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Risk-Based Process Engineering Framework for Strengthening Reliability Across Complex Natural Gas Infrastructure Systems
Subject area: Science,Engineering and Technology · Area of research: Process Engineering Framework
Abstract
Natural gas infrastructure is a coupled system of wells, gathering lines, processing units, compressors, transmission pipelines, storage assets, metering stations, and distribution interfaces. Reliability failures within this system rarely arise from one technical defect. They emerge through interactions among degradation, process variability, protection-system performance, human decisions, organizational controls, and external hazards. Existing approaches often treat process safety, asset integrity, inspection, maintenance, and operational risk as separate programs. This paper develops a unified risk-based process engineering framework that connects these programs through a common decision structure. The study uses an integrative review of standards and scholarly literature published to date. The synthesis draws on risk management, risk-based inspection, functional safety, pipeline integrity management, barrier theory, human factors, and reliability engineering. The proposed framework contains eight linked functions: system definition, hazard identification, consequence modelling, failure-likelihood assessment, barrier evaluation, risk aggregation, intervention selection, and performance learning. A bow-tie representation connects initiating causes, preventive barriers, loss-of-containment events, mitigative barriers, and consequences. A dynamic risk register then links each scenario to operating limits, inspection findings, maintenance tasks, management-of-change actions, and leading indicators. The framework replaces isolated equipment rankings with system-level prioritization and treats uncertainty as a decision variable. It also introduces reliability, safety, environmental, and economic criteria into one intervention portfolio. The paper contributes a practical architecture for allocating engineering attention across heterogeneous gas assets while preserving traceability from hazard evidence to action. The framework is suitable for conceptual testing, case-study validation, and later quantitative implementation. Its central proposition is that reliability improves when risk information moves continuously across lifecycle functions rather than remaining within specialist silos.
Keywords
natural gas infrastructure; risk-based process engineering; reliability; process safety; asset integrity; barrier management; risk-based inspection; functional safety
References
[1] Adaramola, T. S., Fadero, S., & Gideon, E. N. (2018). Predictive maintenance and condition monitoring in critical power and energy infrastructure. Iconic Research and Engineering Journals, 2(5), 454-477. https://doi.org/10.64388/IREV2I5-1722489
[2] Adeyelu, O. O. (2018). A predictive compliance monitoring framework for detecting systemic safety risks through aviation consumer complaint data. Iconic Research and Engineering Journals, 1(8), 250-276. https://doi.org/10.64388/IREV1I8-1718478
[3] Adeyelu, O. O. (2019). An adaptive safety management system implementation model for aerodromes in developing economy contexts. Iconic Research and Engineering Journals, 3(4), 628-654. https://doi.org/10.64388/IREV3I4-1718479
[4] Agbabiaka, J., Okonkwo, C. S., Ogunwole, O., Mayo, W., & Okeke, O. T. (2019). Supply chain risk management model for EPC and gas processing projects. Iconic Research and Engineering Journals, 3(2), 968-980. https://doi.org/10.64388/IREV3I2-1713124
[5] Ahammed, M. (1998). Probabilistic estimation of remaining life of a pipeline in the presence of active corrosion defects. International Journal of Pressure Vessels and Piping, 75(4), 321-329. https://doi.org/10.1016/S0308-0161(98)00006-4
[6] Akeju, B., Edivri, J., Ogbole, J. I., Okoruwa, P. O., Fadayomi, O., & Abolaji, T. O. (2018). Conceptual model for insider threat classification and risk modeling in complex digital systems. Iconic Research and Engineering Journals, 1(9), 476-492. https://doi.org/10.64388/IREV1I9-1713778
[7] Akomolafe, O., & Agu, M. U. (2018). A conceptual model for enhancing internal audit quality through technology-enabled risk assessment frameworks. Iconic Research and Engineering Journals, 1(9), 458-475.
[8] Akomolafe, O., & Agu, M. U. (2019a). A conceptual framework for developing risk-based internal control models in the insurance and banking sectors. Iconic Research and Engineering Journals, 2(8), 335-354.
[9] Akomolafe, O., & Agu, M. U. (2019b). A review of data-driven risk evaluation models for emerging market financial institutions. Iconic Research and Engineering Journals, 3(6), 433-448.
[10] Akomolafe, O., & Agu, M. U. (2019c). Advances in financial resilience through integrated governance and compliance strategies. Iconic Research and Engineering Journals, 2(10), 607-620.
[11] Ale, B. J. M. (2005). Tolerable or acceptable: A comparison of risk regulation in the United Kingdom and in the Netherlands. Risk Analysis, 25(2), 231-241. https://doi.org/10.1111/j.1539-6924.2005.00585.x
[12] Allen, D. T., Pacsi, A. P., Sullivan, D. W., Zavala-Araiza, D., Harrison, M., Keen, K., Fraser, M. P., Hill, A. D., Sawyer, R. F., & Seinfeld, J. H. (2015). Methane emissions from process equipment at natural gas production sites in the United States: Pneumatic controllers. Environmental Science & Technology, 49(1), 633-640. https://doi.org/10.1021/es5040156
[13] Amayo, E. B. (2017). Multi algorithm of loss objective function of a single phase induction motor. International Journal of Development Research, 7(5), 12805-12810.
[14] Amayo, E. B., & Popoola, T. T. (2017a). Multi algorithm of weight objective function of a single phase induction motor. International Journal of Trend in Research and Development, 4(2), 184-188.
[15] Amayo, E. B., & Popoola, T. T. (2017b). Scientific study of telecommunication deployment in achieving quality network. International Journal of Trend in Research and Development, 4(5), 311-314.
[16] Amayo, E. B., Ubeku, E., & Oshevire, P. (2015). Multi algorithm of a single objective function of a single phase induction motor. Journal of Multidisciplinary Engineering Science and Technology, 2(12), 3400-3403.
[17] American Petroleum Institute. (2013). API Recommended Practice 1160: Managing system integrity for hazardous liquid pipelines (2nd ed.). API.
[18] American Petroleum Institute. (2014). API Standard 521: Pressure-relieving and depressuring systems (6th ed.). American Petroleum Institute.
[19] American Petroleum Institute. (2015). API Recommended Practice 1173: Pipeline safety management systems. API.
[20] American Petroleum Institute. (2016). API Recommended Practice 581: Risk-based inspection methodology (3rd ed.). American Petroleum Institute.
[21] American Petroleum Institute. (2016). API Standard 580: Risk-based inspection (3rd ed.). American Petroleum Institute.
[22] American Petroleum Institute. (2016a). API Recommended Practice 580: Risk-based inspection (3rd ed.). API.
[23] American Society of Mechanical Engineers. (2018). ASME B31.8S-2018: Managing system integrity of gas pipelines. ASME.
[24] Aminu-Ibrahim, A. Y., Ogbete, J. C., & Ambali, K. B. (2018). Developing sustainable diagnostic laboratory infrastructure models for emerging and resource constrained health systems. Iconic Research and Engineering Journals, 1(8), 118-132. https://doi.org/10.64388/IREV1I8-1713586
[25] Aminu-Ibrahim, A. Y., Ogbete, J. C., & Ambali, K. B. (2019). Capital project delivery models for high risk healthcare infrastructure in developing national health systems. Iconic Research and Engineering Journals, 2(10), 626-649. https://doi.org/10.64388/IREV2I10-1713588
[26] Aneke, O.B. & Adesemoye, A.C., 2019. Toward an Integrated Conceptual Framework for Traceability and Chain-of-Custody Integrity in Pharmaceutical Distribution. Iconic Research and Engineering Journals, 3(4), pp.655-672.
