Digital twin model improves riser integrity management

Many of the advances in riser assessment are part of the industry’s growing trend toward digitalization and the digital oilfield.

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David F. Renzi, Stress Engineering Services

Deepwater riser systems consist of conduits (typically pipe) used for the safe transportation of materials (primarily fluids and gases) between the seafloor and a floating host platform. In the US Gulf of Mexico, deepwater drilling riser systems have been in use since the 1970s, and deepwater production riser systems have been in use since the late 1980s. Riser systems may vary in functionality and configuration, but the primary goal of the riser design process is always to ensure safe operation during the expected life of the system under the conditions it is likely to experience.

Due to the specialized nature of risers, the software used to evaluate designs and the methodologies used for riser integrity management (IM) and maintenance are also specialized. Many of the advances in riser assessment are part of the industry’s growing trend toward digitalization and the digital oilfield. These digitalization tools are typically focused on IM and maintenance, but also have direct applicability to design, fabrication, installation, and decommissioning.

Riser integrity management solutions

Much of the emphasis behind the industry’s push toward digitalization has focused on integrity management solutions to facilitate operations and maintenance. Many of these technologies and methodologies are being developed for larger, more publicized areas of the industry and can be easily applied for riser systems. For example, digital twins, machine learning, and artificial intelligence. Of particular importance are the capabilities of a fully developed digital twin system. A digital twin is an up-to-date virtual representation of the system that provides functionality for performing assessments using either historical, real-time, or forecast conditions. Assessment may be performed using traditional physics-based analytical models, data science techniques such as machine learning, or a combination of both methods. A fully developed digital twin also incorporates a data management system, allowing for documentation and data relevant to the riser systems to be stored and accessed in a convenient and user-friendly manner.

Digital twins enhance facility management

The phrase “digital twin” represents the merging of data with a virtual model of an asset, whether it be a component, process, or system. The condition and performance of the asset can then be assessed in virtual space using the model. Digital twin models are ideally suited for asset integrity management and operational guidance of floating production systems (FPS).

FPS asset integrity management programs are dependent on a combination of inspection, analysis, and measured data. These three data sets are often used separately. Digital twin models allow for the integration of all available data. The existing digital twin models developed for FPSs have so far been focused on facilitating generic inspection programs or evaluating the response of hull and deck structures. However, a new digital twin model has been developed that focuses on the global performance (riser, mooring/tendon, and motion response) of the FPS. The FPS digital twin model combines, in a fully automated fashion, measured data and analytical tools for more representative and complete insight into behavior of floating production systems. The digital twin model provides opportunities to maximize production, help plan future events, and reduce downtime and instrumentation and data analysis demands. It also helps in the development of risk-based inspection (RBI) and condition-based maintenance (CBM) programs, provide fault detection, and enhance continued service evaluation efforts.

The digital twin model provides continuous monitoring and simulation of the FPS generating a virtual data stream for all components, including areas that cannot be instrumented. Key performance indicators (KPIs) are generated and tracked automatically for immediate performance feedback. Continuous monitoring and automated data analysis can identify instrumentation failures, anomalies, and responses above identified threshold values. Extreme values of some responses can be used to verify regulatory compliance. For example, extreme mooring tensions for synthetic mooring systems can be compared to allowable levels to ensure additional insert testing is not required. Automatically generated fatigue damage accumulation, which can be determined using a combination of simulated response and measured response, can be leveraged for integrity management assessments, tieback/expansion assessments, and continued service assessments.

Appropriate IM and maintenance strategies

The recent release of API RP 2RIM, Integrity Management of Risers from Floating Production Systems, in September 2019 provides further guidance for appropriate IM and maintenance strategies. The generic IM process described by RP 2RIM is shown in the first figure. Data describing the condition of the riser system is gathered and then evaluated to identify anomalies. A strategy is developed to address any concerns identified and then a program is developed to implement any necessary mitigations. The cycle is continuous for the life of the riser system. The data describing the condition of the riser system can be:

• Documentation and drawings from the design, fabrication, installation, or operations phase

• Inspection data and findings

• Instrumentation data from sensors

• Analysis data from design or assessments.

The fully developed digital twin referenced above can contain or provide all of the data required for the integrity management process.

Effects on riser design and assessment

Many of the advancements made in the software used to evaluate riser behavior consist of refinements to better capture nuances of behavior. For example, capturing non-linear flex joint rotational stiffness behavior instead of assuming a constant stiffness or better modeling of the interaction between the riser and the seafloor. Additional advances have been made in software user-friendliness with respect to model creation, review of results, and ease of performing multiple analysis types. Examples of this include incorporation into primary riser analysis packages of previously separate software to evaluate vortex induced vibration. Unfortunately, the specialized nature of riser software and its inherently limited customer base have caused advancement of riser design software to naturally lag behind the general state of the art in engineering analysis tools.

