Abstract

Summary Appraisal programs undertaken by exploration and production (E&P) companies are designed to resolve subsurface uncertainties that contribute to uncertainty in the economic potential of undeveloped fields. Value-of-information (VOI) assessments allow E&P players to quantify the economic value of their proposed appraisal programs before carrying them out. This study proposes a VOI methodology that is tuned to the nature of the subsurface uncertainties in unconventional plays and is capable of assessing a wide range of appraisal strategies (defined as the number and configuration of wells). It addresses two main problems. The first is how to characterize the uncertainty (in a play) that an appraisal program is intended to reduce or resolve. The second is how to cast that characterization of the uncertainty in a VOI context so that the merits of various appraisal programs can be evaluated. This paper characterizes the subsurface uncertainty that arises because of inadequate sampling of natural geologic variability. In this work, three quantities are assumed to be uncertain: the mean and standard deviation (SD) (variability) of the expected ultimate recovery (EUR) of the population of wells to be drilled, should development go ahead, and the range of the variogram that describes the spatial correlation of EUR as a function of the distance between wells. The optimal appraisal program would presumably depend on the true values of these quantities. The methodology is illustrated by application to a typical unconventional play. The VOI of an appraisal program can be optimized in terms of the number of the appraisal wells to be drilled and the placement of those wells. This VOI increases as the placement of the set of wells is changed from being clustered in the central part of the appraised area to approaching uniform distribution across the area. To obtain the optimal well placement, the incremental learning from changing the well locations should be balanced against the incremental costs that are required to increase the spacing of the appraisal wells. The study results demonstrate how the VOI of each incremental appraisal well decreases with the number of appraisal wells and how an optimal number of appraisal wells can be determined.

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