carbon capture, utilization, and sequestration (CCUS) value chain (115); generating a digital representation (450, 500, 600, 601, 602, 700) of the CCUS value chain (115) based on processing the operational data (116); mapping real-time alarm data associated with the CCUS value chain (115) to the digital representation (450, 500, 600, 601, 602, 700) of the CCUS value chain (115); setting a mode associated with displaying the digital representation, based on an alert (471) comprised in the real-time alarm data and a type of the alert (471), wherein the mode is characterized by a two-dimensional (2D) display mode or a three-dimensional (3D) display mode; displaying a graphical visualization of the digital representation (450, 500, 600, 601, 602, 700) according the mode; and displaying the alert (471) via the graphical visualization.

2. The computer-implemented method of claim 1, wherein: the operational data (116) comprises real-time operational data obtained by one or more sensors (425, 625) associated with the interconnected assets (120, 420, 620); and the computer-implemented method further comprises generating the real-time alarm data and the alert based applying an alert rule (471) to the real-time operational data.

3. The computer-implemented method of claim 1, further comprising: providing a notification (476, 486) associated with the alert (471) corresponding to an interconnected asset (120) of the interconnected assets (120), wherein the notification (476, 486) comprises a link associated with displaying the graphical visualization; and processing a user input associated with the notification, wherein displaying the graphical visualization according the mode is based on processing the user input.

4. The computer-implemented method of claim 1 , further comprising processing, by a machine learning model, one or more of: the operational data, wherein the operational data comprises: real-time operational data obtained by one or more sensors associated with the interconnected assets; and71CCS-511081-WO-1 (BHI0576PCT4) historical operational data associated with the interconnected assets; and the real-time alarm data, wherein setting the mode is based on processing the one or more of the operational data and the real-time alarm data by the machine learning model.

5. The computer-implemented method of claim 1, further comprising modifying the mode based on a user input.

6. The computer-implemented method of claim 1, wherein the alert comprises an indication of one or more of: an interconnected asset which is associated with the alert and comprised among the interconnected assets; and an equipment component comprised among a set of equipment components associated with the interconnected asset, wherein the alert is associated with the equipment component.

7. The computer-implemented method of claim 6, further comprising: displaying a second alert via the graphical visualization, wherein the second alert indicates: a second interconnected asset which is contributing to a performance anomaly associated with the interconnected asset; and a second performance anomaly associated with the second interconnected asset; and displaying a third alert via the graphical visualization, wherein the third alert indicates: a third interconnected asset which is impacted by one or more of the performance anomaly associated with the interconnected asset and the second performance anomaly associated with the second interconnected asset; and a third performance anomaly associated with the second interconnected asset.

8. The computer-implemented method of claim 1, wherein: the graphical visualization comprises graphical representations of the interconnected assets; and the computer-implemented method further comprises displaying, based on the mapping of the real-time alarm data, an alert indicator at one or more of: a graphical representation of an interconnected asset represented in the graphical visualization; and a graphical representation of an equipment component associated with the interconnected asset.71CCS-511081-WO-1 (BHI0576PCT4)9. The computer-implemented method of claim 1, wherein displaying the graphical visualization comprises displaying, in the graphical visualization, based on applying a display filter against respective asset types of the interconnected assets, at least one of: a subset of the interconnected assets; and respective identifiers of the subset of the interconnected assets.

10. The computer-implemented method of claim 9, wherein applying the display filter associated with displaying the graphical visualization is based on a target asset type indicated in a user input.

11. The computer-implemented method of claim 9, further comprising: identifying an interconnected asset associated with the alert from among the interconnected assets, based on the mapping of the real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; and determining an asset type of the interconnected asset, wherein applying the display filter associated with displaying the graphical visualization is based on determining the asset type of the interconnected asset.

12. The computer-implemented method of claim 1, further comprising: displaying a severity level of the alert; providing one or more control actions associated with the alert, wherein the one or more control actions are further associated with one or more of: an interconnected asset associated with the alert; a second interconnected asset causing the alert; and a third interconnected asset impacted by the alert; displaying temporal information associated with the alert; and displaying operational data of one or more interconnected assets associated with the alert with respect to the temporal information, wherein the operational data comprises a performance anomaly associated with the one or more interconnected assets.

13. The computer-implemented method of claim 1, further comprising: setting the mode based on: a second alert provided by an interconnected asset comprised among the interconnected assets; and a type of the second alert; and71CCS-511081-WO-1 (BHI0576PCT4) displaying the second alert via the graphical visualization.

14. A system comprising: a computing device comprising a processor and a memory, wherein the memory comprises instructions stored thereon that, when executed by the processor, cause the processor to perform operations comprising: processing operational data associated with interconnected assets comprised in a carbon capture, utilization, and sequestration (CCUS) value chain; generating a digital representation of the CCUS value chain based on processing the operational data; mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; setting a mode associated with displaying the digital representation, based on an alert comprised in the real-time alarm data and a type of the alert, wherein the mode comprises a two-dimensional (2D) display mode or a three-dimensional (3D) display mode; displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.

15. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform operations characterized by: processing, by a computing device, operational data associated with interconnected assets characterized by a carbon capture, utilization, and sequestration (CCUS) value chain; generating a digital representation of the CCUS value chain based on processing the operational data; mapping real-time alarm data associated with the CCUS value chain to the digital representation of the CCUS value chain; setting a mode associated with displaying the digital representation, based on an alert characterized by the real-time alarm data and a type of the alert, wherein the mode is characterized by a two-dimensional (2D) display mode or a three-dimensional (3D) display mode; displaying a graphical visualization of the digital representation according the mode; and displaying the alert via the graphical visualization.

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