A neuro‐fuzzy theoretic approach to safety control at crude oil exploration platforms

Abstract

Purpose

The purpose of this paper is to present a new approach in viewing the control of safety at crude oil exploration platforms.

Design/methodology/approach

The approach utilized in this work is the fusion of artificial neural network and fuzzy logic. The approach is adopted in view of the better presentation of solutions to the safety control problem that neuro‐fuzzy exhibits. It is better than the individual application of either artificial neural network or fuzz logic to the problem at hand. The model captures uncertainties and imprecision that are prevalent in the quantification or data gathering stage of safety control measurement.

Findings

It was demonstrated that the application of neuro‐fuzzy is feasible. The results seem applicable to similar settings with similar system characteristics.

Practical implications

Since more confidence is obtained with the use of this more effective tool, there is improvement in decision making based on reliance on the model. Thus, the improved quality of decision made would positively affect lives of workers at the oil platforms or the materials or equipment used for exploration purposes.

Originality/value

The work is original in that it is the first time the neuro‐fuzzy methodology would be applied to offshore oil platform safety control.

Citation

Oke, S.A., Johnson, A.O. and Omogoroye, O.O. (2005), "A neuro‐fuzzy theoretic approach to safety control at crude oil exploration platforms", Disaster Prevention and Management, Vol. 14 No. 4, pp. 454-461. https://doi.org/10.1108/09653560510618302