Overview of Robotic Applications on Offshore OGI IMR: Splash Zone

Abstract

Inspection, Maintenance and Repair (IMR) are tasks constantly performed by the Oil and Gas Industry (OGI) in offshore platforms, risers, submerged oil wells and pipelines. Many of these underwater operations can be dangerous and tiring when done by human divers. Remotely Operated Vehicles (ROVs) and crawlers are increasingly employed to perform underwater IMR, commissioning and decommissioning operations with obvious advantages in reducing human risks and allowing longer operating time. These vehicles still require extensive infrastructure to work, such as human operators and support vessels. Autonomous Underwater Vehicles (AUVs) enable many exploratory and survey missions to happen without constant human intervention. However, intervention capable AUVs are still subject to further research, as the incorporation of technologies needed to guarantee the correct execution of these tasks are not yet completely developed. This work reviews the current literature on the application of underwater robotics in IMR tasks in offshore OGI, with great interest in the splash zone, a highly dynamic region around the surface of the ocean, in which corrosion and structural stress are common. Moreover, the formation of biofouling on the exposed surfaces of structures and equipment is also a usual problem in this region. Several Non-Destructive Tests (NDTs), cleaning and intervention techniques are routinely employed in the splash zone and many of them are still done by human divers. Besides presenting an overview of such techniques, we sought to correlate their application with robotic systems, in order to identify potential applications and future directions for the development of new solutions for the offshore OGI. Through our survey of current underwater robotic solutions and other factors, like the push for underwater Oil and Gas (O&G) resource exploration and the lack of more pervasive automation of existing IMR operations, the need for greater research and development of autonomous robotic systems for underwater IMR can be inferred.