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(Lefley and Morgan, 1999), some that are inherent, others which are caused by a lack
of information or specification in the literature. As such, the knowledge that the
decision-maker can gain from the output of one tool is limited. Therefore, a combination of decision analysis techniques and concepts should be used. This would
allow the decision-maker to gain greater insights and, hence, encourage more
informed decision-making. Some writers had recognised this and presented the collection of decision analysis tools that they believed constituted those that decisionmakers ought to use for investment decision-making in the oil and gas industry (for
example, Newendorp, 1996). However, as indicated above, new techniques, such as
option theory, have only recently been applied to the industry and clearly, these
previously presented approaches required modification.
The research presented in this thesis addressed this first question by drawing on the
decision theory and industry literatures to ascertain which decision analysis tools are
the most appropriate for upstream oil companies to use for investment appraisal
decision-making. This involved firstly, identifying the whole range of techniques that
are available and, secondly, deciding which of these are the most appropriate for
upstream investment decision-making. This meant careful consideration of factors
such as the business environment of the upstream and the level and type of
information used for investment decision-making in the industry.
Through this process, the research identified the following decision analysis
techniques as particularly useful for upstream investment decision-making: the
concepts of expected monetary value and decision tree analysis, preference theory,
risk analysis, portfolio theory and option theory. Then by drawing again on the
decision theory and industry literatures, and also on insights gained at conferences
and seminars, a 9-step investment decision-making process was presented.
184 This provided an illustration of how these tools can be used together in the particular
decision situation where an upstream company is considering whether to drill an
exploration well in a virgin basin at an estimated cost of £10 million. The approach
was summarised in figure 5.12 and this is reprinted here.
1. Assess the chance of success based on historic statistics and analogues of other basins and plays
with similar geological characteristics.
2. Use sensitivity analysis to determine the critical reservoir parameters.
3. Conduct a probabilistic analysis of reserves using Monte Carlo techniques. If necessary, perform
a further sensitivity analysis here by altering the shapes of the probability distributions assigned
to the reservoir parameters and changing the nature of the dependencies between the variables.
4. Extraction from the probabilistic output of the reserves calculation of some deterministic samples
–for example, p10, p50 and p90 (high, mid, low cases).
5. Use sensitivity analysis to determine the critical economic parameters.
6. Perform a probabilistic economic analysis for each deterministic reserve case using Monte Carlo
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This document was uploaded on 03/30/2014.
- Summer '14
- The Land