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Abstract: The purpose of this paper is to describe a methodology for assessing the impact of different risks and uncertainties on the financial output of a carbon capture and storage (CCS) project. The Value Chain Assessment (VCA) methodology is developed by DNV as a decision making tool for project developers to assess the financial feasibility of the investment and for alternative concepts. The methodology can be applied to optimize the financial result and the performance of a CCS project for a given level of risk. In this paper the VCA methodology is described and applied on a case study with a CCS project developer selecting between different capture technologies. [Copyright &y& Elsevier]

A main field and satellite fields consist of several separate reservoirs with gas cap and/or oil rim. A processing facility on the main field receives and processes the oil, gas, and water from all the reservoirs. This facility is typically capable of processing only a limited amount of oil, gas, and water per unit of time. In order to satisfy these processing limitations, the production needs to be choked. The available capacity is shared among several field owners with different commercial interests. In this paper, we focus on how total oil and gas production from all the fields could be optimized. The satellite-field owners negotiate processing capacities on the main-field facility. This introduces additional processing-capacity constraints (booking constraints) for the owners of the main field. If the total wealth created by all owners represents the economic interests of the community, it is of interest to investigate whether the total wealth may be increased by lifting the booking constraints. If all reservoirs may be produced more optimally by removing the booking constraints, all owners may benefit from this when appropriate commercial arrangements are in place. We will compare two production strategies. The first production strategy optimizes locally, at distinct time intervals. At given intervals, the production is prioritized so that the maximum amount of oil is produced. In the second production strategy, a fixed weight is assigned to each reservoir. The purpose of the weights is to be able to prioritize some reservoirs before others. The weights are optimized from a life-cycle perspective. As an illustration, a case study based on real data is presented. For the examples considered, it is beneficial to lift the booking constraints because all of the reservoirs combined can be produced more efficiently when this is done. [ABSTRACT FROM AUTHOR]