--> Rock Evolution on the Permeability-Porosity Plane: Data Sets and Models, by Philip H. Nelson, #90027 (2004)

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Rock Evolution on the Permeability-Porosity Plane: Data Sets and Models

Philip H. Nelson
U.S. Geological Survey, Denver, Colorado

The study of flow and storage in reservoir rocks (“reservoir quality”), has progressed from (1) description and classification to (2) petrophysical prediction to (3) prediction of reservoir quality before drilling by modeling the evolutionary (diagenetic) path. This paper reviews some results of (1) description and classification and (2) petrophysical prediction. 

Classification is furthered by a recently developed catalog of siliciclastic permeability and porosity data sets, supplemented with descriptors such as grain size or depositional environment, that provides examples of familiar controls on reservoir quality. The effect of grain size, so prominent in unconsolidated and poorly consolidated samples, becomes blurred as diagenesis progresses, although a high-permeability signature is commonly retained in conglomerates and coarse-grained sandstone samples. Quartz arenites are the most efficient in terms of fluid flow, maintaining high permeability at lower total porosity than rocks with lower quartz content. The presence of grain-rimming secondary minerals such as chlorite can preserve porosity while the presence of pore-blocking clays can greatly reduce permeability and porosity. These and other factors combine to determine the position and shape of core plug data on permeability-porosity plots. The patterns vary from one formation to another. 

Petrophysical prediction refers to the estimation of permeability from porosity and other measurements. Most predictive models use some form of the Kozeny-Carman equation as a starting point and may emphasize either grain size, mineralogy, surface area, or pore size as the key predictive parameter. For example, the nuclear magnetic resonance method can be classed as a surface-area method. Most satisfying are the pore size approaches, which incorporate the square of the product of pore-throat size and porosity as a predictor of permeability. Despite the widely varying diagenetic histories in siliciclastics, a simple relationship among permeability, pore-throat size and porosity does exist. Data sets plotted on the permeability-porosity plane are a projection of data clouds in three-dimensional space, with pore-throat size comprising the missing third dimension.

These results highlight issues that must be considered in the third stage of study (not reviewed herein): modeling the evolutionary (diagenetic) path from initial deposition to present-day conditions. 


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