Noslēguma darbu reģistrs
  
Studiju darba apraksts
Studiju veids maģistra akadēmiskās studijas
Studiju programmas nosaukums Loģistikas sistēmu un piegādes ķēdes vadība
Nosaukums Piegāžu ķēžu ietekme uz apkārtējo vidi naftas un gāzes ieguves industrijā
Nosaukums angļu valodā Environmental Footprint of Supply Chain in Oil and Gas Industry
Struktūrvienība 12100 Informācijas tehnoloģijas institūts
Darba vadītājs Egils Ginters
Recenzents Olga Girvica
Anotācija This master thesis explores the hazards and effects that happen within the oil and gas industry which is widely responsible for the environmental footprint and how to improve them by observing the risk factors in sustainability assessment through risk modeling. This thesis mainly focuses on the aspect of the oil and gas industry as a whole and explores its processes in segments thus providing the necessary information required for the analysis of the hazards. The thesis contains a theoretical analysis of the industry and hazard, data analytical component of the hazards, and finally, a risk assessment model using Bayesian Network to sum it all. The online data is used for doing the survey research quantitative analysis gives information on the risk factor that each of the hazards mentioned would pose in the industry and same is done for accidents but the only difference being that the occurrence of accidents is precedented by the hazard itself. Finally, the risk assessment model is designed to give the outcome i.e. the effects that these hazards would cause. Territory planners, regional policymakers, geological experts, and municipalities are all can be the potential audience of the results as the results from the model can be directly used to determine the state of the oil and gas company that needs and where they stand in terms of the environmental consideration. The master thesis contains 131 pages, 45 images, 41 tables, 125 reference sources, and 1 appendix.
Atslēgas vārdi RISK ANALYSIS, OIL AND GAS INDUSTRY, BAYESIAN NETWORK
Atslēgas vārdi angļu valodā RISK ANALYSIS, OIL AND GAS INDUSTRY, BAYESIAN NETWORK
Valoda eng
Gads 2021
Darba augšupielādes datums un laiks 28.05.2021 15:10:30