[27] Arumosoye, O. M., & Obriki, O. D. (2018). Development of an integrated heat stress risk conceptual model for industrial operations in extreme environments. Iconic Research and Engineering Journals, 1(12), 141-160. https://doi.org/10.64388/IREV1I12-1714415
[28] Arumosoye, O. M., & Obriki, O. D. (2019). Systematic review of near-miss and hazard observation data utilization in industrial safety management. Iconic Research and Engineering Journals, 3(2), 981-999. https://doi.org/10.64388/IREV3I2-1714417
[29] Askari, M., Aliofkhazraei, M., & Afroukhteh, S. (2019). A comprehensive review on internal corrosion and cracking of oil and gas pipelines. Journal of Natural Gas Science and Engineering, 71, 102971. https://doi.org/10.1016/j.jngse.2019.102971
[30] Atta, S., Asomani, E., & Adenuga, O. M. (2018). A systematic review of green corrosion inhibitors from agricultural extracts for mild steel protection in acidic and alkaline media. International Journal of Engineering and Modern Technology, 4(1), 64-97. https://doi.org/10.56201/ijemt.vol.4.no1.2018.pg64.97
[31] Aven, T. (2012). Foundations of risk analysis (2nd ed.). Wiley.
[32] Aven, T. (2016). Risk assessment and risk management: Review of recent advances on their foundation. European Journal of Operational Research, 253(1), 1-13.
[33] Aven, T., & Renn, O. (2010). Risk management and governance: Concepts, guidelines and applications. Springer.
[34] Aven, T., & Vinnem, J. E. (2007). Risk management: With applications from the offshore petroleum industry. Springer.
[35] Aven, T., & Zio, E. (2014). Foundational issues in risk assessment and risk management. Risk Analysis, 34(7), 1164-1172.
[36] Aye, P. A., & Tawose, O. M. (2016). Physiological responses of West African dwarf sheep fed graded levels of Gmelina arborea leaf and cassava peel concentrates under different management systems. Agriculture and Biology Journal of North America, 7(4), 185-195. https://doi.org/10.5251/abjna.2016.7.4.185.195
[37] Babadagli, T. (2005). Mature field development: A review. SPE Middle East Oil and Gas Show and Conference. Society of Petroleum Engineers. https://doi.org/10.2118/93884-MS
[38] Badmus, O., Dosunmu, A. A., & Ozowara, D. E. (2018). A systematic review of CI/CD pipeline strategies in Salesforce DevOps: Tools, practices, and deployment outcomes. Iconic Research and Engineering Journals, 2(6).
[39] Badmus, O., Dosunmu, A. A., & Ozowara, D. E. (2019a). A conceptual model for ETL design and data integration in Salesforce-centric enterprise architectures. Iconic Research and Engineering Journals, 3(5).
[40] Bagheri, M., Alamdari, A., & Davoudi, M. (2016). Quantitative risk assessment of sour gas transmission pipelines using computational fluid dynamics. Journal of Natural Gas Science and Engineering, 31, 108-118. https://doi.org/10.1016/j.jngse.2016.02.057
[41] Bahadori, A. (2014). Natural gas processing: Technology and engineering design. Gulf Professional Publishing.
[42] Balcombe, P., Anderson, K., Speirs, J., Brandon, N., & Hawkes, A. (2017). The natural gas supply chain: The importance of methane and carbon dioxide emissions. ACS Sustainable Chemistry & Engineering, 5(1), 3-20. https://doi.org/10.1021/acssuschemeng.6b00144
[43] Baybutt, P. (2015). A critique of the hazard and operability study. Journal of Loss Prevention in the Process Industries, 33, 52-58.
[44] Baybutt, P. (2018). The validity of engineering judgment and expert opinion in hazard and risk analysis: The influence of cognitive biases. Process Safety Progress, 37(2), 205-210.
[45] Bevilacqua, M., & Braglia, M. (2000). The analytic hierarchy process applied to maintenance strategy selection. Reliability Engineering & System Safety, 70(1), 71-83. https://doi.org/10.1016/S0951-8320(00)00047-8
[46] Bevilacqua, M., & Ciarapica, F. E. (2018). Human factor risk management in the process industry: A case study. Reliability Engineering & System Safety, 169, 149-159. https://doi.org/10.1016/j.ress.2017.08.013
[47] Bian, H., Xu, W., Li, X., & Qian, Y. (2011). A novel process for natural gas liquids recovery from oil field associated gas with liquefied natural gas cryogenic energy utilization. Chinese Journal of Chemical Engineering, 19(3), 452-461. https://doi.org/10.1016/S1004-9541(11)60006-2
[48] Boschee, P. (2012). Offshore asset integrity management: Advances with new technologies. Oil and Gas Facilities, 1(4), 16-20. https://doi.org/10.2118/0812-0016-OGF
[49] Bransby, M. (1999). The human contribution to safety: Designing alarm systems for reliable operator performance. Measurement and Control, 32(7), 209-213. https://doi.org/10.1177/002029409903200705
[50] Bresnen, M., Edelman, L., Newell, S., Scarbrough, H., & Swan, J. (2003). Social practices and the management of knowledge in project environments. International Journal of Project Management, 21(3), 157-166. https://doi.org/10.1016/S0263-7863(02)00090-X
[51] Cai, B., Liu, Y., Liu, Z., Tian, X., Dong, X., & Yu, S. (2012). Using Bayesian networks in reliability evaluation for subsea blowout preventer control system. Reliability Engineering & System Safety, 108, 32-41.
[52] Caleyo, F., Gonzalez, J. L., & Hallen, J. M. (2002). A study on the reliability assessment methodology for pipelines with active corrosion defects. International Journal of Pressure Vessels and Piping, 79(1), 77-86. https://doi.org/10.1016/S0308-0161(01)00124-7
[53] Center for Chemical Process Safety. (1992). Guidelines for hazard evaluation procedures (2nd ed.). American Institute of Chemical Engineers.
[54] Center for Chemical Process Safety. (1995). Guidelines for process safety documentation. American Institute of Chemical Engineers.
[55] Center for Chemical Process Safety. (2000). Guidelines for chemical process quantitative risk analysis (2nd ed.). American Institute of Chemical Engineers.
[56] Center for Chemical Process Safety. (2001). Layer of protection analysis: Simplified process risk assessment. American Institute of Chemical Engineers.
[57] Center for Chemical Process Safety. (2003). Guidelines for analyzing and managing the security vulnerabilities of fixed chemical sites. American Institute of Chemical Engineers.
[58] Center for Chemical Process Safety. (2007). Guidelines for risk based process safety. John Wiley & Sons.
[59] Center for Chemical Process Safety. (2007). Human factors methods for improving performance in the process industries. Wiley.
[60] Center for Chemical Process Safety. (2008). Guidelines for hazard evaluation procedures (3rd ed.). John Wiley & Sons.
[61] Center for Chemical Process Safety. (2008). Guidelines for the management of change for process safety. Wiley-AIChE. https://doi.org/10.1002/9780470924969
[62] Center for Chemical Process Safety. (2009). Guidelines for developing quantitative safety risk criteria. Wiley.
[63] Center for Chemical Process Safety. (2010). Guidelines for process safety metrics. John Wiley & Sons.
[64] Center for Chemical Process Safety. (2011). Guidelines for auditing process safety management systems (2nd ed.). Wiley-AIChE.
