Collision between FPSO and shuttle tanker in tandem offloading operation has caused a growing concern in the North Sea. Several recent contact incidents between FPSO/FSU and shuttle tanker have clearly demonstrated a high likelihood of contact between vessels in tandem offloading. The large masses involved, i.e. high potential impact energy, make the collision risk large. Traditional ship/platform collision risk model may not be effective for tandem offloading operation. Further more in a broader sense, offshore quantitative risk analyses generally focus more on technical aspects, little on human aspects. This leads to a hardware-centered risk control approach, which may not be effective in the face of risks in complex marine operations. A collision risk modeling approach for FPSO and tanker offloading operation is presented in this paper. The collision frequency is modeled in the initiating stage and the recovery stage. In the initiating stage, this paper is focused on tanker powered forward movement (PFM) scenarios. The initiation of tanker PFM involves a complex man machine interaction. The risk model is set up which integrates technical events, human actions and their interaction in the initiating stage. This model guides us further to identify the two failure prone situations where man machine interaction happened and resulted in most collision incidents. The study to quantitatively analyze these failure prone situations and minimize their occurrence is presented in a companion paper OMAE 28101. In the recovery stage, this paper is focused on the tanker initiated recovery. Based on the proposed probabilistic model for the recovery stage, possible recovery actions are identified and the event development is modeled from initiation of tanker PFM to the final outcome, i.e. collision or near miss. The success of recovery is analyzed from the human action timing perspective. Based on qualitative and preliminary quantitative analyses, recommendations are made to reduce the failure of recovery in design and operation.
Iterative Bayesian Estimation of Navigation Performance Modeled by a Mixture of Gaussian and Laplace Distributions for the Application of Collision Risk Modeling