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The Arctic is known for its abundant reserve of natural resources. Last decade has seen some exploration and production activities in this region. The assurance of safe operations in this region is a critical and challenging task because of the harsh environment, the remoteness of operation sites, the limited infrastructure, and resources available in response to emergent situations, the application of costly equipment and facilities, and the sensitive marine environment. For complex process systems operating in a harsh environment, the scope of conventional risk assessment is not enough because of the highly uncertain environment, and its impacts on equipment performance. Risk assessment needs to be extended to include both the pre-failure and the post-failure phases. Additionally, risk assessment approaches under normal operating, and environmental conditions may not be applicable in the Arctic regions with unique and uncertain characteristics of the harsh environment. Therefore, this study aims to develop a quantitative resilience assessment method for process units operating under Arctic extreme conditions. Dynamic Bayesian network (DBN) is applied to model the probabilistic relationships between causes and effects in a dynamic manner. The proposed method is applied to the resilience assessment of a separator (as part of an oil production system). The proposed approach will help reveal the critical operating parameters under extreme conditions for process units. It also helps identify potential design improvement to enhance process safety.

Using Aspen Plus, operating parameters of an existing triethylene glycol natural gas dehydration plant including the solvent circulation rate, stripping gas flow rate, regenerator reboiler duty, solvent temperature, absorber (contactor) pressure, flash unit pressure and regenerator pressure were optimized to reduce BTEX, VOCs and CO 2 emissions. The plant consists of an absorber, a flash tank, a stripper and a regenerator. Two thermodynamic models including PRMHV 2 and PSRK were utilized for this plant. The sensitivity analysis study was conducted using two methods, namely Method A and Method B. Method A considered the effect of an individual parameter on the emissions, while other parameters were set at their base case values. Method B studied the impact of a given parameter, while other parameters were at their optimum values. Using the two methods, BTEX emission reduced more than 40%, while VOCs and CO 2 emissions were decreased more than 60%. However, the moisture content of the dehydrated gas was higher when Method A was applied (249.9 × 10 −6 kg H 2 O/m 3 ) compared to Method B (65.7 × 10 −6 kg H 2 O/m 3 ). Method B was found to be a more precise approach to achieve the optimum plant operation.