Managing Director at Eye-bot Aerial Solutions, David Palmerton, has analysed the current decommissioning ambit within the Gulf of America, the challenges posed by the vast scope of end-of-life work to carry out, and how robotics and data-driven technologies play an integral role in transforming the market.
In the Gulf of America, a significant number of offshore oil and gas wells and platforms are overdue for decommissioning. According to the Bureau of Safety and Environmental Enforcement (BSEE), there are 1,366 offshore structures, with 273 having submitted decommissioning applications and 451 located on terminated leases, of which only 192 have pending decommissioning applications. These delays pose environmental risks, including potential leaks, structural failures, and threats to marine ecosystems as well as increased costs for operators and regulators.
The financial burden of decommissioning these structures is substantial, potentially reaching billions of dollars, with concerns that taxpayers may ultimately bear the cost if companies fail to meet their obligations. A significant portion of these wells are classified as orphaned or abandoned, meaning the companies responsible for their decommissioning no longer exist or lack the financial capability to carry out the required work.
Under regulations set out by the Interior Department, administered by BOEM and BSEE, operators are jointly and severally liable for decommissioning obligations. Even if a company transfers its lease to another operator, it remains responsible for ensuring that all abandonment and removal obligations are fulfilled. Operators must complete decommissioning within one year of lease termination or within three to five years of a structure becoming idle. However, with aging infrastructure and a backlog of overdue removals, BSEE has emphasised the need for proactive compliance throughout the life of a lease.
Leveraging drones and robotics
Given the magnitude of overdue decommissioning in the Gulf, oil and gas operators are turning to advanced technology to enhance pre-decommissioning inspections and streamline project planning. Drones, robotics, and AI-powered digital modelling are now at the forefront of assessing the structural integrity of offshore platforms, pipelines, and subsea infrastructure before decommissioning begins.
By deploying aerial and underwater drones, operators can conduct high-resolution LiDAR scans, ultrasonic inspections, and photogrammetry surveys without sending personnel into hazardous environments. These drone-based inspections provide real-time structural data, detecting corrosion, metal fatigue, and structural integrity risks before dismantling begins.
Simultaneously, AI-driven Building Information Modelling (BIM) and Simultaneous Localised and Mapping (SLAM)-based 3D mapping allow engineers to simulate decommissioning scenarios, optimise removal sequences and enhance worker safety.
The integration of data-driven decommissioning is reshaping offshore well abandonment practices, making projects safer, more efficient, and cost-effective. With thousands of overdue structures requiring removal, these technological advancements offer a critical solution for tackling the Gulf's growing decommissioning backlog.
Advanced digital twin modelling
The process begins with autonomous aerial and underwater drones conducting high-resolution scans of the platform. These drones are equipped with LiDAR, thermal imaging, and photogrammetry sensors, capable of capturing structural details down to the millimetre. The data collected is processed using SLAM technology, generating a real-time digital twin of the platform.
This BIM model provides:
- Structural integrity analysis – identifies areas of structural weakness.
- Corrosion mapping – detects deterioration in steel and welds.
- Failure point identification – highlights at-risk areas to prevent collapses.
- Real-time stress redistribution simulations – predicts how deconstruction will impact platform stability.
For areas of the platform that are potentially unsafe for human entry, such as confined interiors or corroded sections, a quadruped robotic system is deployed. This autonomous robotic platform is equipped with a LiDAR camera, thermal sensors, and AI-driven navigation, allowing it to traverse hazardous environments, capture high-resolution scans and transmit critical data to the BIM model.
By integrating robotic mobility solutions, teams can inspect structural conditions without exposing personnel to risk, ensuring a complete and accurate dataset for decommissioning planning.
Optimising the decommissioning sequence
The digital twin model allows engineers to simulate decommissioning scenarios before physical execution, ensuring a safe and efficient process. Potential structural instabilities can be identified, allowing engineers to plan necessary reinforcement measures before deconstruction.
Key considerations for deconstruction planning include:
- Modular removal strategies – if the platform was originally installed in separate lifts, digital twin modelling integrates the original installation sequence to optimise the removal sequence.
- Weight distribution and balance – AI-driven BIM models simulate the centre of gravity for each lift, reducing risks of imbalance.
- Real-time structural analysis – drones and LiDAR-equipped quadrupeds scan and analyse structural integrity, dynamically updating the BIM model.
- AI-driven dismantling sequences – AI simulations determine the most efficient cutting and lifting sequence, reducing structural failure and minimising environmental impact.
Precision execution with robotics and automation
The decommissioning process is executed with robotic precision, leveraging drones, autonomous robotics and AI-driven modelling.
Some of the execution processes include:
- Autonomous drones conduct thermal and ultrasonic testing of the remaining load-bearing structures before cutting operations.
- Underwater remotely operated vehicles (ROVs) ensure pipelines are safely sealed and detached.
- Heavy-lift vessels, guided by real-time BIM data, dismantle the platform in a controlled sequence.
- Quadruped robotic systems navigate interior spaces, providing real-time updates on stability and potential hazards.
- Continuous LiDAR monitoring updates the digital twin, ensuring execution aligns with predicted structural responses.
A number of positive results can come from AI-driven decommissioning processes, including a 40% reduction in project time, enhanced worker safety, greater compliance with both regulatory and environmental standards, and increased material recycling and disposal.
The future of offshore decommissioning
As drone technology, AI-driven modelling, and autonomous robotics advance, offshore platform decommissioning is shifting toward zero-contact, data-driven precision. The integration of real-time digital twin modelling, predictive analytics, and autonomous robotic inspections marks the beginning of a fully AI-driven offshore decommissioning era.
This article was authored by David Palmerton, Managing Director at Eye-bot Aerial Solutions.