[65] Center for Chemical Process Safety. (2012). Guidelines for engineering design for process safety (2nd ed.). Wiley.
[66] Center for Chemical Process Safety. (2015). Guidelines for initiating events and independent protection layers in layer of protection analysis. Wiley-AIChE. https://doi.org/10.1002/9781118948743
[67] Center for Chemical Process Safety. (2016). Guidelines for implementing process safety management systems (2nd ed.). John Wiley & Sons.
[68] Center for Chemical Process Safety. (2018). Bow ties in risk management: A concept book for process safety. Wiley-AIChE.
[69] Chebbi, R., Qasim, M., & Abdel Jabbar, N. (2019). Optimization of triethylene glycol dehydration of natural gas. Energy Reports, 5, 723-732. https://doi.org/10.1016/j.egyr.2019.06.014
[70] Cheng, Y. F. (2013). Stress corrosion cracking of pipelines. Wiley. https://doi.org/10.1002/9781118537022
[71] Clayton, C. A., et al. (1998). Ubit field rejuvenation: A case history of reservoir management of a giant oil field, offshore Nigeria. SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers. https://doi.org/10.2118/49165-MS
[72] Conley, M. (2005). Integrating risk-based inspection into risk management plans. Process Safety Progress, 24(4), 236-243. https://doi.org/10.1002/prs.10103
[73] Cox, L. A., Jr. (2008). What's wrong with risk matrices? Risk Analysis, 28(2), 497-512. https://doi.org/10.1111/j.1539-6924.2008.01030.x
[74] Cozzani, V., & Reniers, G. (2013). Historical background and state of the art on domino effect assessment. In G. Reniers & V. Cozzani (Eds.), Domino effects in the process industries: Modelling, prevention and managing (pp. 1-10). Elsevier. https://doi.org/10.1016/B978-0-444-54323-3.00001-4
[75] Dagodzo, D. (2018a). A conceptual framework for UAV integration into national power grid inspection programs. Iconic Research and Engineering Journals, 2(5), 391-412. https://doi.org/10.64388/IREV2I5-1716082
[76] Dagodzo, D. (2018b). A review of UAV applications in electrical transmission line inspection: Methods, technologies, and challenges. Iconic Research and Engineering Journals, 2(6), 234-254. https://doi.org/10.64388/IREV2I6-1716083
[77] Dagodzo, D., 2018. Hydrothermal Alteration Interpretation of LANDSAT and ASTER Data. Saarbrücken, Germany: Lambert Academic Publishing. ISBN: 978-3-330-02903-3.
[78] de Ruijter, A., & Guldenmund, F. (2016). The bowtie method: A review. Safety Science, 88, 211-218.
[79] de Waard, C., Lotz, U., & Milliams, D. E. (1991). Predictive model for CO2 corrosion engineering in wet natural gas pipelines. Corrosion, 47(12), 976-985.
[80] Det Norske Veritas. (2009). DNV-RP-F116: Integrity management of submarine pipeline systems. DNV.
[81] Dey, P. K. (2001). A risk-based model for inspection and maintenance of cross-country petroleum pipeline. Journal of Quality in Maintenance Engineering, 7(1), 25-41.
[82] Dhillon, B. S. (2006). Maintainability, maintenance, and reliability for engineers. CRC Press.
[83] Dogbatsey, E. A., Ebhojie, O., & Oyeleye, A. O. (2019). Reconciliation control and financial workflow redesign in emerging market organizations: A conceptual framework. Zenodo. https://doi.org/10.5281/zenodo.20447103 \[Originally numbered 3(5); journal name not captured in source.\]
[84] Dosunmu, A. A., & Ogundele, P. O. (2019). Security audit and enterprise risk assessment frameworks for resilient information systems. Iconic Research and Engineering Journals, 3(5), 434-447. https://doi.org/10.64388/IREV3I5-1713225
[85] Duijm, N. J. (2009). Safety-barrier diagrams as a safety management tool. Reliability Engineering & System Safety, 94(2), 332-341.
[86] Elbashir, N. O. (2018). Introduction to natural gas monetization. In Natural gas processing from midstream to downstream (pp. 1-14). Wiley. https://doi.org/10.1002/9781119269618.ch1
[87] Ericson, C. A. (2015). Hazard analysis techniques for system safety (2nd ed.). Wiley.
[88] Fadayomi, O., Abolaji, T. O., Edivri, J., Ogbole, J. I., Okoruwa, P. O., & Akeju, B. (2019). Risk-based cybersecurity assurance and data availability limitations, advances and future research opportunities. IRE Journals, 2(12), 602-617. https://doi.org/10.64388/IREV2I12-1713779
[89] Fang, W., Wu, J., Bai, Y., Zhang, L., & Reniers, G. (2019). Quantitative risk assessment of a natural gas pipeline in an underground utility tunnel. Process Safety Progress, 38(4), e12051. https://doi.org/10.1002/prs.12051
[90] Faseemo, O., Massot, J., Essien, N., Healy, W., & Owah, E. (2009). Multidisciplinary approach to optimising hydrocarbon recovery from conventional offshore Nigeria: OML100 case study. SPE Nigeria Annual International Conference and Exhibition. Society of Petroleum Engineers. https://doi.org/10.2118/128889-MS
[91] Ferdous, R., Khan, F., Sadiq, R., Amyotte, P., & Veitch, B. (2011). Fault and event tree analyses for process systems risk analysis: Uncertainty handling formulations. Risk Analysis, 31(1), 86-107. https://doi.org/10.1111/j.1539-6924.2010.01475.x
[92] Gas Processors Suppliers Association. (2012). Engineering data book (13th ed.). GPSA.
[93] Gas Processors Suppliers Association. (2012). GPSA engineering data book (13th ed.). GPSA.
[94] Gas Processors Suppliers Association. (2017). GPSA engineering data book (14th ed.). GPSA.
[95] Gbadamosi, I.T. & Obogo, S.F., 2013. Chemical Constituents and In Vitro Antimicrobial Activities of Five Botanicals Used Traditionally for the Treatment of Neonatal Jaundice in Ibadan, Nigeria. Nature and Science, 11(10), pp.130-135. Available at: http://www.sciencepub.net/nature.
[96] Gideon, E. N., Adaramola, T. S., & Fadero, S. (2019). Reliability engineering and failure analysis in complex engineering systems. Iconic Research and Engineering Journals, 2(11), 703-727. https://doi.org/10.64388/IREV2I11-1722490
[97] Guo, Y., Meng, X., Wang, D., Meng, T., Liu, S., & He, R. (2017). Quantitative risk assessment of submarine pipeline instability. Journal of Loss Prevention in the Process Industries, 45.
[98] Hagemeijer, P. M., & Kerkveld, G. (1998). A methodology for risk-based inspection of pressurized systems. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 212(1), 37-47. https://doi.org/10.1243/0954408981529286
[99] Han, Z. Y., & Weng, W. G. (2011). Comparison study on qualitative and quantitative risk assessment methods for urban natural gas pipeline network. Journal of Hazardous Materials, 189(1-2), 509-518.
[100] Helton, J. C., & Davis, F. J. (2003). Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering & System Safety, 81(1), 23-69.
[101] Hopkins, A. (2005). Safety, culture and risk: The organisational causes of disasters. CCH Australia.
