In a Nutshell:
Just imagine the following: easily accessing all data sources and having them available to combine with other data streams from third parties or geographic information system (GIS) in order to estimate the lifetime of your assets and make strategic decisions based on all the collected data. This is exactly where the NIMA framework comes into play. In this article, we will explore how our colleagues have implemented this digital solution in the case of a mining company in our South America region.
Back in 2018, a South American client observed that fatigue-driven cracks could be a strong threat to their assets. After doing a field investigation and analysis of fatigue-driven cracks at the head affected zone (HAZ) of the long seam weld of the pipeline, this threat was confirmed as dangerous. After the inspections in 2018, the integrity of the pipeline was assessed and guaranteed by determining the “minimum fatigue life” for the pipeline. This is currently being calculated on a monthly basis to monitor performance.
ROSEN is currently leading a project to develop a digital “minimum fatigue life” model, which will predict and ultimately prevent an unexpected leak to occur due to the fatigue-driven crack failure mechanism as evaluated in 2018. The online model will give the operational and technical teams a real-time indication of the pipeline’s operational conditions and determine the optimum inspection intervals to guarantee pipe integrity.
In case of the South American operator, ROSEN offered to configure a platform following the client’s needs and considering data integration of pressure data on a daily basis. The NIMA framework is the digital solution for the implementation of comprehensive data and integrity management processes. It has been conceived as a bridge that connects data and knowledge with great flexibility to adapt to unique business and regulatory environments. The framework enables cross-department interaction and collaboration, powerful integrity calculations, and data handling and storage. With the assistance of the platform, operators can easily collect and use the recorded data for all assets and apply it to their unique process landscapes.
NIMA is an IM (integrity management) cloud-based solution in a secure cloud environment, including the corresponding process templates for estimating remaining fatigue life. Moreover, ROSEN is storing the data needed to run the process templates on a secure database, making sure this information is readily accessible and backed up frequently.
In the case of the South American operator, we developed two process templates for the NIMA IM Remaining Fatigue Life Estimation project: data loading and update, and remaining fatigue life prediction.
The data loading and update process contains six process steps:
- Data load review
- Validate inputs
- Calculate rainflow
- Calculate equivalent cycles
- Reading and joint matching
- Commit to database
These process steps guide the user through the required stages to review the integrity of the database, process the data uploaded to the file cloud via SSH File Transfer Protocol (SFTP) and commit the data to the database. Each stage contains a dashboard that allows the user to review and assure the quality of the data before finally committing the results to the database. Additionally, this process template is used when the user has to update incorrect data within the database and/or when new pressure files have to be generated and uploaded.
Step By Step
The remaining fatigue life prediction process template contains five process steps:
- Cycles comparison
- Remaining Life – minimum last three months
- Remaining Life – average last three months
- Remaining Life – minimum representative period
- Remaining Life – average representative period
These five process steps analyze the results stored in the database in order to estimate the cycle count to date and the predicted remaining fatigue life based on maximum and average cycling. This process template provides a workflow to track the remaining fatigue life of joints. It also offers a means to predict remaining life into the future in terms of years using representative cycling. There are two steps to calculating the remaining life. The first step is to convert reported pressures to equivalent cycles and store the information in a database. The second step predicts the remaining fatigue life based on the calculated equivalent cycles stored in the database.
The first predictions are made using the maximum and average cycling during the last three months. The minimum remaining life uses the worst-case monthly cycling from the last three months as a representative cycling profile to predict the remaining fatigue life on a joint-by-joint basis. The average cycling uses the average monthly cycling from the last three months to predict the remaining fatigue life. Furthermore, the user can select a range of representative dates to predict the remaining fatigue life.
Get Everyone On Board
As part of the NIMA implementation, ROSEN is performing online training sessions for the whole integrity team. They include user training, IT infrastructure (login, file cloud, online help), application basics (backstage view, configuration/dashboard view), managing projects (creation, data import, troubleshooting, outputs, etc.) and a NIMA technical support model.