The Role of Autonomous Underwater Vehicles in Deepwater Life of Field Integrity Management

Abstract

Integrity Management of deepwater fields requires routine general visual inspections of critical infrastructure. To date the only means of conducting general visual inspection is through the use of ROVs. Deepwater ROV spreads are large and heavy requiring large support vessels with dynamic positioning capability and a significant number of personnel at sea. The capabilities of unmanned underwater vehicles have been enhanced through developments in Autonomous technology progressing to the point that autonomous underwater vehicles can now routinely conduct general visual inspection of subsea facilities. Benefits of Autonomous inspection include: Reduced cost of operations Faster inspection Automatic Change Detection Georegistered inspection data Simultaneous operations from a single support vessel Large standoff distances from the facility being inspected Increased safety of operations Reduced environmental impact Reduced specification requirements on support vessel o Smaller footprint o Dynamic Positioning not required 2 OTC 22438 o Fewer personnel at sea o Reduced Mobilization Costs o Faster response to emergency inspections Lockheed Martin's Marlin ™ Autonomous Underwater Vehicle recently completed a series of tests in the US Gulf of Mexico demonstrating autonomous change detection of a fixed offshore platform. Examples of the Marlin's capabilities from these tests are illustrated. Deepwater Field Owners now have a new tool that can bring significant operational and financial benefits to Life of Field Integrity Management.

AUV-Based 3D Laser Inspection for Structural Integrity Management in Deepwater Fields

“…high precision georegistered image points underwater • At a rate of 20,000 points per second • While traveling at approximately two knots • Processing the data in real time • Building a 3D image on-the-fly Using software algorithms developed for LiDARs mounted on land-based vehicles, Lockheed Martin engineers have produced astonishing 3D models from point clouds generated using the Coda Octopus Echoscope sonar [1][4].…”