Operations optimization for natural resource projects
Research output: Thesis › Doctoral Thesis
Standard
2016.
Research output: Thesis › Doctoral Thesis
Harvard
Vancouver
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TY - BOOK
T1 - Operations optimization for natural resource projects
AU - Mitschanek, Mathias
N1 - no embargo
PY - 2016
Y1 - 2016
N2 - The development of conventional hydrocarbon bearing formations requires proper planning as the industry is capital intensive and a well placed or a surface facility placed at the wrong location might lead to severe economic setbacks. A successful development requires the collaboration of interdisciplinary teams as every discipline affects the others. With the development of shale formations the need to work interdisciplinary has become more necessary as never before. Large drilling campaigns require an operations fleet to work together seamlessly. As a lot of equipment is involved in such a development and infrastructure needs to be built at a large scale, “factory drilling” has become a buzzword in the industry. This factory style drilling campaigns require engineers to look at all the details of the operations and engineering and sometimes require an entirely new approach for efficiency gains, like the development of walking or skidding rigs. Such a large system is inherently complex to manage. Numerous parameters can be chosen and a vast number of possible development strategies exist. Optimization methodologies that have already been developed have their main application for conventional fields. Thus manual planning for shale formations was very often the case. However, to find the optimal strategy manually amongst a vast number of possibilities is almost impossible. That’s why this research aims to optimize strategies and operational plans for such shale formations. A model was developed that allows evaluating and comparing various scenarios. An optimization methodology was added in order to systematically find the “best” strategy for a shale oil or gas project. At the end of this research, recommendations are given what parameters will result in “good” strategies based on the size of the lease.
AB - The development of conventional hydrocarbon bearing formations requires proper planning as the industry is capital intensive and a well placed or a surface facility placed at the wrong location might lead to severe economic setbacks. A successful development requires the collaboration of interdisciplinary teams as every discipline affects the others. With the development of shale formations the need to work interdisciplinary has become more necessary as never before. Large drilling campaigns require an operations fleet to work together seamlessly. As a lot of equipment is involved in such a development and infrastructure needs to be built at a large scale, “factory drilling” has become a buzzword in the industry. This factory style drilling campaigns require engineers to look at all the details of the operations and engineering and sometimes require an entirely new approach for efficiency gains, like the development of walking or skidding rigs. Such a large system is inherently complex to manage. Numerous parameters can be chosen and a vast number of possible development strategies exist. Optimization methodologies that have already been developed have their main application for conventional fields. Thus manual planning for shale formations was very often the case. However, to find the optimal strategy manually amongst a vast number of possibilities is almost impossible. That’s why this research aims to optimize strategies and operational plans for such shale formations. A model was developed that allows evaluating and comparing various scenarios. An optimization methodology was added in order to systematically find the “best” strategy for a shale oil or gas project. At the end of this research, recommendations are given what parameters will result in “good” strategies based on the size of the lease.
KW - Schieferöl
KW - Schiefergas
KW - Erschießungsstrategien
KW - Shale oil
KW - shale gas
KW - field development strategy
M3 - Doctoral Thesis
ER -