Much industry interest is centered on how to integrate well data and attributes derived from 3-D seismic data sets in the hope of defining reservoir properties in interwell areas. Unfortunately, the statistical underpinnings of the methods become less robust in areas where only a few wells are available, as might be the case in a new or small field. Especially in areas of limited well availability, we suggest that the physical basis of the attributes selected during the correlation procedure be validated by generating synthetic seismic sections from geologic models, then deriving attributes from the sections. We demonstrate this approach with a case study from Appleton field of southwestern Alabama. In this small field, dolomites of the Jurassic Smackover Formation produce from an anticlinal feature about 3800 m deep. We used available geologic information to generate synthetic seismic sections that showed the expected seismic response of the target formation; then we picked the relevant horizons in a 3-D seismic data volume that spanned the study area. Using multiple regression, we derived an empirical relationship between three seismic attributes of this 3-D volume and a log-derived porosity indicator. Our choice of attributes was validated by deriving complex trace attributes from our seismic modeling results and confirming that the relationships between well properties and real-data attributes were physically valid. Additionally, the porosity distribution predicted by the 3-D seismic data was reasonable within the context of the depositional model used for the area. Results from a new well drilled after our study validated our porosity prediction, although our structural prediction for the top of the porosity zone was erroneous. These results remind us that seismic interpretations should be viewed as works in progress which need to be updated when new data become available.