--> Statistical Prediction of Porosity in the Permian Zechstein 2 Carbonate of Northern Germany, by K. M. Love, C. Strohmenger, and K. Rockenbauch; #90986 (1994).

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Abstract: Statistical Prediction of Porosity in the Permian Zechstein 2 Carbonate of Northern Germany

Karen M. Love, Christian Strohmenger, Konrad Rockenbauch

A multivariate regression model successfully predicts the areal distribution of porous dolomite vs. nonporous calcitized dolomite (dedolomite) in the Permian Zechstein 2 Carbonate of northern Germany. Although these carbonate rocks experienced numerous diagenetic modifications, an extensive calcitization of dolomites, particularly within slope deposits, degraded reservoir porosity and permeability to the greatest extent. Thus, predicting the distribution of the nonporous diagenetic calcite is crucial in predicting reservoir quality within this prolific gas play.

To predict the nonporous calcite, an integrated multivariate statistical study was conducted using location, facies and subfacies, faulting and fracturing, formation thicknesses, production rates, geochemistry, porosity, permeability, and mineralogy data. Location variables (x, y, and z) best predict calcite distribution within the slope deposits; in addition, facies and formation thicknesses contribute significantly to the prediction model. Prediction can be improved by generating separate models for areal subdivisions (on the order of several hundred sq km) of the region studied. This improvement likely reflects a structural control on calcite distribution; diagenetic fluids presumably caused calcitization along fault and fracture systems, which vary in orientation, abundance, and d stribution within structurally distinct parts of the study area. Improved prediction using the areal subdivisions also reflects the non-rectilinear distribution of facies over larger areas.

That location variables provide a reasonable predictive model is important because the predicting parameters are either known (in the case of x and y) or can be estimated fairly well (in the case of depth). In addition, reasonable input values for facies and formation thicknesses can be entered based on existing geologic models. This approach should be useful in other reservoirs, especially where porosity prediction has been complicated by diagenesis.

AAPG Search and Discovery Article #90986©1994 AAPG Annual Convention, Denver, Colorado, June 12-15, 1994