Evaluation of emerging shale plays often requires assessment of the distribution of porosity, fluid type, resource volumes, rock mechanical properties, and in-situ stress. In extensively drilled basins, estimates of these parameters can be obtained by building play maps from existing well data. However, in frontier basins or in plays deeper than conventional reservoirs, more reliance is placed on modeling technology. New tools are now available to provide a rigorous, systematic, and play-based approach to the evaluation of shale resources. New advances in petroleum system modeling, coupled with play chance mapping, offer an efficient and effective approach to identify " sweet spots" early in the life of plays when only limited seismic or well data are available. Traditional petroleum system modeling provides a means to predict the type, quantity, and quality of hydrocarbon remaining in source rocks, as well as the proportion of hydrocarbon that is adsorbed. Advances in petroleum system modeling also allow prediction of geomechanical properties and stress characteristics, important for assessing the potential for successful hydraulic fracture stimulation of shale reservoirs. Maps of these predicted properties are then converted to chance-of-success and volume segment maps for the shale play. Stacking of the chance maps and volume parameter segments defines the spatial variation of risks and the resource volumes, delineating the sweet spots in the play.
In this paper, we illustrate this methodology using examples from unconventional resource plays in North America. We show an example of how predictions from petroleum system modeling based on sparse data provide a good match with results of subsequent development drilling and production. Petroleum system-based assessment of in-place resources, combined with assessment of recovery factors and shared play risk, enables companies to acquire acreage that has the best probability of containing economically viable resources early in the life of the plays.