A stochastic programming approach for the optimization of gas detector placement in offshore platforms

Abstract In offshore platforms, effective gas detection system is an essential layer of protection for preventing potential gas release accident from turning to fire and explosion disasters. However, according to statistics the actual efficiency of gas detection systems is still unsatisfactory. In this work, a stochastic programming (SP) approach is proposed to arrange gas detectors in optimal places. Combined with meteorological data and the hydrocarbon releases (HCR) database, the equipment leakage scenarios are envisaged. The computational fluid dynamics (CFD) commercial code Ansys-Fluent is used to simulate selected scenarios and predict the consequences. With the objective of minimizing the cumulative risk of gas leakage scenarios, a stochastic mixed-integer linear programming formulation based on p-median value theorem is proposed. Then particle swarm optimization (PSO) algorithm is used to solve the optimization model. The gas detector placement optimization on an oil drilling production platform (DPP) is also carried out as a case example. This methodology can be used in the design phase of offshore platform and can hopefully enhance the performance of the gas detection system.