Value-of-Information Lookbacks - Was the Information You Gathered Really Worth Getting?

Abstract

Abstract Due to the nature of our industry, we understand the importance of being able to value information and continue to develop skill in that domain. Daily, we face decisions regarding buying 3D seismic, taking cores and designing well tests and pilots; all with the aim to determine if it is valuable to do so prior to taking large investment decisions on our assets. This is an analysis performed at "time zero", before information is acquired. How we determine its worth post acquisition, is important, less common, and often performed incorrectly. It is also the focus of this work. This paper reviews how information is valued pre-acquisition and addresses how to take the post acquisition interpretation, and operational results, and translate them to correct lookback valuations. Many information lookbacks erroneously consider the value associated with acquiring information pre-acquisition as an integral part of the value of the information post acquisition, and then find that it does not "marry well" with the actual results. The missing step in most post information acquisition lookbacks is the proper consideration of what was interpreted from the new information, applied to the proper comparison to the actual outcome of the variable measured. For illustrative purposes, this work considers a 3D seismic reprocessing program example. It notes the development drilling success rate immediately prior to reprocessing, the interpreted location results post reprocessing, and the associated drilling results. The paper describes proper pre-information asset characterization (i.e., drilling success rate), reliability of information assessment, post information interpretation statistics, and post information drilling results. Most importantly, the paper ties the pre-acquisition value-of-information (VOI) analysis, and the reliability estimate of that information, to the post information interpretation and outcome of the measured variable. Introduction New information allows us to "update" our view of project risks and uncertainties. How well it does this depends on how reliable the information is at helping predict the true state of the variable to be measured. If information is reliable, it keeps us from making poor decisions (e.g., drilling a dry hole, or developing sub-economic fields) as often as we might have, without the new information. That in turn increases the value of our projects, given we acquire the information. Sometimes we "upgrade" our view of a project uncertainty and sometimes we "downgrade" our view. In either case, if information is reliable, we are less likely to make a poor decision (e.g., drill or develop sub-economic fields). In that respect, quality information helps clarify the risks in our projects and enables us to take appropriate action with more confidence. This increases project success by helping teams pursue more good projects and stay away from bad ones. How then do we estimate the value of information? As others have described before1, 2, in terms of asset management, we estimate the increase, or decrease, of an asset's value, after acquiring information; classically defining the value as: Value-of-Information (VOI) = (Asset Valuewith Information) - (Asset Valuewithout Information) The Information Timeline Information has different value at different points in time. Failing to recognize this leads to common errors encountered with many value-of-information lookbacks.