LAUSR

The Value of Information (VoI) analysis typically assesses information opportunities to manage uncertainty. The VoI is traditionally estimated using the expected monetary value (EMV), which overlooks the decision maker's (DM) attitude towards upsides and downsides. In this study, we assess the VoI for DMs with different attitudes, under different levels of information reliability. We define attitude to be as: neutrality to upsides and downsides, aversion to downside risk, and willingness to exploit upside potential. We applied a simple and flexible formula, which incorporates EMV with lower and upper semi-deviations from a benchmark, to quantify downside risk and upside potential. We determined VoI using many uncertain scenarios to maintain interactions between parameters instead of deterministically isolating the uncertainty under analysis. To accelerate analysis and reduce computational costs, we used a set of candidate production strategies optimized for extremely different scenarios. Our case study was the UNISIM-I-D, a benchmark reservoir model with a key structural uncertainty affecting production strategy selection. We used an appraisal well as an information source, and four hypothetical DMs with different attitudes. Our results showed that these DMs value information differently, that one DM may decide to acquire information while another may not, for the same situation. In our case study, information reduced downside risk but did not increase upside potential, meaning that information was more valuable to risk-averse DMs (which was up to 20 times higher), and less valuable to DMs exclusively focused on maximizing upsides. Introduction Acquiring additional information before deciding on field development is common in uncertainty management. However, the cost and potential delays in production should not outweigh the benefits of acquiring additional information. The Value of Information (VoI) methodology quantifies the advantages of acquiring additional information. This calculation is essential because reducing uncertainty or increasing confidence in a decision has no value in itself. To add value, the information must: change our understanding of the uncertain parameter, have the potential to influence a decision that would be made otherwise, and cost less than its value (e.g. Delquié, 2008; Bratvold et al., 2009). Various measures determine information value, including: expected utility, selling price of information, buying price of information, probability price, and certainty equivalent (cf. Delquié, 2008; Abbas et al.,