Drilling Risk Identification, Filtering, Ranking and Management

Yasseri, Sirous

doi:10.18869/acadpub.ijcoe.1.1.17

Drilling Risk Identification, Filtering, Ranking and Management

Author

Sirous Yasseri

Brunel University

10.18869/acadpub.ijcoe.1.1.17

Abstract

Drilling Operations are exposed to a variety of hazards, some of which may be location and activity dependent and each could pose different risk from different paths. Drilling operation may be vulnerable to hurricanes in one region and be exposed to Geohazards in another. However, there are other hazards, (e.g. corrosion, age degradation, poor maintenance), which equally affects every rig. Identifying what can go wrong and their likelihood and possible consequences provides insight into vulnerability of the operation and helps to generate mitigation options. Filtering and Ranking risk contributors enable to decide priorities and to focus on the most important risk contributors. This paper offers a framework to identify, assess, prioritize, and manage drilling risks, which includes: (1) a holistic approach to risk identification; (2) prioritization of a large number of risk influencing factors or risk scenarios; (3) structured elicitation of experts’ opinion and effective integration of experts judgment into qualitative and quantitative analyses to supplement limited data availability; (4) extreme and catastrophic event analysis; and (5) use of multi-objective framework to evaluate risk management priorities.

Keywords

20.1001.1.25382667.2017.2.1.3.7

References

1- Kaplan, S. and B.J. Garrick, B.J., On the Quantitative Definition of risk, 1981, Risk Analysis Vol. l (1), pp11-27, 1981.

2- Kaplan, S., Haimes, Y.Y. and Garrick, B.J., Fitting hierarchical holographic modelling (HHM) into the theory of scenario structuring and a refinement to the quantitative definition of risk, Risk Analysis, Vol.21 (5): pp 807-819, 2001.

3- Leveson N., Applying systems thinking to analyse and learn from events, Safety Science, Vol.49, pp 55–64, 2011.

4- Ouchi, F., A Literature Review on the Use of Expert Opinion in Probabilistic Risk Analysis, World Bank Policy Research Working Paper 3201, February 2004, last accessed 23/03/2015. http://wwwwds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2004/04/15/000009486_20040415130301/additional/115515322_20041117173031.pdf

5- Pitblado, R. and Nelson, W. R., Advanced Safety Barrier Management with Inclusion of Human and Organizational Aspects, Chemical engineering transactions Vol. 31, 2013. http://www.aidic.it/cet/13/31/056.pdf

6- Ramanathan, R. and Ganesh, L. S., Group preference aggregation methods employed in the AHP: an evaluation and an intrinsic process for deriving members, European Journal of Operational Research 79, 249–265, 1994.

7- Ramanathan, R., A note on the use of the analytic hierarchy process for environmental impact assessment R. Journal of Environmental Management Vol.63, pp 27–35, 2001.

8- Saaty, T.L., The analytic hierarchy process, New York- McGraw Hill 1980.

9- Saaty, T., How to make a decision: the analytic hierarchy process, European journal of operational Research, Vol. 48(1): 9-26, 1990.

10- Yasseri, S., Subsea technologies selection using analytic hierarchy process, International journal of underwater technology, Society for Underwater Technology, Volume 30, Number 3, pp. 151-164, 2012.