Abstract Geologic modeling and reservoir simulation provide information critical to successful commercialization of discovered and undeveloped reserves, as well as to the effective management of producing reservoirs. Often, uncertainty associated with the reservoir&s characterization and with the geologic model can be reduced by integrating interpretations from multiple data sources, most commonly from the well and the seismic data. These data types provide very different, yet complementary information to the geologic model. The well data provide information over a broad range of scales, but these data are only sparsely sampled in the reservoir. The seismic data are more densely sampled, but provide only a limited scale of information. The integration of these two data types should properly account for their scale differences. Traditional geostatistical simulation methods do not properly account for the fact that the seismic data and the well data represent very different scales of information. Spectral Component Geologic Modeling (SCGM) properly accounts for the difference in scale between the seismic and the well data. A spectral component is an interpreted map or volume of a rock property. All spectral components contain information over a limited frequency bandwidth. A tentative geologic model is built by mathematically combining spectral components; each component providing information to the model that is limited with respect to its frequency content. The tentative geologic model is then constrained to honor the desired spatial continuity of the modeled property, the statistical distribution (histogram) of that property, and the properties measured at the well locations. Spectral simulation is used to honor the desired spatial continuity of the modeled property. With this method, the exact and non-stationary continuity information contained within the combined spectral components can be preserved in the constrained geologic model. As a result, depositional features such as sinuous channel sands, which are observed in the spectral components, are preserved in the model. An application of SCGM is presented. Results clearly show that the SCGM model honors both the spatial distribution and the spatial continuity of the modeled property, as they are represented in the spectral components.