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SERPENT a great success but more help needed

Posted on 14 May 2009

“From a scientific point of view, we’re interested in everything,” said Mr Gates, who said SERPENT was a clear demonstration of how effective collaboration could be.

He pointed out that, whereas the scientific community possessed only about 20 remotely operated vehicles, the offshore industry has over 200 deepwater ROVs and more than 1,000 in total.

 Use of ROVs from drilling rigs has provided scientists many opportunities to view the deep-sea environment.

“As most of these vehicles are on site and used continually, there are at least 50 dives globally per day,” said Mr Gates. “This presents a huge amount of opportunity to view the deep-sea environment and its fauna.”

He said SERPENT was proving to be a very powerful tool, and even more so when combined with strategic sampling. This has enabled a substantial databank to be built over the past several years, generating valuable case studies.

Homing in on West of Shetland, where visual data gathering under the scheme has been relatively intensive, Mr Gates selected the TOTAL-operated Laggan gas discovery as a case study, comparing the impact of drilling disturbance on “megafauna” … basically fish and shellfish … over a decade or so.

He said there had been a high impact out to a radius of some 200 m on population densities immediately after drilling, and this brought an influx of scavengers. There were clear signs of recovery after two years and, beyond 100 m, little impact.

Ten years on from drilling, there was increased evidence of recovery, notably higher densities close to the well. Differences were not significant beyond 100 m, though cuttings were still obvious.

Mr Gates said everyone – scientists and the industry – still have a lot to learn and that ongoing visual assessments and continued presence was vital for understanding deepwater communities.

“Experiments will lead to future breakthroughs in understanding and, coupled with detailed knowledge of what is there, will eventually lead to prediction power.”

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