ABSTRACT

Matrix permeability, the permeability associated with measurements on small samples, is controlled by depositional fabric and diagenesis. Prediction of matrix permeability requires: (1) specification of a fabric, (2) specification of the diagenetic state, and (3) a means to assess both factors in a sample set taken from a target basin. The data from the sample set can be used to extrapolate or interpolate within the basin or may be used to calibrate fabric response to basin history data (e.g., thermal history). The effects of fabric and diagenesis on the sample set can be determined using a combination of image analysis data and mercury porosimetry data.

Strong correlations exist between permeability and grain size of unconsolidated sands and gravels, with permeability increasing exponentially with increasing grain size. Permeability in clastic fabrics is controlled by networks of packing flaws, characterized by large pores connected by large pore throats. Such circuits comprise only a fraction of the porosity and represent the effective flow component of porosity. Diagenesis usually brings about permeability reduction, but preferentially affects the grains in close-packed arrangements that separate the networks of packing flaws. A methodology

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has been developed over the past decade that quantifies thin-section-based data precisely enough to estimate the effects of grain size and diagenesis on the rock fabric with respect to flow properties. Such rock physics data are necessary for permeability prediction as a function of basin position.