Sound decision making requires the elicitation and quantification of key uncertainties. Probabilities are, in general, subjective and most petro-technical experts find assessing them challenging. Furthermore, much evidence shows that, although they may not be aware of it, assessors find it difficult to make unbiased assessments.
We show how the maximum entropy principle, an idea from information theory, can be used to overcome the challenge of uncertainty assessment in oil & gas decision-making situations. It has found great popularity in natural language processing, space communication, biomedical engineering, and many other fields but has received limited attention in oil & gas. After describing how the technique can be adapted to information typical of oil and gas, we illustrate its application to a field development decision.
We conclude that the maximum entropy approach can incorporate many types of partial information. The examples and applications in this paper illustrate the relevance and power of the approach for quantifying probabilities in the context of oil E&P decision making. It is shown that arbitrarily "interpolating" between assessed probabilities, or ignoring dependencies, can lead to biased probability distribution, which in turn may lead to sub-optimal decisions.