Prioritization of environmental issues in offshore oil and gas operations: A hybrid approach using fuzzy inference system and fuzzy analytic hierarchy process

To implement an environmental management system (EMS) in offshore oil and gas (OOG) operations, decision makers always encounter a problem of how to prioritize the environmental issues for establishing an environmental policy. Analytic hierarchy process (AHP) is a popular method to perform multi-attribute decision-making to solve this problem. In order to deal with vague information, various fuzzy AHP methods have been proposed. However, these methods suffer four serious limitations: (1) there is a tremendous computational requirement; (2) sometimes only triangular fuzzy numbers can be used; (3) adding or deleting criteria/attributes is not easy to operate in the algorithm; (4) inconsistent judgments is more likely to be expected with fuzzy numbers. This paper proposes a hybrid approach using fuzzy inference system (FIS) and fuzzy AHP which not only eliminates the above limitations but also serves as a robust tool for the prioritization of environmental issues in OOG operations. In this approach, a five-level hierarchy is developed. The highest level of the hierarchy corresponds to the goal - prioritization of significance of environmental issues, and the lowest level corresponds to environmental issues, whereas intermediate levels correspond to major concerns (environmental risks) and sub-parameters of risk. The FIS is applied at the lower levels of the hierarchy to infer the major risk parameters. After this, the scores representing the extent of risk are calculated. Fuzzy AHP is used at the higher levels to synthesize the Significance Scores that will help to prioritize environmental issues. An application of the proposed approach is demonstrated through a numerical example.