Success Path: The Secret Methodology to Priority and Probability Assessment for High Reliability Offshore Operation

Abstract Proper risk assessment involves prioritization and probability, which are themselves a form of uncertainty evaluation. This paper illustrates development of a methodology where a powerful multiple-criteria decision analysis technique known as "Success Path" could further improved the risk assessment of complex offshore operation in a high risk & high rewards environment. Traditional probability of failure analysis forces decision-maker to converge vague judgment to single numeric preferences in order to estimate high reliability offshore operation. The final resultant of alternatives cannot be tested for statistical significance of and it lacks systematic approach to capture all categories of uncertainties. To overcome the above limitation, this paper demonstrates a modified analytical process, which incorporated uncertainty dealing with human and organizational factors. The proposed method in this work can offer improved assessment for generating mutually exclusive path sets that assure the system's successful operation. The "Success Path" method have been applied in a variety of situation involving risk and uncertainty in different aspects of offshore oil and gas operation. It is generally useful in such cases to carry out the evaluation over a period of time as project evolves and pass certain phase of the operation. The proposed approach (Success Path), used in the present paper could be used as one of the techniques for making concept maintenance or modification evaluations. This technique is enhancing the capability of taking into consideration different categories of uncertainties both qualitatively, and quantitatively. This paper will present novel method that can be of benefit to the petroleum industry in the following areas: Facilitates consensus, generate new insights and provide more confidence in making decision during the critical phases of offshore oil and gas operation Provides a systematic approach that can test the alternative paths for statistical significance. Incorporate extrinsic uncertainties such as human and organizational factors.