More than 400 oil and gas fields have stopped producing in the last five years and, during 2018-22, analysts estimate USD32 billion to be spent on decommissioning. Shell, for example, is expected to book GBP1.152 billion on decommissioning in the North Sea before 2025, with the Brent field being the main driver, along with Pierce and Curlew.2
For ageing assets no longer producing at economically sustainable rates, identifying the right time, method and model for decommissioning is critical in managing the cost. Given there is no return on expenditure, it is now widely appreciated that procedure optimisation with early account for decommissioning can help to reduce the inevitable financial burden.
Sharing SIM data for decommissioning
A structural integrity management (SIM) system is already widely adopted by offshore assets’ operators. It ensures that assumptions made in the design phase of an asset are safely monitored and assessed from conception through to end of life. The assessments, according to API RP 2SIM, are continual with interactions broadly falling into four key areas: data collection, data evaluation, SIM strategy, and the inspection programme.
Over the past two decades, DNV GL’s Fixed and Floating Structures (FFS) team has been using the SIM system on more than thirty offshore assets worldwide.
A data management system (DMS), as shown in Figure 1, is the backbone of the SIM system. It is set up for archive and retrieval of structural and inspection data, collected during design, construction and operational stages of an asset. Boxes highlighted in blue are DMS components highly relevant for decommissioning.
Comparing tasks commonly associated with a decommissioning project, such as removal, lift and transportation, there are many areas in SIM DMS where efficiencies can be targeted during an asset’s operational life. Key areas such as weight control, knowledge of structural conditions, and information management are assessed.
For any asset to be decommissioned, adopting and maintaining a robust weight control procedure as early as possible can be vital in choosing the right decommissioning method, avoiding schedule delays and preventing cost escalation (Figure 2). For instance, when lifting methodology needs to be developed, if the weight of an asset is close to the capacity of the crane or the removal vessel, the completeness and credibility of existing weight records can play a vital role during the decision-making process.
DNVGL-RP-N102 is DNVGL’s latest code of practice for marine removal operations, providing guidelines on the level of allowance to be introduced for weight information.
Knowledge of Structural Condition
For integrity issues that are difficult to identify from a decommissioning survey, a sound anomaly management system and the resulting anomaly database can be a useful reference for any decommissioning project. Being a centralised database registering anomalies from all past inspections, it provides insight into the evolving history of an anomaly which can fed into the development of regular inspection plans as well as decommissioning planning.
As an example, during early consultation for the removal of a North Sea jacket, various possible methods were considered against the cost and schedule. Without the existence of an anomaly database, the asset owner would need to commission and wait for the results of a pre-decommissioning survey, which can cause lags in efficiency.
In another instance, loose bolts for a section of a J-tube close to the seabed were recorded in the anomaly database but missed from the commissioned subsea survey. Apart from safety implications, this margin of error can be reduced by an anomaly database, saving hundreds of man-hours, if not more.
Asset-specific knowledge, together with the weight database, can help minimise the efforts associated with weight reviews and offshore surveys.
Most aging assets have experienced modifications. For decommissioning, SIM providers are uniquely positioned to verify the records of all implemented modifications and identify key information relevant to the decommissioning exercise. Forward looking, SIM practitioners can review, justify and close-out incoming changes and make simultaneous updates to DMS components and structural model. This way, an up-to-date asset profile is ready-made for decommissioning.
Digital innovation is expected to play a stronger role in decommissioning projects. DNVGL is working with Rolls-Royce and the Norwegian University of Technology Science (NTNU) to develop the concept of Digital Twins, aiming for a cloud-based virtual representation of marine assets.
The creation of a global weight library is also underway to provide a valuable benchmark tool for decommissioning weight assessment. This will be available on Veracity3, an open and secure platform built by DNV GL, facilitating the exchange of datasets, APIs, applications and insights.