--> Abstract: Permeability Prediction in Chalks, by M. M. Alam, R. Sharma, M. Prasad, and I. L. Fabricius; #90090 (2009).

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Permeability Prediction in Chalks

Alam, Mohammad M.1; Sharma, Ravi 2; Prasad, Manika 2; Fabricius, Ida L.1
1 Environmental Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark.
2 Petroleum Engineering, Colorado School of Mines, Golden, CO.

Permeability of North Sea chalk from a reservoir zone was estimated by using porosity, specific surface area, velocity, density and resistivity data measured in core plugs. We investigated the use of velocity and resistivity data to predict permeability from wireline logging data.

We first examined the nature of relationships between permeability and porosity. We then extended the porosity-permeability relationship to seismic velocity and formation factor using laboratory data. We further explored theoretical confines and limits for these empirical permeability predictions, analyzed them statistically for reliability, and applied them to well log data.

We used core plug data of 12 samples from Ekofisk and Tor formations along with published data for these formations. The Ekofisk samples have high specific surface area due to their high clay content (more than 12%). The smaller specific surface area in the Tor formation is due to high CaCO3 content (more than 95%). We studied the influence of Flow Zone Indicator (FZI) and specific surface on Kozeny’s equation. Formation factor, F of Archie’s equation and permeability relation was analyzed for cementation factor, m.

We found that the porosity-permeability relationship can be improved by separating in to FZI units. Knowing the specific surface area by Nitrogen adsorption (BET), permeability can be closely predicted by using Kozeny’s equation. A correlation coefficient of 0.89 was found between Klinkenberg corrected liquid permeability and permeability calculated with the Kozeny equation and BET specific surface area. The formation factor and permeability are also correlated (R2 = 0.83). We will explore the potential of permeability prediction by using resistivity data and extending the predictions to well logs.

 

AAPG Search and Discovery Article #90090©2009 AAPG Annual Convention and Exhibition, Denver, Colorado, June 7-10, 2009