Flow Assurance (FA) has grown as a concern in deepwater developments and long distance hydrocarbon transportation. Main challenges related to flow assurance of remote systems are the risks of production loss due to equipment failure or flow line blockage due to hydrate formation or deposits.

The traditional way of addressing such problems has been to design production & transport systems and implement operating procedures to fully avoid events such as hydrate formation, wax precipitation and sand production. However, as the industry moves toward deeper and arctic waters, traditional solutions that entirely avoid flow assurance problems may not remain technically or economically feasible.

During a field development from the first front end engineering design (FEED) basis to the production close down, the knowledge of the input data and hence the expected outcome and performance will progress from an engineering qualified guess to more exact knowledge. The span of uncertainty will become smaller and smaller with knowledge and experience. The level of risk tied to the uncertainty is seldom aligned or balanced across technical disciplines and over the total life cycle of the enterprise. A decision maker assessing large projects will face problems when trying to rank the various solutions and development alternatives quantitatively.

The FAMUS methodology is a suitable tool for a decision maker who wants to quantitatively assess and compare FA design alternatives or how operational aspect will influence on total system performance. The approach opens up for an integration of adjacent elements influencing the production performance and identification of the risk elements. The approach will systematically preserve and accumulate the uncertainty, to gain control of the probabilistic room of outcome for solution or development alternative in question. The methodology identifies the risk / cost drivers and calculates cost / value of risk reduction and risk mitigation in a life cycle perspective. The FAMUS approach gives the decision maker a consistent probabilistic quantitative assessment of the concept alternatives under consideration.