Risk-based selection of subsea leak detection technologies

Abstract

As traditional oil and gas deposits dwindle, non-traditional marginal reserves are being exploited to further economical and industrial needs worldwide. These reserves are often far from civilization, deep in the sea or in regions such as the Arctic. Now, more than ever, risks related to transporting oil and gas products need to be determined in these remote and sensitive ecological areas. Continuous monitoring of subsea pipelines is the best way to detect leaks quickly and prevent/minimize damage. A number of systems and technologies exist for this purpose. The present work describes two analytical approaches to making decisions related to best technology selection. The first is selecting the best available technology through researching desired parameters and conducting objective analysis. The second approach uses a risk-based methodology for identifying the best technology. The key focus of the present work is to develop a method to quantify uncertainties involved with leak detection technologies on subsea arctic pipelines applicable to harsh environments and use the quantified uncertainty in decision making. This thesis presents both approaches in detail and discusses their application to a real-life case study.