[102] Howarth, R. W. (2014). A bridge to nowhere: Methane emissions and the greenhouse gas footprint of natural gas. Energy Science & Engineering, 2(2), 47-60. https://doi.org/10.1002/ese3.35
[103] Ibrahim, S. J., Ewim, D. R., & Edeoja, O. A. (2013). Simulation of safety and transient analysis of a pressurized water reactor using the Personal Computer Transient Analyzer. Leonardo Electronic Journal of Practices and Technologies, 22, 93-105.
[104] Ilodigwe, L., & Adesemoye, A. C. (2019a). A critical review of health insurance financing mechanisms and provider payment reform strategies for balancing coverage expansion and financial protection in emerging markets. International Journal of Health and Pharmaceutical Research, 5(2), 31-55. https://doi.org/10.56201/ijhpr.vol.5.no2.2019.pg31.55
[105] Ilodigwe, L., & Adesemoye, A. C. (2019b). From molecules to health systems: A conceptual model explaining why scientific innovation fails to improve patient outcomes without effective healthcare delivery infrastructure. International Journal of Health and Pharmaceutical Research, 5(2), 56-79. https://doi.org/10.56201/ijhpr.vol.5.no2.2019.pg56.79
[106] International Electrotechnical Commission. (2006). IEC 60812: Analysis techniques for system reliability: Procedure for failure mode and effects analysis. IEC.
[107] International Electrotechnical Commission. (2009). IEC 61511-1: Functional safety: Safety instrumented systems for the process industry sector. IEC.
[108] International Electrotechnical Commission. (2010). IEC 61508:2010, Functional safety of electrical/electronic/programmable electronic safety-related systems (2nd ed.). IEC.
[109] International Electrotechnical Commission. (2016). IEC 61511-1:2016, Functional safety: Safety instrumented systems for the process industry sector, Part 1. IEC.
[110] International Electrotechnical Commission. (2018). IEC 31010: Risk management: Risk assessment techniques. IEC.
[111] International Organization for Standardization. (2009). ISO 31010:2009 Risk management: Risk assessment techniques. ISO.
[112] International Organization for Standardization. (2014). ISO 55000:2014, Asset management: Overview, principles and terminology. ISO.
[113] International Organization for Standardization. (2014). ISO 55001:2014 Asset management: Management systems: Requirements. ISO.
[114] International Organization for Standardization. (2015). ISO 9001:2015 Quality management systems: Requirements. ISO.
[115] International Organization for Standardization. (2016). ISO 14224:2016 Petroleum, petrochemical and natural gas industries: Collection and exchange of reliability and maintenance data for equipment. ISO.
[116] International Organization for Standardization. (2018). ISO 31000:2018, Risk management: Guidelines. ISO.
[117] Ismail, O. S., & Umukoro, G. E. (2012). Global impact of gas flaring. Energy and Power Engineering, 4(4), 290-302.
[118] Ismail, O. S., & Umukoro, G. E. (2016). Modelling combustion reactions for gas flaring and its resulting emissions. Journal of King Saud University: Engineering Sciences, 28(2), 130-140. https://doi.org/10.1016/j.jksues.2014.02.003
[119] Jin, H., & Summers, A. (2015). Dependent, independent, and pseudo-independent protection layers in risk analysis. Process Safety Progress, 35(3), 286-294. https://doi.org/10.1002/prs.11796
[120] Jo, Y. D., & Ahn, B. J. (2005). A method of quantitative risk assessment for transmission pipeline carrying natural gas. Journal of Hazardous Materials, 123(1-3), 1-12.
[121] Kalantarnia, M., Khan, F., & Hawboldt, K. (2009). Dynamic risk assessment using failure assessment and Bayesian theory. Journal of Loss Prevention in the Process Industries, 22(5), 600-606.
[122] Kaplan, S. (1997). The words of risk analysis. Risk Analysis, 17(4), 407-417.
[123] Kaplan, S., & Garrick, B. J. (1981). On the quantitative definition of risk. Risk Analysis, 1(1), 11-27.
[124] Kariuki, S. G., & Löwe, K. (2006). Increasing human reliability in the chemical process industry using human factors techniques. Process Safety and Environmental Protection, 84(3), 200-207. https://doi.org/10.1205/psep.05160
[125] Khakzad, N. (2015). Application of dynamic Bayesian network to risk analysis of domino effects in chemical infrastructures. Reliability Engineering & System Safety, 138, 263-272. https://doi.org/10.1016/j.ress.2015.02.007
[126] Khakzad, N., Khan, F., & Amyotte, P. (2011). Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches. Reliability Engineering & System Safety, 96(8), 925-932.
[127] Khakzad, N., Khan, F., & Amyotte, P. (2012). Dynamic risk analysis using bow-tie approach. Reliability Engineering & System Safety, 104, 36-44.
[128] Khakzad, N., Khan, F., & Amyotte, P. (2013). Dynamic safety analysis of process systems by mapping bow-tie into Bayesian network. Process Safety and Environmental Protection, 91(1-2), 46-53.
[129] Khan, F. I., & Abbasi, S. A. (1998). Techniques and methodologies for risk analysis in chemical process industries. Journal of Loss Prevention in the Process Industries, 11(4), 261-277.
[130] Khan, F. I., & Abbasi, S. A. (1999). Major accidents in process industries and an analysis of causes and consequences. Journal of Loss Prevention in the Process Industries, 12(5), 361-378. https://doi.org/10.1016/S0950-4230(98)00062-X
[131] Khan, F. I., & Abbasi, S. A. (2001). An assessment of the likelihood of occurrence, and the damage potential of domino effect (chain of accidents) in a typical cluster of industries. Journal of Loss Prevention in the Process Industries, 14(4), 283-306. https://doi.org/10.1016/S0950-4230(00)00048-6
[132] Khan, F. I., & Amyotte, P. R. (2004). Integrated inherent safety index (I2SI): A tool for inherent safety evaluation. Process Safety Progress, 23(2), 136-148.
[133] Khan, F. I., & Haddara, M. M. (2003). Risk-based maintenance of ethylene oxide production facilities. Journal of Hazardous Materials, 108(3), 147-159.
[134] Khan, F. I., Sadiq, R., & Haddara, M. M. (2004). Risk-based inspection and maintenance (RBIM): Multi-attribute decision-making with aggregative risk analysis. Process Safety and Environmental Protection, 82(6), 398-411.
[135] Khan, F., Rathnayaka, S., & Ahmed, S. (2015). Methods and models in process safety and risk management: Past, present and future. Process Safety and Environmental Protection, 98, 116-147.
[136] Kidam, K., & Hurme, M. (2013). Analysis of equipment failures as contributors to chemical process accidents. Process Safety and Environmental Protection, 91(1-2), 61-78.
[137] Kletz, T. (1999). Hazop and hazan: Identifying and assessing process industry hazards (4th ed.). IChemE.
[138] Korppoo, A. (2018). Russian associated petroleum gas flaring limits: Interplay of formal and informal institutions. Energy Policy, 116, 232-241. https://doi.org/10.1016/j.enpol.2018.02.005
[139] Kukadiya, K. N., & Gajendran, B. (2017). Energy efficiency and cost optimization assessments in Mangala processing terminal. SPE Oil and Gas India Conference and Exhibition. https://doi.org/10.2118/185385-ms
[140] Ladapo, O. O., Dosunmu, A. A., Jooda, D., & Abolaji, T. O. (2018). Lessons learned from offline assessment of security-critical systems: The case of Microsoft Active Directory. Iconic Research and Engineering Journals, 2(6), 277-299. https://doi.org/10.64388/IREV2I6-1717205
[141] Ladapo, O. O., Jooda, D., Dosunmu, A. A., & Abolaji, T. O. (2019). Implementation of Active Directory for efficient management of enterprise networks. Iconic Research and Engineering Journals, 3(4), 608-627. https://doi.org/10.64388/IREV3I4-1717206
[142] Lamidi, O. B. A., & Olamide, A. (2018). Spatially explicit risk modeling framework for tracking subsurface contaminant migration in data-limited remediation sites. Iconic Research and Engineering Journals, 2(6), 178-198.
