Published in

Volume 8: Ian Jordaan Honoring Symposium on Ice Engineering

DOI: 10.1115/omae2015-41366

Links

Tools

Export citation

Search in Google Scholar

Optimization of OSV Fleet for an Offshore Oil and Gas Field in the Russian Arctic

Proceedings article published in 2015 by Aleksandar-Saša Milaković, Mads Ulstein, Alexei Bambulyak, Sören Ehlers
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Due to a constantly increasing global energy demand on one side, and depletion of available hydrocarbon resources on another, a continuous search for new reserves of hydrocarbons is required (BP Energy Outlook 2035 [1]). Having in mind that estimated 22% of the world’s undiscovered petroleum is located in the Arctic, 84% of which is projected to be offshore (US Geology Survey [2]), the Arctic becomes a logical region of activities expansion for the oil and gas industry. Opposing large expected quantities of hydrocarbons that are to be found in the Arctic, there are also numerous challenges that need to be overcome in order to make production economically feasible. One of the segments of offshore production process that is expected to be influenced by Arctic conditions is upstream supply chain, or chain of delivery of products and services that are necessary for unhindered operation of an offshore field. Within upstream supply chain, it is expected that the configuration of Offshore Supply Vessel (OSV) fleet will be significantly affected by specific Arctic conditions, mainly by large distances to supply base as well as by environmental conditions. Therefore, this paper seeks to identify an optimal composition of OSV fleet taking into consideration specific Arctic conditions. A simulation model describes an upstream supply chain taking into consideration stochastic nature of environmental conditions in the Arctic. An optimization model is built on top of the simulation model in order to assess optimal configuration of the fleet with respect to operational costs. Simulation and optimization are run for a case of an offshore oil and gas field development in the Russian Arctic.