Risk-Based Cost Benefit Analysis of Offshore Resource Centre to Support Remote Offshore Operations in Harsh Environment
Introduction
Activities in remote northern offshore regions are expected to increase, due mainly to available hydrocarbon resources. The extended distance from shore support and the inherent harsh environment comprising generally high winds and waves, fog, freezing temperatures, and the presence of seasonal ice all pose significant logistical challenge in maintaining regular operations [5, 7, 14, 16]. Also, a quick response cannot be provided in case of emergency due to the long distance between shore and platform(s). The risk associated with the logistical support operations is analyzed in two previous studies [20, 21] and a risk mitigating Offshore Resource Centre (ORC) concept is presented in (Figure 1) [22]. The ORC has two primary mission requirements for cases where an offshore development is exceptionally remote from land-based support:
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Provide an intermediate point for helicopter operations that enables refueling, alternate landing and shorter transit distance.
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Provide a forward staging or response asset for emergency response in case of fire, spill, sinking or ice damage.
As a risk reduction strategy, the cost of an ORC would be a significant fraction of the total development cost for a remote offshore development. Thus it would be beneficial to have a rational methodology for comparing the costs and benefits of the ORC. These costs and benefits are evaluated in this paper based on the benefit scenario of response time reduction for a blowout accident. This evaluation considers only one of the two main functions of the proposed ORC but provides a methodology which would allow all functions of the intermediate platform to be evaluated by comparing costs to potential savings in an operational or emergency scenario.
The first step is to estimate the capital cost of the ORC. There are various methods available for cost estimation in the shipping business. Caprace and Rigo [2] classified the methods for estimating production cost into three categories, namely, top-down, bottom-up, and life cycle approaches. In a top-down approach, the cost of a new ship is estimated from the parametric relationships of similar historical ship cost data using statistical regression analysis. This approach does not require the detailed specifications of the new ship. It provides a high-level cost estimate under the assumptions that vessels have similar functionalities and construction procedures remain the same. In a bottom-up approach, the project is broken down into smaller and smaller intermediate products until the most basic product is described. This approach is suitable when the detailed design particulars of a new building ship are available. In this study we have used the top-down method and adapted data from other ship types as there is no historical data for the new concept ORC.
The second stage is to estimate the life cycle cost (LCC) of the ORC, which is the present value of the total cost that it may encounter over its life cycle. This includes building cost, operational cost, maintenance cost and scrap. The LCC approach is a promising holistic approach to estimate the cost of the overall life of a ship. Since the ORC is in the concept design phase, the cost estimation is possible only at a very high level and this requires rather broad assumptions about the ship design, its general functional requirements, and its physical and operational characteristics [9].
The capital and life cycle costs make up the cost side of the equation. The benefits arise from the functions of the ORC system. One of two primary functions of the ORC is to mitigate risk by reducing response time when a remote offshore platform is in danger. In general, this should minimize the loss of production, loss of the platform and recovery costs. This risk reduction, particularly in the consequences of an accident can be considered as a financial benefit. Inherent in this logic is the assumption that a faster response in the case of an accident results in reduced loss. This is particularly true when environmental damage from a blowout is considered.
The use of a loss function (LF) is a structured approach to estimate the loss arising from an incident. Loss functions (LFs) express losses related to the deviation of a product from its optimal value. In recent years loss functions have gained wide acceptance among researchers and quality assurance practitioners due to Taguchi's philosophy and quality improvement strategies [25, 29]. Several types of loss functions are found in the literature such as quadratic [26], inverted normal [8, 25], inverted beta [11], inverted gamma loss function [12, 24], etc. The loss of a production platform leads to production downtime, loss of material assets, loss of human lives and environmental damage. This loss is linked with the risk of an accident in a production platform.
A main contributor to the total risk is the uncontrolled release of pressurized hydrocarbons, i.e., gas leakages and blowouts. In this paper, cost data from previous blowout incidents are used to develop a loss function. The details of the historical data are described in the case study section. Adopting a deterministic approach would be unsuitable due to the scarcity of data and the variability in previous accident circumstances. Hence, the complete analysis is conducted in a probabilistic framework using the Monte Carlo Simulation (MCS) technique. The methodology proposed in this paper aims to:
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estimate the building cost and operational cost of the ORC from historical ships data and recent offshore operational day rates and establish a net present value (Cost model);
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develop a loss function model from past offshore platform blowout accidents and project this data to present day figures (Benefit model);
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integrate the cost and benefit model in a probabilistic framework, and
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determine a break-even probability for an offshore development considering ORC as part of risk reduction strategy.
The paper is organized as, Section 1 provide general basis of ship cost estimation and a review of relevant literature on LFs. The methodology of this study is presented in Section 2. A case study to demonstrate the methodology is presented in Section 3. Discussions and conclusions are presented in Sections 4 and 5, respectively.
Section snippets
The Proposed Methodology
The methodology proposed here comprises three elements: cost model, benefit model and integrated probabilistic cost - benefit comparison. The flow chart of the proposed methodology is given in Figure 2.
Example location of ORC
The Flemish Pass Basin is chosen for a case study to illustrate the cost-benefit analysis of an ORC and a hypothetical hydrocarbon platform that may operate in this region. The Flemish Pass basin is located approximately 500 nautical miles offshore St. John's, Newfoundland and Labrador. Equinor Canada Ltd. (Equinor) is proposing to conduct an exploration drilling project in the Flemish Pass Basin between 2019 and 2027 [1] although this is currently uncertain due to low oil prices.
As
Discussion
This study presents a methodology to analyze the economic costs and benefits of an ORC as a risk reduction measure for use in a remote harsh offshore environment. The capital cost and operational costs are determined based on comparable historic ship cost data. A high level approximation approach is adopted rather than a detailed analysis of construction or operating costs which is not practical at the present concept evaluation phase. However, the total estimated life-cycle cost of an ORC in
Conclusions
The paper presents a probabilistic cost-benefit analysis method applied to the concept of an offshore resource centre in support of remote offshore operation. The methodology comprises estimating the total cost of ORC, developing loss model for blowout type accidents, determining the reduced loss as benefit, integrating cost-benefit models and uncertainty analysis. The proposed methodology and model provides:
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A basis for risk-based cost-benefit analysis that helps to assess the net financial
CRediT authorship contribution statement
Md Samsur Rahman: Conceptualization, Methodology, Formal analysis, Investigation, Writing - original draft, Writing - review & editing. Bruce Colbourne: Conceptualization, Methodology, Formal analysis, Writing - review & editing, Supervision. Faisal Khan: Conceptualization, Methodology, Writing - review & editing, Supervision, Project administration, Funding acquisition.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Authors thankfully acknowledge funding support from the Natural Science and Engineering Council of Canada (NSERC) and the Canada Research Chair (Tier I) program in Offshore Safety and Risk Engineering.
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