The subsidiary of Kraken Robotics Inc. (TSXV:$PNG), Kraken Robotic Systems Inc., has been awarded a contract for Newfoundland and Labrador’s offshore oil and gas sector. The highly coveted contract, priced at $750,000, is to help digitize integrated operations for the sector by developing underwater sensors and robotics.
Petroleum Research Newfoundland and Labrador (PRNL), InnovateNL, and its industry partners will be providing the funding. The contract begins in the fourth quarter of this year and will finish in quarter 4 for 2018.
“We are very pleased to win this contract as it enables us further entry into the oil and gas industry,” said President and CEO of Kraken, Karl Kenny. “The rapid progression of technology such as sensors, robotics, big data, and predictive analytics offer oil and gas operators the ability to digitize and automate high-cost, dangerous, and error-prone tasks. While digitalization offers many potential benefits in the upstream value chain, some of the biggest opportunities are in integrated operations, such as reducing unplanned downtime by enhancing asset integrity management.”
PRNL is also happy with the arrangement.
“PRNL is pleased to support Kraken’s initiatives in digitalization of the oil field. This project is consistent with our member’s pursuit of opportunities to gain competitive advantage by harnessing new technologies to improve operational efficiencies, increase cost savings, improve real-time understanding of operations and the environment, and reduce risk within Newfoundland and Labrador’s offshore environment,” said Alan Clarke, Chief Executive Officer of PRNL.
Kraken will be using its SeaVision™ 3D laser imaging sensor and underwater robotics technologies, along with cloud-based data analytics infrastructure, to help demonstrate an end-to-end digitalization methodology for subsea asset integrity management.
With the intended digitalization methodology, subsea assets will be connected with unprecedented visibility in a controlled and repeatable process, at any time and from any vendor. It will be able to capture holistic views of asset condition with predictive-based maintenance and will be able to optimize asset performance by balancing reliability, performance, and cost when defining maintenance strategies across operations.
This project hopes to improve the process for data collection, analysis, and predictive analytics in oil-field Inspection, Maintenance, and Repair. It hopes to showcase the next generation of 3D subsea imaging and asset inspection solution, generating millimeter resolution data.
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