[143] Landucci, G., Necci, A., Antonioni, G., Argenti, F., & Cozzani, V. (2017). Risk assessment of mitigated domino scenarios in process facilities. Reliability Engineering & System Safety, 160, 37-53. https://doi.org/10.1016/j.ress.2016.11.023
[144] Lawal, O. A., & Oduleye, T. E. (2018a). A conceptual model for financial analytics driven enterprise value creation in technology firms. Iconic Research and Engineering Journals, 2(2).
[145] Lawal, O. A., & Oduleye, T. E. (2019a). A conceptual risk assessment model for transfer pricing in multinational corporations. Iconic Research and Engineering Journals, 2(12).
[146] Lawal, O. A., & Oduleye, T. E. (2019b). Conceptualizing data driven executive decision systems for strategic financial planning. Iconic Research and Engineering Journals, 3(3).
[147] Leveson, N. (2011). Engineering a safer world: Systems thinking applied to safety. MIT Press.
[148] Li, D., Hu, J., Wang, H., & Huang, W. (2015). A distributed parallel alarm management strategy for alarm reduction in chemical plants. Journal of Process Control, 34, 117-125. https://doi.org/10.1016/j.jprocont.2015.07.008
[149] Li, X., Chen, G., & Zhu, H. (2016). Quantitative risk analysis on leakage failure of submarine oil and gas pipelines using Bayesian network. Process Safety and Environmental Protection, 103, 163-173. https://doi.org/10.1016/j.psep.2016.06.006
[150] Li, X., Ding, Q., & Sun, J. Q. (2018). Remaining useful life estimation in prognostics using deep convolution neural networks. Reliability Engineering & System Safety, 172, 1-11. https://doi.org/10.1016/j.ress.2017.11.021
[151] Li, X., Zhang, W., & Ding, Q. (2019). Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction. Reliability Engineering & System Safety, 182, 208-218. https://doi.org/10.1016/j.ress.2018.11.011
[152] Liang, W., Pang, L., Zhang, L., & Hu, J. (2012). Reliability-centered maintenance study on key parts of reciprocating compressor. 2012 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering. https://doi.org/10.1109/icqr2mse.2012.6246265
[153] Listou Ellefsen, A., Bjorlykhaug, E., Aesoy, V., Ushakov, S., & Zhang, H. (2019). Remaining useful life predictions for turbofan engine degradation using semi-supervised deep architecture. Reliability Engineering & System Safety, 183, 240-251. https://doi.org/10.1016/j.ress.2018.11.027
[154] Lu, L., Liang, W., Zhang, L., Zhang, H., Lu, Z., & Shan, J. (2015). A comprehensive risk evaluation method for natural gas pipelines by combining a risk matrix with a bow-tie model. Journal of Natural Gas Science and Engineering, 25, 124-133.
[155] Macaulay, T., & Singer, B. L. (2016). Cybersecurity for industrial control systems: SCADA, DCS, PLC, HMI, and SIS. Auerbach Publications. https://doi.org/10.1201/b11352
[156] Mannan, S. (2012). Lees process safety essentials: Hazard identification, assessment and control. Butterworth-Heinemann.
[157] Mannan, S. (Ed.). (2012). Lees' loss prevention in the process industries (4th ed.). Butterworth-Heinemann.
[158] Marchese, A. J., Vaughn, T. L., Zimmerle, D. J., Martinez, D. M., Williams, L. L., Robinson, A. L., Mitchell, A. L., Subramanian, R., Tkacik, D. S., Roscioli, J. R., & Herndon, S. C. (2015). Methane emissions from United States natural gas gathering and processing. Environmental Science & Technology, 49(17), 10718-10727. https://doi.org/10.1021/acs.est.5b02275
[159] Marhavilas, P. K., Koulouriotis, D., & Gemeni, V. (2011). Risk analysis and assessment methodologies in the work sites: A review, classification and comparative study. Journal of Loss Prevention in the Process Industries, 24(5), 477-523.
[160] Marhavilas, P. K., Koulouriotis, D., & Gemeni, V. (2011). Risk analysis and assessment methodologies in the work sites: On a review, classification and comparative study of the scientific literature of the period 2000-2009. Journal of Loss Prevention in the Process Industries, 24(5), 477-523. https://doi.org/10.1016/j.jlp.2011.03.004
[161] Marinos, V., Stoumpos, G., & Papazachos, C. (2019). Landslide hazard and risk assessment for a natural gas pipeline project: The case of the Trans Adriatic Pipeline, Albania section. Geosciences, 9(2), 61.
[162] Massaiu, S., & Paltrinieri, N. (2016). Human reliability analysis. In N. Paltrinieri & F. Khan (Eds.), Dynamic risk analysis in the chemical and petroleum industry (pp. 171-179). Elsevier. https://doi.org/10.1016/B978-0-12-803765-2.00014-7
[163] Mbonu, I. S., Aliliele, C., Iwuanyanwu, U., & Oluoha, O. M. (2018). A conceptual framework for legal and ethical risk modeling in enterprise data protection governance systems. Iconic Research and Engineering Journals, 2(2), 207-226. https://doi.org/10.64388/IREV2I2-1714911
[164] Mbonu, I. S., Aliliele, C., Uzoka, E., & Oluoha, O. M. (2019). A review of comparative data protection regulations and secure cloud implementation strategies across jurisdictions. Iconic Research and Engineering Journals, 2(9), 482-501. https://doi.org/10.64388/IREV2I9-1714912
[165] Mbonu, I. S., Iwuanyanwu, U., Uzoka, E., & Oluoha, O. M. (2019). Advances in enterprise log analytics and automated incident response architectures using Python and SIEM platforms. Iconic Research and Engineering Journals, 3(2), 1000-1019. https://doi.org/10.64388/IREV3I2-1714915
[166] Meel, A., & Seider, W. D. (2006). Plant-specific dynamic failure assessment using Bayesian theory. Chemical Engineering Science, 61(21), 7036-7056. https://doi.org/10.1016/j.ces.2006.07.007
[167] Meyer, H. W. H., III. (2011). Analysis of independent protection layers used in three typical chemical processes. Process Safety Progress, 30(4), 346-350. https://doi.org/10.1002/prs.10486
[168] Michael, O. N., & Ogunsola, O. E. (2019a). Determinants of access to agribusiness finance and their influence on enterprise growth in rural communities. Iconic Research and Engineering Journals, 2(12), 533-548.
[169] Michelsen, O. (1998). Use of reliability technology in the process industry. Reliability Engineering & System Safety, 60(2), 179-181. https://doi.org/10.1016/S0951-8320(98)83011-1
[170] Modarres, M., Kaminskiy, M. P., & Krivtsov, V. (2016). Reliability engineering and risk analysis: A practical guide (3rd ed.). CRC Press.
[171] Mondal, B. C., & Dhar, A. S. (2019). Burst pressure assessment of corroded pipelines using fracture mechanics criterion. Engineering Failure Analysis, 104, 139-153.