The new technology being developed as part of the industry’s digitalization efforts can be used to implement some well-established tools to increase the versatility and efficiency of performing riser assessment.

Life extension concerns

Many of the floating production facilities in the Gulf of Mexico were installed in the late 1990s and early 2000s. These facilities are rapidly approaching the end of their design life (typically 20 years). The strategy for justifying continued service past the end of the original design life (so-called “life extension”) is similar to the strategy defined in an integrity management program. Thus, the integrity management benefits of digital twins are directly applicable to life extension concerns as well. In addition to providing the history of the design, fabrication, installation, inspection and maintenance programs, the analytical capabilities of the digital twin allow for accurate assessments of riser fatigue damage accumulation. The second figure shows typical parameters used to define sea states, wave height and wave period. A comparison is provided between the typical design and assessment assumption (shown in red) and the data available to a digital twin model (shown in blue).

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Case studies have shown an increase in calculated fatigue life of 30%-400% when using actual measured conditions instead of the typical assessment assumptions. It is noteworthy that these improvements leverage the same analysis methodologies that have been verified over decades of industry use. The fatigue life increase in these case studies is recognized solely by performing a large number of analysis cases that more accurately represent the day-to-day conditions experienced by the riser system. Additional refinements can be realized by revisiting other typical assessment assumptions regarding hydrodynamic coefficients, effectiveness of vortex-induced-vibration suppression, and marine growth characterization.

Hurricane season planning activities

Most operators rely on a marine operations manual containing information largely generated during the design phase of a floating facility. The design phase typically considers a range of conditions meant to represent the lower and upper bounds of the asset configuration. For example, a minimum riser and maximum riser condition may be evaluated. Or a minimum topsides vertical center of gravity (VCG) and maximum topsides VCG may be evaluated. The operational guidance is then developed based on the worst-case response of all these various conditions. However, the as-is condition of a facility is seldom well represented by the extreme bounding conditions. These assumptions directly affect predicted motion behavior, therefore affecting the predicted response of all other components, including the riser systems. A digital twin represents the best-known (and up-to-date) condition of the facility and can be used to determine the system response to expected or historical environmental and operational loads. This capability can be leveraged in many ways to provide operational guidance during hurricane season:

1. Evaluation of response due to extreme event conditions based on pre-determined metocean criteria (e.g., a 100-yr hurricane as defined in API RP 2MET)

2. Predicted response due to named storms (e.g., using forecasted conditions of a hurricane moving into and through the Gulf of Mexico)

3. Measured response of a hurricane event experienced by the facility.

The operator can use the response of the as-is system to hurricane events to optimize asset integrity management and operational plans. The response due to pre-determined metocean criteria can guide long-term plans, while the response for particular events will guide short-term plans. The primary benefits are derived from:

1. Determining the ideal evacuation condition of the facility to minimize loading of components

2. Understanding the strength and fatigue utilization of the floating system and components during hurricane events.

Evacuation procedures typically consist of adjusting mooring line or tendon tensions, re-positioning the floating system, adjusting top-tensioned riser tensions, securing a drilling rig (mechanical lockdown), and re-ballasting or offloading equipment to maintain desired weight and VCG conditions. These procedures can be optimized based on expected environmental conditions and as-is facility conditions, allowing those activities that are necessary to maintain asset integrity to be prioritized.

Determining which components and locations are critical in terms of strength and fatigue utilization is a long-term asset integrity management activity. Determining system response during hurricane events is a portion of this activity. Identifying the actual utilization of components during hurricane events experienced by the system allows for more accurate understanding asset behavior. This understanding then informs the development of risk-based inspection plans and condition-based maintenance programs.

Conclusions

While the industry’s fundamental understanding of the physics of riser behavior has not significantly changed over the past decades, we have greatly improved our ability to perform assessments and manage data. One tool for doing this is a fully developed digital twin capable of providing all the data that is required in the integrity management process. Digital twins can provide system information not only for real-time conditions, but also for past and future conditions. The large computational effort represented by requiring robust physics-based modeling in the digital twin can be accomplished in near-real-time by incorporating time-tested analysis techniques and leveraging advances in computing technology. These capabilities can be leveraged for many benefits, one of which is maintaining riser integrity during hurricane events. •   

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