| Summary: | The papers of this thesis are not available in Munin. Paper I. Ayele YZ, Barabadi A, Barabady J.: A methodology for identification of a suitable drilling waste handling system in the Arctic region. (Manuscript). Paper II. Ayele YZ, Barabady J, Droguett EL.: Dynamic Bayesian network based risk assessment for Arctic offshore drilling waste handling practices. (Manuscript). Published version available in Journal of Offshore Mechanics and Arctic Engineering 138(5), 051302 (Jun 17, 2016) Paper III. Ayele YZ, Barabadi A, Droguett EL.: Risk-based cost-effectiveness analysis of waste handling practices in the Arctic drilling operation. (Manuscript). Published version available in Journal of Offshore Mechanics and Arctic Engineering 138(3), 031301 (Apr 01, 2016) Paper IV. Ayele YZ, Barabadi A, Barabady J.: Dynamic spare parts transportation model for Arctic production facility. Available in International Journal of System Assurance Engineering and Management (2016) 7: 84 Paper V. Ayele YZ, Barabadi A, Barabady J.: A risk-based approach to manage the Occupational Hazards in the Arctic drilling waste handling practices. Available in CRC Press 2014. ISBN 9781138026810.s. pp. 1329 – 1334 As the offshore industry expands into the Arctic and sub-Arctic areas, the oil and gas exploration activities generate all kinds of waste, varying from contaminated runoff water to material packaging; however, the majority of the waste is associated with the drilling cuttings from drilling activities. Offshore Arctic projects have a high degree of technical and social complexity. The technological challenges of drilling at remote location coupled with the extreme weather conditions makes the operation of drilling waste handling in this environment very demanding and risky. Hence, the competence to reduce the adverse impacts of undesirable events during the drilling waste handling activities depends in part upon the effectiveness of our rigorous risk management plan and clear understanding of the effect of the Arctic operating environment on the drilling waste handling systems. The aim of this research study is to evaluate, identify, and propose a methodology for drilling waste handling practices by considering the complex and fast-changing nature of the Arctic operational conditions. Moreover, the study seeks to foster an integrated interdisciplinary understanding of technical and operational risks associated with drilling wastes and their management by implementing the risk-based analysis. This includes identifying and assessing risks throughout the logistical chain of handling of petroleum related waste. Furthermore, to assure the operational performance of waste handling systems, the study focuses on developing and introducing the concept of a dynamic model for spare parts transportation in Arctic conditions by considering the time-independent and time-dependent covariates. The first part of the study describes the main factors that may influence the operation and performance of the waste handling technologies and processes under Arctic conditions. Then, the current industry practice for managing and disposing of drilling waste are studied. Afterwards, the pros and cons of the common offshore and onshore disposal options are reviewed. Thereafter, a step-by-step methodology is developed for the identification of suitable drilling waste handling systems for Arctic offshore drilling. The application of the methodology is demonstrated by a case study of drilling waste handling practices of an oil field in the Barents Sea (part of Norwegian and Russian Arctic). In the second part of this research study, a risk-based cost-effectiveness analysis model is developed. This model seeks to identify the drilling waste handling practice that is expected to provide the highest level of benefit for a given level of cost, and which has a minimal impact on the HSE (health, safety and environment). Moreover, to avoid inadequacies of the traditional risk assessment approaches and manage the major risk elements connected with handling of drilling wastes, a dynamic Bayesian network (DBN) based risk assessment model is developed. The proposed DBN based risk model combines prior operating environment information with actual observed data from weather forecasting to predict the future potential hazards and/or risks. Furthermore, to assure the availability of production facilities, including waste handling systems, a dynamic model for spare parts transportation called Dynamic Spare Parts Transportation Block Diagram (DSTBD) is described and introduced. The DSTBD model analysed the effect of the time-independent and time-dependent covariates on the spare parts transportation operation. The result of the study shows that working in the cold Arctic environments has the potential if not managed properly to cause a significant negative effect on the cost elements and the risk of events. Moreover, the result from the temporal link or dynamic Bayesian network based risk analysis demonstrates that these negative impacts of the peculiar Arctic risk influencing factors on the reliability of the waste handling system and the risk of marine pollutions, is more significant with time. Furthermore, the DSTBD analysis results demonstrate that the operating environment of the Arctic region increases the spare parts transportation time significantly, particularly, during winter season, when transporting the spare parts from the south-western part of Norway to northern Norway.
|
|---|