A Real Options Analysis of the Effects of Oil Price Uncertainty and Carbon Taxes on the Optimal Timing of Oil Field Decommissioning.

AuthorAbdul-Salam, Yakubu

    As oil and gas fields reach the end of their economic and technical lifespans, they must be decommissioned to return the environment to, as far as possible, its original state in a safe, efficient and environmentally friendly manner. (1) This is a legal mandate, sanctioned in international law (UNCLOS, 1982). Decommissioning can be a highly complex and costly process, requiring highly skilled operations and personnel. It has become a topical issue in the contemporary oil and gas industry especially in relation to mature provinces such as Europe's North Sea (OGUK, 2020), although it has a longstanding history in other provinces such as the Gulf of Mexico (Bull and Love, 2019). The present value of the global oil and gas decommissioning liability is estimated to be about $340 billion (Wood Mackenzie, 2020). In the mature UK Continental Shelf (UKCS) alone, close to $1.8 billion is forecasted to be spent on decommissioning oil and gas operations annually over the coming decades (OGUK, 2020).

    At the outset, it is important to underscore a key difference between decommissioning and other major oil and gas activities such as prospecting, exploration, development and production. There is an intrinsic economic benefit incentive which motivates the involvement of private sector oil and gas operators, and in some cases governments, to these investment activities. Decommissioning however is a dis-investment. It is a legal obligation in the foremost. This obligation imposes an economic liability on operators to neutralise resource-depleted fields and to remove associated facilities at a significant economic cost to themselves.

    For private sector oil and gas operators therefore, the question of the optimal timing of the permanent cessation of production and onward decommissioning of fields is of significant strategic importance. Resolving this question is complicated by the multiple sources of uncertainty characterising the oil and gas industry. These uncertainties include those related to inherent field factors (e.g. geological characteristics, properties of rocks and fluids, reservoir pressure, etc.) and economic factors (e.g. oil prices, operating costs, etc.) (Fonseca et al., 2017; Gupta and Grossmann, 2014; Helland and Torgersen, 2014). The theory of investment under uncertainty (Dixit and Pindyck, 1994) suggests that uncertainty is an important determinant of investment and by extension, dis-investment, of which decommissioning is a type. The most important source of uncertainty in oil and gas investment economics is oil price uncertainty (Fleten et al. 2011; Garcia-Carranco et al. 2016; Helland and Torgersen, 2014). Given the high direct cost of decommissioning, and the significant loss in value to operators arising from sub-optimal timing of decommissioning (e.g. due to loss in the value of un-produced and therefore foregone oil reserves), price uncertainty has an important influence on private sector operators' timing of decommissioning and therefore the ultimate value realised in oil and gas operations.

    For governments also, sub-optimal timing of private sector oil and gas decommissioning may represent significant costs by way of the decommissioning tax reliefs they award to operators, as well as the loss of future tax revenues from the decommissioned fields. In the UK for example, up to 75% of private sector operators' decommissioning expenditures may be borne by taxpayers through government decommissioning tax reliefs (Deloitte, 2013). Government policymakers are therefore sensitive to the timing of decommissioning of private sector oil and gas operations. It is against this background for example that the UK government and allied institutions have renewed focus on maximising economic recovery (MER) from oil and gas resources in the UKCS (OGA, 2016). Preventing sub-optimal decommissioning is an important part of the overall UK MER strategy.

    Conversely however, early decommissioning may be desirable for policymakers in jurisdictions where the primary goal is to facilitate the drive away from fossil-based energy sources such as oil and gas in order to accelerate the transition to clean and sustainable renewable energy sources. In Norway for example, upstream oil and gas operations are required to offset carbon emissions through mandatory participation in the EU emissions trading scheme. Carbon taxes are also imposed. The internalisation of upstream emission externalities adds to the operating expenditures of private sector oil and gas operators. Over the long run, this has the effect of prompting earlier cessation of production and onward decommissioning of oil and gas operations.

