Accurate and consistent assessment of the Value of Information is a fundamental requirement for efficient management of any Oil and Gas Exploration and Production project. Although the current methods of assessment consider the uncertain nature of the input parameters used to value projects, however, it does not include the risk of ruin or bankruptcy if the case that actually occurs is one with negative or zero value (e.g. in Net Present Value terms).

In this paper, the risk attitude of the decision maker is integrated into the methodology of Value of Information using the Utility Function approach with a special focus on the oil and gas industry. The result obtained following the evaluation methodology developed shows that the Value of Information is an assessment over a set of alternatives which depend on the risk attitude of the decision maker.

Keywords:
Bayesian Inference, machine learning, Drillstem Testing, Artificial Intelligence, drillstem/well testing, Game Theory, exponential utility function, optimal alternative, assessment, information
Subjects:
Formation Evaluation & Management, Information Management and Systems, Drillstem/well testing
Copyright 2017, Society of Petroleum Engineers
You can access this article if you purchase or spend a download.