Parametric generation of explosion scenarios for quantitative risk assessment of gas explosion in offshore plants

In this study, probabilistic risk assessment has been carried out for the prediction of gas explosion loads due to hydrocarbon leaks and subsequent explosions in the topside of offshore platforms. In the initial phase of the risk assessment, the effect of various scenario parameters on the annual probability of gas explosion was quantified via a MATLAB code. For calculating the gas explosion frequency, the hydrocarbon leak frequencies and the ignition probabilities were derived from the HCR (HydroCarbon Release) database from the Health & Safety Executive (HSE, UK), and the IP (Ignition Probability) report from UKOOA (UK Offshore Operators Association), respectively. The MATLAB code has the algorithm to cope with the varying design practice in either Front End Engineering Design phase or detailed design phase. User‐definable parameter setup and spreadsheet data input provide the user with the flexibility in selecting relevant level of elaboration for such design parameters as the leak size distribution, the hydrocarbon composition, etc. These features of the code enable controlling the number of explosion scenarios without any parameter range remaining unaccounted for. The present MATLAB code has been applied to generate hydrocarbon leak scenarios and corresponding explosion probability for the topside process modules of a specific oil Floating Production, Storage and Offloading. Varying the number of cases for each parameter leads to the variation of the number of explosion scenarios selected, which are either 48 or 24 in the particular case. For each explosion scenario, the gas leak and explosion simulation was carried out using the FLame Acceleration Simulator (FLACS) commercial S/W package, giving rise to the annual probability of exceedance for the explosion overpressure. Discussion of the influence of explosion scenario selection method on the change of the overpressure exceedance curves is made. © 2016 American Institute of Chemical Engineers Process Saf Prog 36: 139–149, 2017