Abstract
Unplanned and uncontrolled releases of hazardous materials could result in major casualties and environment impact. Natural gas (sour) containing significant amounts of hydrogen sulfide is toxic, flammable and corrosive. Incidents like 2003 Kaixian blowout ("12.23 disaster") and 2015 Saskatchewan in Oil & Gas industry highlight the significance of conducting appropriate technical (safety) risk assessments and exercising effective risk management. It is estimated that for 90% of accidental releases of sour gas during pipeline transfer results toxic impacts as typical releases will not get immediately ignited. Lack of adequate information of the hazards and the lack of realistic estimate of the hydrogen sulfide toxic exposure zone are the main challenges in addressing the risk to public from sour natural gas.
The challenge risk analysts come across is the lack of guidance on appropriate tool and methodology to estimate the toxic impact zone following an accidental loss of containment. Dispersion following accidental release of high pressure and high flow rate sour gas in complex terrain should take account of multicomponent thermodynamics, terrain effect and the phase transitions. For selecting processing sites, pipeline routes etc., stakeholders require convincing results addressing the uncertainties. Simple correlation like Gaussian model alone is not considered as suitable and appropriate.
This paper is based on the academic research conducted to overcome the uncertainties in sour gas dispersion modelling. The focus of this research is on the dispersion following an accidental release from sour natural gas pipeline. The expansion following release and the initial air entrainment will be estimated to determine a range of cloud behaviour. Based on the sensitivity analysis, this paper provides guidance on the natural gas composition and the source term characteristics to define and select the appropriate dispersion phenomenon. The results and analysis will minimize the knowledge gap/uncertainty with the consequence calculations by identifying the key assumptions and parameters that should be put through sensitivity analysis.
