Operation and Maintenance (O&M) Risks Management Based on the Hazard and Effect Management Index (HEMI) in an Oilfield

الموضوعات :

Ali Askari ¹ , Hasan Maihanparast ² , Laila Mahdinasab ³ , Ali Salehi sahlabadi ⁴ , Masoud Davoodi ⁵ , Mohammad Nemati ⁶

1 - Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
2 - Department of Health, Safety, and Environment (HSE), OICO Safety Division Shift Supervisor, Azar Oilfield, Ilam, Iran
3 - Department of Work and Knowledge, Work and Education School, Mehran Education Office, Ilam, Iran
4 - Workplace Health Promotion Research Center, Department of Occupational Health and Safety at Work, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
5 - Department of Health, Safety, and Environment (HSE), OICO HSE Manager, Azar Oilfield, Ilam, Iran
6 - Department of Planning and project control, OICO Planning Division, Azar oilfield, Ilam, Iran

تاريخ الإرسال : 04 الإثنين , شوال, 1444 تاريخ التأكيد : 29 الأحد , ذو القعدة, 1444 تاريخ الإصدار : 19 الأحد , رجب, 1446

الکلمات المفتاحية: Risk Priority Number, Risk Assessment, Oil and Gas Industry, HARPI, HMEI,

ملخص المقالة :

One of the main factors in achieving safety management and safety objectives is designing in addition, applying specific risk evaluation techniques. The present study takes this approach to manage the risks related to non-routine activities and hazardous work inOperation and Maintenance (O&M) project inan oilfield. This semi-quantitative and descriptive study was conducted at the Sarvak Azar oil field in Iran in 2023. A combination of the Hazard and Effect Management Process (HEMP) and the Hazard and Risk Prioritization Index (HARPI) are used to assess the risk of activities. Then, to simplify managers' decisions to implement control measures, final risk scores reported based on the Pareto principle. The results show that based on the conventional use of RPN, T11 (Desalters bypassing; 850), has the highest risk, and T1 (PSV installation on the off spec tank; 30) activity has the lowest calculated risk. However, based on the HEMI, T12 (Electrical substation commissioning; 749.7) has the highest calculated risk, and the lowest estimated risk score is associated with T7 (Loading chemical barrels and collecting pallets and empty barrels; 25.5). Furthermore, a survey of the standard deviation of the data shows that among the factors added to the risk assessment, involved people number (Pi), is more influential than other factors. The study showed we could optimize the conventional use of the risk priority number (RPN) with slight modifications. Changes made while maintaining the simplicity and applicability of the method can improve the accuracy of the priority set by the RPN.

المصادر:

1. Moro L.F.L, 2003. Process technology in the petroleum refining industry—current situation and future trends. Computers & Chemical Engineering . 27(8-9), 1303-1305.
2. Kulkarni S.J., 2017. Safety and hazards in petroleum industries: research, studies and surveys. International Journal of Petroleum and Petrochemical Engineering. 3(1), 31-34.
3. Dahl Ø., Kongsvik T., 2018. Safety climate and mindful safety practices in the oil and gas industry. J Safety Res. 64, 29-36. DOI: 10.1016/j.jsr.2017.12.009 From NLM.
4. Askari A., Abadi A.S.S., Golbabaei F., Jafarzadeh E., Aazam K., 2022. Cancer and Noncancer Risk Assessment for Workers Exposed to the Chemical Pollutants in Ahvaz Gas Stations, Iran. International Journal of Environmental Health Engineering. 11(1), 19.
5. Samimi A., 2020. Risk management in oil and gas refineries. Progress in Chemical and Biochemical Research. 3(2), 140-146.
6. Osinovskaya I., 2015. Prinyatie upravlencheskih reshenij v usloviyah riska (Management decision-making under risk). Economy and Entrepreneurship. 8, 767-770.
7. Carvalho F., Melo R., 2015. Stability and reproducibility of semi-quantitative risk assessment methods within the occupational health and safety scope. Work . 51(3), 591-600.
8. Zhou L.F., Fang T., Hua Z., Yuan W. M., Mo H., Zhang M.B., 2017. Research progress in occupational health risk assessment methods in China. Biomedical and Environmental Sciences. 30(8), 616-622.
9. Tian F., Zhang M., Zhou L., Zou H., Wang A., Hao M., 2018. Qualitative and quantitative differences between common occupational health risk assessment models in typical industries. Journal of Occupational Health. 60(5), 337-347.
10. Hubbard D.W., 2020. The failure of risk management: Why it's broken and how to fix it, 2nd ed., Wiley & Sons: New York, John. pp. 98-123.
11. Parsamehr M., Perera U.S., Dodanwala T.C., Perera, P., Ruparathna R.A., 2022. review of construction management challenges and BIM-based solutions: perspectives from the schedule, cost, quality, and safety management. Asian Journal of Civil Engineering .1-37.
12. Chang K.H., Cheng C.H.A., 2010. risk assessment methodology using intuitionistic fuzzy set in FMEA. International Journal of Systems Science. 41(12), 1457-1471.
13. Askari A., Poursadeqiyan M., Sahl Abadi A.S., Mahdinasab L., Farhadi A.R., 2023. Semi-quantitative risk assessment for workers exposed to occupational harmful agents in an oilfield in Iran. Work . DOI: 10.3233/wor-220077 From NLM.
14. Vulanović S., Delić M., Kamberović B., Beker I., Lalić B., 2020. Integrated management systems based on risk assessment: Methodology development and case studies. Advances in Production Engineering & Management. 15(1), 93-106.
15. Baryannis G., Validi S., Dani S., Antoniou G., 2019. Supply chain risk management and artificial intelligence: state of the art and future research directions. International Journal of Production Research. 57 (7), 2179-2202.
16. Saisandhiya N., Babu M.K.V., 2020. Hazard identification and risk assessment in petrochemical industry. Int J Res Appl Sci Eng Technol. 8(9), 778-783.
17. Askari A., Sepahvand A., Davoodi M., Mokhtari F., Salehi-Sahlabadi A., 2022. Noise Control Measures Prioritization and Job Groups Identification Exposed to Hearing Impairments to Implement a Hearing Conservation Program in the Azar Oil Field. Journal of Safety Promotion and Injury Prevention. 10(2),176-187.
18. Askari A., Abadi A.S.S., Alinia A., Pourjaafar M., Haghighi A.H., Pirposhteh E.A., 2021. Prioritizing and Providing Sound Pollution Control Strategies at the CPF of North Azadegan Oilfield Project. Sound & Vibration. 55(4), 329-341.
19. Mousavi S.M., Naeini M.J., Haghighat M., Yazdanirad S., 2021. Prioritization of Noise Control Solutions in an Oil Refinery Using the Noise Control Priority Index. Jundishapur Journal of Health Sciences.13(3), 1-12.
20. Liu H.C., Liu L., Liu N., 2013. Risk evaluation approaches in failure mode and effects analysis: A literature review. Expert Systems with Applications: An International Journal. 40(2), 828-838.
21. Mikulak R.J., McDermott R., Beauregard M., 2017. The basics of FMEA, 2nd ed.,CRC press, New York, John. pp. 35-48.
22. Stamatis D.H., 2003. Failure mode and effect analysis: FMEA from theory to execution, 2nd ed, Quality Press, Milwaukee, pp. 72-83.
23. Mahoney J.F., Yeralan S., 2019. Dimensional Analysis. Procedia Manufacturing. 29th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2019), June 24-28, 2019, Limerick, Ireland. 38, 694-701.