[172] Moskowitz, I. H., Seider, W. D., Arbogast, J. E., Oktem, U. G., Pariyani, A., & Soroush, M. (2016). Improved predictions of alarm and safety system performance through process and operator response time modeling. AIChE Journal, 62(9), 3461-3472. https://doi.org/10.1002/aic.15419
[173] Moubray, J. (1997). Reliability-centered maintenance (2nd ed.). Industrial Press.
[174] Muhlbauer, W. K. (2004). Pipeline risk management manual: Ideas, techniques, and resources (3rd ed.). Gulf Professional Publishing.
[175] NACE International. (2010). NACE SP0502-2010: Pipeline external corrosion direct assessment methodology. NACE.
[176] Neagu, M., & Cursaru, D. L. (2017). Technical and economic evaluations of the triethylene glycol regeneration processes in natural gas dehydration plants. Journal of Natural Gas Science and Engineering, 37, 327-340. https://doi.org/10.1016/j.jngse.2016.11.052
[177] Necci, A., Cozzani, V., Spadoni, G., & Khan, F. (2015). Assessment of domino effect: State of the art and research needs. Reliability Engineering & System Safety, 143, 3-18. https://doi.org/10.1016/j.ress.2015.05.017
[178] Nessim, M., Zhou, W., Zhou, J., & Rothwell, B. (2009). Target reliability levels for design and assessment of onshore natural gas pipelines. Journal of Pressure Vessel Technology, 131(6), 061701. https://doi.org/10.1115/1.3110017
[179] Nivolianitou, Z. S., & Papazoglou, I. A. (1998). An auditing methodology for safety management of the Greek process industry. Reliability Engineering & System Safety, 60(3), 185-197. https://doi.org/10.1016/S0951-8320(97)00148-8
[180] Nnaji, E., Adgidzi, D., Dioha, M. O., Ewim, D. R. E., & Huan, Z. (2019). Modelling and management of smart microgrid for rural electrification in Sub-Saharan Africa: The case of Nigeria. The Electricity Journal, 32(10), 106672.
[181] NORSOK. (2010). NORSOK Z-013: Risk and emergency preparedness assessment. Standards Norway.
[182] Nwafor, M. I., Uduokhai, D. O., Ifechukwu, G. O., Stephen, D. E. S. M. O. N. D., & Aransi, A. N. (2019). Developing an analytical framework for enhancing efficiency in public infrastructure delivery systems. IRE Journals, 2(11), 657-670.
[183] Obogo, S. F., Ozobu, C. O., & Uduokhai, D. O. (2019a). Advances in leadership driven safety culture transformation in large construction workforces. Iconic Research and Engineering Journals, 3(5), 507-523. https://doi.org/10.64388/IREV3I5-1715497
[184] Obogo, S. F., Ozobu, C. O., & Uduokhai, D. O. (2019b). Development of a construction safety risk governance model for multi contractor high rise projects. Iconic Research and Engineering Journals, 2(9), 502-522. https://doi.org/10.64388/IREV2I9-1715495
[185] Obogo, S. F., Uduokhai, D. O., & Ozobu, C. O. (2019). Systematic review of hazard identification and risk control practices in urban construction projects. Iconic Research and Engineering Journals, 2(12), 666-681. https://doi.org/10.64388/IREV2I12-1715496
[186] Obriki, O. D., & Arumosoye, O. M. (2018). Conceptual modeling of data-driven occupational safety risk control in large-scale energy infrastructure projects. Iconic Research and Engineering Journals, 1(7), 169-189. https://doi.org/10.64388/IREV1I7-1714414
[187] Obriki, O. D., & Arumosoye, O. M. (2019). A conceptual framework linking management safety walkthrough frequency and coverage to safety culture outcomes in mega projects. Iconic Research and Engineering Journals, 2(8), 355-374. https://doi.org/10.64388/IREV2I8-1714416
[188] Ogbete, J. C., Aminu-Ibrahim, A. Y., & Ambali, K. B. (2018). Optimizing laboratory spatial planning strategies to improve diagnostic accuracy, safety, and clinical throughput. Iconic Research and Engineering Journals, 2(1), 87-113. https://doi.org/10.64388/IREV1I7-1713587
[189] Ogbete, J. C., Aminu-Ibrahim, A. Y., & Ambali, K. B. (2019). Regulatory compliant design systems for molecular and pathology laboratories in highly controlled environments. Iconic Research and Engineering Journals, 3(4), 607-631. https://doi.org/10.64388/IREV3I4-1713589
[190] Ojijiagwo, E., Oduoza, C. F., & Emekwuru, N. (2016). Economics of gas to wire technology applied in gas flare management. Engineering Science and Technology, an International Journal, 19(4), 2109-2118. https://doi.org/10.1016/j.jestch.2016.09.012
[191] Okonkwo, C. S., Ogunwole, O., & Okeke, O. T. (2018a). Framework for strategic procurement optimization in oil and gas operations. Iconic Research and Engineering Journals, 1(7), 153-168. https://doi.org/10.64388/IREV1I7-1713119
[192] Okonkwo, C. S., Ogunwole, O., & Okeke, O. T. (2018b). Model for inventory availability and plant uptime improvement in energy facilities. Iconic Research and Engineering Journals, 2(4), 160-172. https://doi.org/10.64388/IREV2I4-1713120
[193] Okonkwo, C. S., Ogunwole, O., Okeke, O. T., & Mayo, W. (2019). Conceptual framework for cost reduction through contract negotiation and vendor governance. Iconic Research and Engineering Journals, 2(9), 468-482. https://doi.org/10.64388/IREV2I9-1713121
[194] Osiki, O. M. (2018). Gas flaring and environmental issues in the Niger Delta, 1956-2007. Journal of Energy and Natural Resource Management, 1(2), 127-131. https://doi.org/10.26796/jenrm.v1i0.28
[195] Ossai, C. I. (2012). Advances in asset management techniques: An overview of corrosion mechanisms and mitigation strategies for oil and gas pipelines. ISRN Corrosion, 2012, Article 570143. https://doi.org/10.5402/2012/570143
[196] Ossai, C. I., Boswell, B., & Davies, I. J. (2015). Pipeline failures in corrosive environments: A conceptual analysis of trends and effects. Engineering Failure Analysis, 53, 36-58. https://doi.org/10.1016/j.engfailanal.2015.03.004
[197] Paltrinieri, N., Khan, F., Amyotte, P., & Cozzani, V. (2014). Dynamic approach to risk management: Application to the Hoeganaes metal dust accidents. Process Safety and Environmental Protection, 92(6), 669-679.
[198] Paltrinieri, N., Massaiu, S., & Matteini, A. (2016). Human reliability analysis in the petroleum industry. In N. Paltrinieri & F. Khan (Eds.), Dynamic risk analysis in the chemical and petroleum industry (pp. 181-192). Elsevier. https://doi.org/10.1016/B978-0-12-803765-2.00015-9
[199] Papadakis, G. A. (1999). Major hazard pipelines: A comparative study of onshore transmission accidents. Journal of Loss Prevention in the Process Industries, 12(1), 91-107.
[200] Perrin, M., Zhu, B., Rainaud, J.-F., & Schneider, S. (2005). Knowledge-driven applications for geological modelling. Journal of Petroleum Science and Engineering, 47(1-2), 89-104. https://doi.org/10.1016/j.petrol.2005.03.001
[201] Perrow, C. (1984). Normal accidents: Living with high-risk technologies. Basic Books.