    For policymakers therefore, whether the goal is to enhance MER and/or to facilitate a drive towards energy transition, understanding the effect of oil and gas price uncertainty on private sector operators' optimal timing of decommissioning is critical. As Muelenbachs (2015) argues, the shale oil and gas boom make it ever more relevant for policymakers to understand oil and gas operators' decommissioning propensities. This understanding would help identify windows of opportunity for policy interventions leading to MER and/or sustainable energy transition. Interventions aimed at a MER goal for example may be in the form of favourable fiscal measures (e.g. reduction in upstream taxes) so as to extend the life of oil and gas operations in periods where the likelihood of early private sector decommissioning is high. The opposite policy course is true for interventions aimed at a drive towards energy transition (e.g. high carbon taxes).

    In a more certain and stable world, metrics based on deterministic discounted cashflow analysis may be used to determine optimal investment and dis-investment decisions (e.g. Net Present Value, Internal Rate of Return, etc.). In an oil and gas industry with significant and inherent uncertainties however, these methods may not adequately represent these uncertainties and therefore may not provide realistic indicators of the value of oil and gas operations hence leading to misplaced investment and/or dis-investment (decommissioning) decisions.

    In recent decades, the real options (henceforth RO) approach has become the most favoured method for examining investment decisions under uncertainty in the academic literature (Dixit and Pindyck, 1994; Luehrman, 1998; Trigeorgis, 1996). This approach inherently incorporates the nature of uncertainty and the value of information and managerial flexibility. It is hence especially suited for decision-making in the oil and gas industry due to these attributes, as well as the natural characteristics of the industry itself. Several papers have used the RO approach to explore decision-making in the oil and gas industry. The options often considered include to 'defer investment', 'optimal timing of an investment', 'alter the scale of an investment', 'decommission (abandon) a project', and so on. Fleten et al. (2011) for example use the RO method to explore the flexibility related to investment timing in offshore oil and gas exploration and production. They specifically explore the option for larger fields to tie-in smaller fields which, as standalone developments, are economically not viable. Ekern (1988) uses the RO approach to examine the valuation of satellite fields and adding incremental capacity. They find that seemingly unprofitable satellite fields can have an option value. Lund (1999) uses the RO method to explore the optimal investment timing and size of oil and gas production rigs, taking into consideration the uncertainty regarding oil prices, reservoir sizes and well rates. Other studies using the RO method to explore investment decision-making in the oil and gas industry include Armstrong et al. (2004), Chorn and Shokhor (2006), Steck (2018), Agerton (2020) and so on.

    Studies with robust treatment of the option to decommission (abandon) an oil and gas field using an RO approach are however relatively few. Amongst the studies with significant treatment of this option include Smith and McCardle (1998) who examine the timing of investment, the option to vary the production rate by drilling additional wells and the option to decommission, taking into consideration stochastic production rates and oil prices. Santa-Cruz and Heredia-Zavoni (2011) also examine the option to decommission an oil field, taking into consideration the uncertainties associated with oil prices, maintenance costs, environmental loading, rig structural capacity, etc. More recently, Muehlenbachs (2015) examined the issue of operator mothballing of oil and gas fields as a means of avoiding the high expenditures associated with permanent decommissioning. Dias (2004) and Trigeorgis and Tsekrekos (2018) provide an overview of the use of RO methods in the oil and gas industry and more generally. This paper makes a significant contribution to the relatively scant literature examining the option to decommission an oil field using a RO approach.

    Specifically, we use a RO model to examine the effect of three important sources of oil price uncertainty on the optimal timing of decommissioning for an example oil field. These are (1) the degree of oil price volatility, (2) the level of the long-run equilibrium oil price, and (3) the speed of reversion of oil prices to their long-run equilibrium. The levels and trends of these sources of oil price uncertainty encapsulate many of the factors that affect the dynamics of the global oil markets which then ultimately impact the optimal timing of decommissioning of oil fields. For example, significant technological advancements in more recent years have resulted the US tight oil boom which has in turn caused a large downward pressure on the long-run equilibrium oil price (Kilian, 2017). Similarly, the degree of the volatility in oil prices results from several factors including shifts in oil demand (Kilian, 2010) as observed since the...

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT