Rock physics model-based prediction of shear wave velocity in the Barnett Shale formation

Guo, Zhiqi; Li, Xiang-Yang. 2015 Rock physics model-based prediction of shear wave velocity in the Barnett Shale formation. Journal of Geophysics and Engineering, 12 (3). 527-534.

Full text not available from this repository. (Request a copy)


Predicting S-wave velocity is important for reservoir characterization and fluid identification in unconventional resources. A rock physics model-based method is developed for estimating pore aspect ratio and predicting shear wave velocity Vs from the information of P-wave velocity, porosity and mineralogy in a borehole. Statistical distribution of pore geometry is considered in the rock physics models. In the application to the Barnett formation, we compare the high frequency self-consistent approximation (SCA) method that corresponds to isolated pore spaces, and the low frequency SCA-Gassmann method that describes well-connected pore spaces. Inversion results indicate that compared to the surroundings, the Barnett Shale shows less fluctuation in the pore aspect ratio in spite of complex constituents in the shale. The high frequency method provides a more robust and accurate prediction of Vs for all the three intervals in the Barnett formation, while the low frequency method collapses for the Barnett Shale interval. Possible causes for this discrepancy can be explained by the fact that poor in situ pore connectivity and low permeability make well-log sonic frequencies act as high frequencies and thus invalidate the low frequency assumption of the Gassmann theory. In comparison, for the overlying Marble Falls and underlying Ellenburger carbonates, both the high and low frequency methods predict Vs with reasonable accuracy, which may reveal that sonic frequencies are within the transition frequencies zone due to higher pore connectivity in the surroundings.

Item Type: Publication - Article
Digital Object Identifier (DOI):
ISSN: 1742-2132
Date made live: 07 Jul 2015 14:06 +0 (UTC)

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...