Exploration and production business faces uncertainty of our knowledge about the Earth at all stages of the aggregated workflow. Every stage uses ambiguous input and generates ambiguous output that becomes the next-stage input. Thus, understanding, quantifying and tracking uncertainty across stages and disciplines are essential for the ultimate uncertainty impacting decision making. In particular, structural uncertainty is derived from model uncertainty as a result of seismic depth imaging. Whilst the underlying ambiguity can never be fully eradicated, a quantified measure of uncertainties provides deeper understanding of the risks and leads to more informed decision making. In the past decade, with the advancement of sensor and computer technology, the seismic industry has made great improvements in data-acquisition designs as well as depth-imaging and model-building algorithms. However, the cost/benefit justification for the value of information (VoI) obtained by these technologies remains mainly qualitative. In this paper, we quantify the uncertainty involved with deciding on facility size based on estimated probability of original oil in place (OOIP), and on a parameter combining oil price, maximum recovery rate, and rate of facility-cost increase with respect to OOIP. Extension of this method will lead to more informed decision making, and justify the VoI.


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