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FlatFish Resident AUV: Leading the Autonomy Era for Subsea Oil and Gas Operations
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Challenged to remain competitive in a low oil price environment whilst navigating the energy transition, the industry is now seeking ways to evolve operations through digitalisation. Robotics has already enabled an evolution of the Oil and Gas industry by enabling deepwater operations through the deployment of ROVs. Now the industry seeks to reduce the unit operating costs of offshore facilities whilst improving safety and environmental performance. Autonomous underwater vehicles (AUVs) such as FlatFish can help the industry achieve this objective by reshaping the concept of operations for subsea surveillance.
Oil and gas operators stand to benefit from robotic technologies which have been successfully adopted in other industries such as aerospace and defence. Technologies that can perform autonomous subsea inspections and interventions: faster, safer, and cheaper than traditional approaches. Robotics and AI (Artificial Inteligence) can play a fundamental role in increasing the competitiveness of the oil and gas industry, the prize for rapid deployment into daily subsea surveillance tasks means not only the unlocking of deep water ventures, but also the safe life extension of offshore assets.
The FlatFish project is a leading example of how technology development in robotics and AI can contribute to the reduction of inspection costs, improve the accessibility of offshore installations and reduce safety risks. The technology development program has shown the capabilities of FlatFish AUV such as: performing autonomous visual inspection, tracking pipelines, hovering around structures such as tree systems and manifolds and returning to the docking station for recharging and data transfer.
The development and pre-production qualification are in the final stage, next steps are the industrialization and commercialization. FlatFish is a leading example of where Robotics and AI can contribute towards a reduction in subsea inspection costs.
Title: FlatFish Resident AUV: Leading the Autonomy Era for Subsea Oil and Gas Operations
Description:
Challenged to remain competitive in a low oil price environment whilst navigating the energy transition, the industry is now seeking ways to evolve operations through digitalisation.
Robotics has already enabled an evolution of the Oil and Gas industry by enabling deepwater operations through the deployment of ROVs.
Now the industry seeks to reduce the unit operating costs of offshore facilities whilst improving safety and environmental performance.
Autonomous underwater vehicles (AUVs) such as FlatFish can help the industry achieve this objective by reshaping the concept of operations for subsea surveillance.
Oil and gas operators stand to benefit from robotic technologies which have been successfully adopted in other industries such as aerospace and defence.
Technologies that can perform autonomous subsea inspections and interventions: faster, safer, and cheaper than traditional approaches.
Robotics and AI (Artificial Inteligence) can play a fundamental role in increasing the competitiveness of the oil and gas industry, the prize for rapid deployment into daily subsea surveillance tasks means not only the unlocking of deep water ventures, but also the safe life extension of offshore assets.
The FlatFish project is a leading example of how technology development in robotics and AI can contribute to the reduction of inspection costs, improve the accessibility of offshore installations and reduce safety risks.
The technology development program has shown the capabilities of FlatFish AUV such as: performing autonomous visual inspection, tracking pipelines, hovering around structures such as tree systems and manifolds and returning to the docking station for recharging and data transfer.
The development and pre-production qualification are in the final stage, next steps are the industrialization and commercialization.
FlatFish is a leading example of where Robotics and AI can contribute towards a reduction in subsea inspection costs.
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