SFI Smart Ocean

SFI Smart Ocean Contributions at the UTC Conference

SFI Smart Ocean  participated with two contributions at UTC – Underwater Technology Conference. PhD student Astrid Marie Skålvik from UiB presented «Smart subsea wireless sensing – Challenges, limitations, and promising measurement strategies for ensuring data quality and reliability», and our partners IMR and Aanderaa presented some of our results and plans in a poster in the exhibition area (can be seen below). Astrid Marie won the Best student paper award for her contribution.

 

Abstract for Astrid Marie Skålvik’s presentation

Smart subsea wireless sensing – Challenges, limitations, and promising measurement strategies for ensuring data quality and reliability

Subsea developments come with a need of monitoring conditions directly related to production, subsea structures (as integrity measurements, leakage) and effect on the environment (as noise, turbidity, polluting particles). Common for all these measurements is that they rely on subsea sensors installed in remote, harsh environments. Effective and safe operations both in petroleum, offshore wind, subsea mining and aquaculture depend on reliable information from the subsea sensors. Poor-quality data can result in sub-optimal resource management, production strategies or even serious incidents. Long-term measurements covering large underwater areas will rely on wireless sensors which can be deployed for several years or even decades, without possibilities for maintenance nor calibration.

We present an overview of factors which may affect the quality and reliability of underwater measurements as well as limitations related to power consumption and communication. A measurement strategy is presented to mitigate risks for measurement errors, relying on the use of smart sensors with self-validating, self-calibrating and self-diagnostics capacities. Signal processing and data-analysis performed by the sensor is found to be a key pre-requisite for obtaining and ensuring high-quality data. Combined with measurements of influencing parameters, internal references, and redundant measurements, this enables correction for sensor drift and environmental influences.

The key learning outcome of this presentation is how data-analysis, sensor design and measurement strategies lay the basis for reliable smart, wireless, autonomous sensors producing high-quality, high-accuracy data, even from remote subsea locations.