Subsea Autonomous Vessel Simulator – Demonstrating the Effectiveness of AI with Advanced Decision Techniques

  • Brown, David (PI)

    Project Details

    Description

    Much of the oil and gas infrastructure is underwater and difficult to access. The undersea environment is very harsh with multiple challenges for stakeholders such as accurate underwater navigation, location of key infrastructure and the need to automatically monitor the condition of the pipelines. Currently, semiautonomous underwater vehicles (AUV) are capable of descending to great depths to attempt to follow pipelines & power cables. However, the vast amounts of data collected is too much for traditional analysis technique sin terms of quantity but also time sensitivity. This means it is difficult for end users to see value in the data and how it could benefit the ir operations. Using environmental and mapping data from NOC, and pipeline infrastructure data from TD, a realistic simulation of pipeline infrastructure underwater will be developed. An AUV will be simulated, along with sensor data from TD, and AI models will be implemented to automatically analyse this AUV sensor data to show visually how early warning of faults can be provided as well as optimised decision making to determine the most cost/time effective response. This demonstrator can be shown to funding agencies and key stakeholders to find partners for future bids in this area.
    StatusActive
    Effective start/end date18/10/21 → …

    Fingerprint

    Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.