Previous studies have shown that integration of well production data in geological reservoir modeling can greatly improve the reliability of reservoir performance forecasting by providing more information on the spatial distribution of permeability. The geologic modeling is further enhanced by honoring reservoir facies data derived from well logs and geologic depositional description. Production data can provide an indicator of facies that is tied to the reservoir＇s performance. This paper presents a new methodology to derive facies-proportion maps from multiple-well, single-phase production data and illustrates how these maps can be utilized for integrated reservoir modeling. A geostatistically based inverse technique, the sequential self-calibration (SSC) method, is used to first generate a series of coarse-scale permeability maps from production data. Facies-proportion maps are then derived from these permeability maps through a calibration relationship between facies proportion and effective block permeability. We quantify the uncertainty and illustrate the limitations of the resulting facies-proportion maps due to the non-unique character of both the calibration and the inverted coarse-scale permeability maps. The facies-proportion maps are to be used along with well petrophysical data, conceptual and descriptive geologic models, as well as seismic data to create fine-scale geostatistical reservoir models for reservoir management. The production data are thus honored indirectly in the final reservoir models.