[202] Popli, S., Rodgers, P., & Eveloy, V. (2012). Trigeneration scheme for energy efficiency enhancement in a natural gas processing plant through turbine exhaust gas waste heat utilization. Applied Energy, 93, 624-636. https://doi.org/10.1016/j.apenergy.2011.11.038
[203] Promoppatum, P., & Viswanathan, V. (2016). Identifying material and device targets for a flare gas recovery system utilizing electrochemical conversion of methane to methanol. ACS Sustainable Chemistry & Engineering, 4(3), 1736-1745. https://doi.org/10.1021/acssuschemeng.5b01714
[204] Qin, S. J., & Chiang, L. H. (2019). Advances and opportunities in machine learning for process data analytics. Computers & Chemical Engineering, 126, 465-473. https://doi.org/10.1016/j.compchemeng.2019.04.003
[205] Rahmanian, N., Ilias, I. B., & Nasrifar, K. (2015). Process simulation and assessment of a back-up condensate stabilization unit. Journal of Natural Gas Science and Engineering, 26, 730-736. https://doi.org/10.1016/j.jngse.2015.06.058
[206] Ramasamy, B. (2018). ADNOC gas processing experience in hydrocarbon and acid gas flare recovery utilizing liquid ring compressor and dry screw compressors. Abu Dhabi International Petroleum Exhibition and Conference. https://doi.org/10.2118/192892-ms
[207] Rasmussen, J. (1997). Risk management in a dynamic society: A modelling problem. Safety Science, 27(2-3), 183-213.
[208] Rathnayaka, S., Khan, F., & Amyotte, P. (2011). SHIPP methodology: Predictive accident modeling approach. Part I: Methodology and model description. Process Safety and Environmental Protection, 89(3), 151-164.
[209] Rathnayaka, S., Khan, F., & Amyotte, P. (2012). Accident modeling approach for safety assessment in an LNG processing facility. Journal of Loss Prevention in the Process Industries, 25(3), 414-423.
[210] Rathnayaka, S., Khan, F., & Amyotte, P. (2014). Risk-based process plant design considering inherent safety. Safety Science, 70, 438-464. https://doi.org/10.1016/j.ssci.2014.06.004
[211] Rausand, M. (2011). Risk assessment: Theory, methods, and applications. Wiley.
[212] Rausand, M., & Hoyland, A. (2004). System reliability theory: Models, statistical methods, and applications (2nd ed.). Wiley.
[213] Reason, J. (1990). Human error. Cambridge University Press.
[214] Reason, J. (1997). Managing the risks of organizational accidents. Ashgate.
[215] Remeljej, C., & Hoadley, A. (2006). An exergy analysis of small-scale liquefied natural gas (LNG) liquefaction processes. Energy, 31(12), 2005-2019. https://doi.org/10.1016/j.energy.2005.09.005
[216] Restrepo, C. E., Simonoff, J. S., & Zimmerman, R. (2009). Causes, cost consequences, and risk implications of accidents in US hazardous liquid pipeline infrastructure. International Journal of Critical Infrastructure Protection, 2(1-2), 38-50.
[217] Roscioli, J. R., Yacovitch, T. I., Floerchinger, C., Mitchell, A. L., Tkacik, D. S., Subramanian, R., Martinez, D. M., Vaughn, T. L., Williams, L. L., Zimmerle, D., Robinson, A. L., Herndon, S. C., & Marchese, A. J. (2015). Measurements of methane emissions from natural gas gathering facilities and processing plants: Measurement methods. Atmospheric Measurement Techniques, 8(5), 2017-2035. https://doi.org/10.5194/amt-8-2017-2015
[218] Roy, P. S., & Amin, M. R. (2011). Aspen-HYSYS simulation of natural gas processing plant. Journal of Chemical Engineering, 26(1), 62-65.
[219] Shittu, H., Opara, I. S., Elumilade, R. A., & Adeniji, I. O. (2019). Hydrogen as a secondary energy carrier: Modeling its integration in national grids. Iconic Research and Engineering Journals, 3(1), 628-643. https://doi.org/10.64388/IREV3I1-1713909
[220] Singh, R. (2017). Pipeline integrity handbook: Risk management and evaluation (2nd ed.). Gulf Professional Publishing/Elsevier.
[221] Sitorus, T., Sitaresmi, R., & Oetomo, H. (2018). Flare gas recovery system using integrated reciprocating compressor in gathering station C. Journal of Earth Energy Science, Engineering, and Technology, 1(2). https://doi.org/10.25105/jeeset.v1i2.3946
[222] Sklet, S. (2006). Safety barriers: Definition, classification, and performance. Journal of Loss Prevention in the Process Industries, 19(5), 494-506.
[223] Skogdalen, J. E., & Vinnem, J. E. (2011). Quantitative risk analysis offshore: Human and organizational factors. Reliability Engineering & System Safety, 96(4), 468-479.
[224] Skogdalen, J. E., & Vinnem, J. E. (2012). Quantitative risk analysis of oil and gas drilling, using Deepwater Horizon as case study. Reliability Engineering & System Safety, 100, 58-66. https://doi.org/10.1016/j.ress.2011.12.002
[225] Skogestad, S. (2008). Chemical and energy process engineering. CRC Press.
[226] Smith, D. J. (2011). Reliability, maintainability and risk: Practical methods for engineers (8th ed.). Butterworth-Heinemann.
[227] Sonawat, A., & Samad, A. (2014). Performance analysis of an ejector for flare gas recovery. Geosystem Engineering, 17(3), 169-177. https://doi.org/10.1080/12269328.2014.957788
[228] Stack, R. J. (2009). Evaluating non-independent protection layers. Process Safety Progress, 28(4), 317-324. https://doi.org/10.1002/prs.10352
[229] Sunday, E. A., & Omoegun, G. O. (2018). Integrating solar power solutions in small-scale manufacturing industries in Nigeria. International Journal of Scientific Research in Science, Engineering and Technology, 4(8), 832-853.
[230] Sunday, E. A., & Omoegun, G. O. (2019). Optimizing electrical load distribution for hybrid solar installations in developing economies. International Journal of Scientific Research in Mechanical and Materials Engineering, 3(6), 27-47.
[231] Sunday, E. A., Omoegun, G. O., Essien, M. A., & Oluokun, O. A. (2019). Thermodynamic efficiency and control strategies in residential air conditioning systems. International Journal of Scientific Research in Civil Engineering, 3(3), 52-76.
[232] Tavakkoli, S., Lokare, O. R., Vidic, R. D., & Khanna, V. (2016). Systems-level analysis of waste heat recovery opportunities from natural gas compressor stations in the United States. ACS Sustainable Chemistry and Engineering, 4(7), 3618-3626. https://doi.org/10.1021/acssuschemeng.5b01685
[233] Teng, K. Y., Thekdi, S. A., & Lambert, J. H. (2012). Identification and evaluation of priorities in the business process of a risk or safety organization. Reliability Engineering & System Safety, 99, 74-86. https://doi.org/10.1016/j.ress.2011.10.006
[234] Trucano, T. G., Swiler, L. P., Igusa, T., Oberkampf, W. L., & Pilch, M. (2006). Calibration, validation, and sensitivity analysis: What's what. Reliability Engineering & System Safety, 91(10-11), 1331-1357.
