The role of marine science in managing environmental risk offshore

Author:

Hardisty Paul E,Dommisse Michaela,Cooper Karin E

Abstract

Australia’s marine economy is worth over $70 billion a year, of which offshore oil and gas is a big contributor. Operating safely and in an environmentally sustainable way is vital to the long-term success of Australia’s offshore petroleum sector. Making good risk management decisions depends on a sound understanding of the complex marine environments in which they operate. Key emerging challenges include the effects of noise on marine life, decommissioning of offshore infrastructure, and the unprecedented rate of change in natural marine systems. The Australian Institute of Marine Science (AIMS) undertakes research that helps industry, regulators, government and the wider community to make informed decisions about the management of Australia’s marine estate. Working closely with industry and government partners, AIMS has established some of the world’s longest running and most comprehensive tropical marine monitoring programs. The regional baseline datasets span the subtropics of Western Australia, the North West and North Marine Regions, through to the Great Barrier Reef and the Coral Sea Marine Region. This unique repository of data and environmental intelligence allows quantification of system changes, modelling of anticipated future trends and impacts of development, and the development and testing of risk mitigation measures. Examples of research specifically tailored to meet the needs of the offshore oil and gas industry include recent projects in noise management, eco-toxicity and machine learning/automation. In each case, AIMS and its science partners worked with industry to develop research programs designed to help manage specific risks, or conduct work more efficiently and safely.

Publisher

CSIRO Publishing

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. For intelligent debugging management of offshore oil engineering with big data;Journal of Intelligent & Fuzzy Systems;2021-04-12

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