It has only recently begun to attract significant

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: f the decisions taken in the upstream. These are: they form part of a multi-stage decision process (figure 5.1); they are, to a large extent, irreversible; there is uncertainty associated 165 with most of the input parameters to the decision analysis; and a decision-maker can postpone the decision to allow the collection of additional data to reduce risk and uncertainty. These characteristics mean that traditional DCF techniques can be modified through the application of option theory (see, for example, Dixit and Pindyck, 1998 and 1994) to assign credit to an opportunity for being able to assess and to avoid the downside uncertainty involved in a decision by aborting or postponing that decision until certain conditions are met. Many companies having been doing this to a limited extent, perhaps without realising that it represented the application of option theory, through the use of decision trees. The simple representation given by the decision tree in figure 7.1, illustrates the benefit of minimising expenditures by realising that a discovery may be too small to be economic and exercising the option of limiting investment to exploration and appraisal seismic and drilling, and waiting until commercial considerations (price, costs, taxes) change and the field becomes economic, or not developing at all, rather than developing at a loss. Dixit and Pindyck (1994) outline more rigorous mathematical techniques for assessing the option value of the uncertainty in an investment over which one has the ability to delay commitment, but the principle is the same. The value of applying option theory to the oil industry has still to be proven. It has only recently begun to attract significant attention within the industry literature and there is no software currently available to automate its use. £M Chance % £M Cost/value xx N co onm m er ci a Discovery P90 P50 xx = xx Dry Hole * xx * xx = xx * xx = xx xx * xx = xx xx * xx = xx xx Cost/value Cost/value xx xx l Commercial P10 Opportunity EMV Figure 7.1: A decision tree 166 = xx 13 Preference, or utility, theory. As indicated in Chapter 5, this aspect of decisionmaking recognises the fact that companies (or, indeed, decision-makers within companies) do not all have the same attitude towards money. For example, a smaller company will be much less able to sustain losses than a larger company, and will therefore be much more wary of risky projects with downside risks that could bankrupt the company. Whilst preference theory has been widely applied to the industry in the literature, its value is questionable. There are difficulties in obtaining preference curves and in the construction of corporate preference curves. There is, however, some software available to automate the technique. For techniques 8-13, two points will be assigned where the technique is used routinely in organisations for investment appraisal and appropriate training is given to staff. One point will be allocated for partial implementation and zero points for non-usage. 14 Qualitat...
View Full Document

Ask a homework question - tutors are online