GENETIC ALGORITHMS APPLIED TO THE CONCEPT OF RISK BASED INSPECTION (RBI): OPTIMIZATION OF INSPECTION PLANS

Abstract

Cost optimization of asset management is a central issue in the offshore Oil and Gas strategy, and risk-based approaches, such as Risk Based Inspection (RBI), have been more and more employed to assist the segment in the concretization of that goal. The inspection procedure aims mitigating the uncertainty related to the asset degradation state, enabling a better quantification of the actual damage, and, consequently, increases the accuracy of remaining life projections. Since the costs involved in offshore subsea inspections are considerable, inspection plans optimization plays a crucial role in the balance of an asset management program. The present paper discusses the use of genetic algorithms, GA, an optimization technique inspired in the concepts of evolutionary genetics, in the development of inspection plans for subsea equipment. The genes are defined in terms of two variables: the type of inspection to be done and in which period it occurs, considering a finite window of opportunities for inspection occurrences. The optimization process considers a multicriteria objective function, consisting in the dimensions time, cost, and risk. Finally, the application of the proposed methodology is illustrated by means of the elaboration of the inspection plans for a subsea Christmas-tree.