[235] Umukoro, G. E., & Ismail, O. S. (2017). Modelling emissions from natural gas flaring. Journal of King Saud University: Engineering Sciences, 29(2), 178-182. https://doi.org/10.1016/j.jksues.2015.08.001
[236] Venkatasubramanian, V., Rengaswamy, R., & Kavuri, S. N. (2003). A review of process fault detection and diagnosis: Part II: Qualitative models and search strategies. Computers & Chemical Engineering, 27(3), 313-326.
[237] Venkatasubramanian, V., Rengaswamy, R., Kavuri, S. N., & Yin, K. (2003). A review of process fault detection and diagnosis: Part III: Process history based methods. Computers & Chemical Engineering, 27(3), 327-346.
[238] Venkatasubramanian, V., Rengaswamy, R., Yin, K., & Kavuri, S. N. (2003). A review of process fault detection and diagnosis: Part I. Quantitative model-based methods. Computers & Chemical Engineering, 27(3), 293-311.
[239] Vianello, C., & Maschio, G. (2014). Quantitative risk assessment of the Italian gas distribution network. Journal of Loss Prevention in the Process Industries, 32, 5-17.
[240] Villa, V., Paltrinieri, N., Khan, F., & Cozzani, V. (2016). Towards dynamic risk analysis: A review of the risk assessment approach and its limitations in the chemical process industry. Safety Science, 89, 77-93.
[241] Vinnem, J. E. (2014). Offshore risk assessment: Principles, modelling and applications of QRA studies (3rd ed.). Springer.
[242] Wetenhall, B., Race, J. M., & Downie, M. J. (2014). The effect of CO2 purity on the development of pipeline networks for carbon capture and storage schemes. International Journal of Greenhouse Gas Control, 30, 197-211. https://doi.org/10.1016/j.ijggc.2014.09.008
[243] Wieczorek, G. M., & Basu, P. K. (1997). Management of change: A pilot plant application. Process Safety Progress, 16(3), 160-164. https://doi.org/10.1002/prs.680160309
[244] Witkowski, A., Rusin, A., Majkut, M., & Stolecka, K. (2014). Comprehensive analysis of pipeline transportation systems for CO2 sequestration: Thermodynamics and safety problems. Energy Conversion and Management, 76, 665-673. https://doi.org/10.1016/j.enconman.2013.07.087
[245] Xing, Z., Ren, F., & Liu, W. (2009). A quantitative method of risk assessment of natural gas pipeline. In Proceedings of the International Conference on Pipelines and Trenchless Technology 2009 (pp. 821-830). American Society of Civil Engineers. https://doi.org/10.1061/41073(361)88
[246] Yang, M., & You, F. (2017). Modular methanol manufacturing from shale gas: Techno-economic and environmental analyses of conventional large-scale production versus small-scale distributed, modular processing. AIChE Journal, 64(2), 495-510. https://doi.org/10.1002/aic.15958
[247] Yang, X., & Haugen, S. (2015). Classification of risk to support decision-making in hazardous processes. Safety Science, 80, 115-126. https://doi.org/10.1016/j.ssci.2015.07.011
[248] Yazdi, M., & Kabir, S. (2017). A fuzzy Bayesian network approach for risk analysis in process industries. Process Safety and Environmental Protection, 111, 507-519. https://doi.org/10.1016/j.psep.2017.08.015
[249] Younsi, K., & Smati, A. (2017). Intrinsic availability assessment of aged gas transmission pipeline using Bayesian update and stochastic process modeling. Journal of Natural Gas Science and Engineering, 45, 659-669. https://doi.org/10.1016/j.jngse.2017.06.012
[250] Yu, W., Song, S., Li, Y., Min, Y., Huang, W., Wen, K., & Gong, J. (2018). Gas supply reliability assessment of natural gas transmission pipeline systems. Energy, 162, 853-870. https://doi.org/10.1016/j.energy.2018.08.039
[251] Yuhua, D., & Datao, Y. (2005). Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis. Journal of Loss Prevention in the Process Industries, 18(2), 83-88.
[252] Zabihi, A., & Taghizadeh, M. (2016). Feasibility study on energy recovery at Sari-Akand city gate station using turboexpander. Journal of Natural Gas Science and Engineering, 35, 152-159. https://doi.org/10.1016/j.jngse.2016.08.054
[253] Zarei, E., Azadeh, A., Aliabadi, M. M., & Mohammadfam, I. (2017). Dynamic safety risk modeling of process systems using Bayesian network. Process Safety Progress, 36(4), 399-407. https://doi.org/10.1002/prs.11889
[254] Zarei, E., Mohammadfam, I., Aliabadi, M. M., Jamshidi, A., & Ghasemi, F. (2016). Efficiency prediction of control room operators based on human reliability analysis and dynamic decision making style in the process industry. Process Safety Progress, 35(2), 192-199. https://doi.org/10.1002/prs.11782
[255] Zavala-Araiza, D., Alvarez, R. A., Lyon, D. R., Allen, D. T., Marchese, A. J., Zimmerle, D. J., & Hamburg, S. P. (2017). Super-emitters in natural gas infrastructure are caused by abnormal process conditions. Nature Communications, 8, 14012. https://doi.org/10.1038/ncomms14012
[256] Zhang, P., Qin, G., & Wang, Y. (2019). Risk assessment system for oil and gas pipelines laid in one ditch based on quantitative risk analysis. Energies, 12(6), 981.
[257] Zio, E. (2009). Reliability engineering: Old problems and new challenges. Reliability Engineering & System Safety, 94(2), 125-141.
How to cite this paper
@article{1723153,
author = {Eromosele Asibor, Daniel Edet Isong},
title = {Risk-Based Process Engineering Framework for Strengthening Reliability Across Complex Natural Gas Infrastructure Systems},
journal = {Iconic Research And Engineering Journals},
year = {2019},
volume = {3},
number = {2},
pages = {1020-1060},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1723153.pdf},
abstract = {Natural gas infrastructure is a coupled system of wells, gathering lines, processing units, compressors, transmission pipelines, storage assets, metering stations, and distribution interfaces. Reliability failures within this system rarely arise from one technical defect. They emerge through interactions among degradation, process variability, protection-system performance, human decisions, organizational controls, and external hazards. Existing approaches often treat process safety, asset integrity, inspection, maintenance, and operational risk as separate programs. This paper develops a unified risk-based process engineering framework that connects these programs through a common decision structure. The study uses an integrative review of standards and scholarly literature published to date. The synthesis draws on risk management, risk-based inspection, functional safety, pipeline integrity management, barrier theory, human factors, and reliability engineering. The proposed framework contains eight linked functions: system definition, hazard identification, consequence modelling, failure-likelihood assessment, barrier evaluation, risk aggregation, intervention selection, and performance learning. A bow-tie representation connects initiating causes, preventive barriers, loss-of-containment events, mitigative barriers, and consequences. A dynamic risk register then links each scenario to operating limits, inspection findings, maintenance tasks, management-of-change actions, and leading indicators. The framework replaces isolated equipment rankings with system-level prioritization and treats uncertainty as a decision variable. It also introduces reliability, safety, environmental, and economic criteria into one intervention portfolio. The paper contributes a practical architecture for allocating engineering attention across heterogeneous gas assets while preserving traceability from hazard evidence to action. The framework is suitable for conceptual testing, case-study validation, and later quantitative implementation. Its central proposition is that reliability improves when risk information moves continuously across lifecycle functions rather than remaining within specialist silos.},
keywords = {natural gas infrastructure; risk-based process engineering; reliability; process safety; asset integrity; barrier management; risk-based inspection; functional safety},
month = {August},
doi = {https://doi.org/10.64388/IREV3I2-1723153}
}