QUANTIFICATION OF RISKS ASSOCIATED WITH A REPRESENTATIVE PRODUCTION WELL IN THE GULF OF MEXICO

After Macondo incident a great effort is under way to improve the safety of deepwater drilling and production operations and enhance the capabilities of different well barrier to stop the oil spill on its earliest stages. This study is a part of that collective effort to make offshore operations safe and decrease the associated risks. The main objective of this study is to quantify and categorize the risk associated with a representative well in the Gulf of Mexico during its normal production operations. In order to achieve an appropriate balance between safety and economics of deepwater oil and gas operations, Quantitative Risk Assessment (QRA) techniques can be successfully used. Quantified risk is computed from the product of blowout frequency and volume of oil spilled as a consequence. Blowout frequency is calculated from Fault Tree Analysis (FTA) and spilled oil volume is estimated from simulating multiphase fluid flow and heat transfer in wellbores. A large number wells are completed with some sort of bottom hole sand control elements to prevent production of sand. The failure of these control elements may have severe consequence and in some cases may result in uncontrolled hydrocarbon flow to the environment as well. A representative production well from the Mississippi Canyon in the Gulf of Mexico is selected for the for quantitative risk assessment (QRA) analysis. The well is completed with cased hole gravel pack and with sand control elements in place. The representative reservoir properties for this well are selected from the literature and uncertainties in properties are accounted for by fitting lognormal distribution and carrying out Monte Carlo simulations. P50 value for the reservoir properties from Monte Carlo simulation is used to find worst case discharge rates by using a commercially available multiphase flow simulator with black oil model. A Fault Tree is constructed to find the blowout probability based on the equipment failure data. From the minimal cut set method the importance and sensitivity of different well bather is analyzed and most important areas to focus on are identified. The analysis showed that the constructed fault tree is most sensitive to sand screen failures, followed by subsea production tree and delayed response to a situation of immediate concern.