2014 GSA Annual Meeting in Vancouver, British Columbia (19–22 October 2014)

Paper No. 140-42
Presentation Time: 7:15 PM

STATISTICAL MODELING OF BIOGENICALLY ENHANCED PERMEABILITY IN TIGHT SANDSTONES


HSIEH, Amy I., ALLEN, Diana M. and MACEACHERN, James A., Department of Earth Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada, aih2@sfu.ca

Bioturbation is generally perceived to be detrimental to bulk permeability by reducing primary grain sorting, homogenizing sediment, and introducing mud as burrow linings and feces. Recent studies show, however, that some ichnogenera and biogenic fabrics can serve to increase porosity and permeability. In tight oil and gas reservoirs, subtle changes in sand and silt distributions, such as is generated by bioturbation, can greatly affect the resulting distribution of porosity and permeability. Despite this, permeability across unfractured sedimentary reservoirs is commonly assessed solely on the basis of average grain size.

Study of the Lower Cretaceous Viking Fm integrated sedimentary and ichnologic features to define recurring hydrofacies possessing distinct permeability grades. Grain size, ichnology, bioturbation index, and lithology were logged from core of well 14-30-22-16W4. Kmax values from plug and full diameter core samples were used to represent each hydrofacies. Hydrofacies were qualitatively defined at the bed/bedset scale based on sedimentary, ichnological and permeability attributes, all of which affect flow pathways in heterolithic facies. The Markov chain method was employed to compare the vertical transitions of permeability (Kmax) within a borehole against grain size and hydrofacies at the bed to bedset scale. This provided an intuitive framework for interpreting facies relationships such as fining-upwards sequences. The results show that in the studied core, grain size only correlates to permeability in homogeneous, very coarse- or very fine-grained rock units (e.g., sandstone or mudstone, respectively). The transiograms show that the volumetric proportions of different Kmax classes show a 15% correlation with grain size, compared to a 97% correlation with the defined hydrofacies, indicating that variations in permeability down the well are strongly related to variations in the hydrofacies. The hydrofacies approach potentially can be used as a conceptual framework for the spatial modeling of permeability in tight oil and gas reservoirs, where grain size may not control permeability distributions.