Natural Fracture Characterization of the Travis Peak Formation, East Texas: Application of New Rock Testing and Modeling Methods

By

RIJKEN, P., HOLDER, J., and OLSON, J.E.

Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX

LAUBACH, S.E.

Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, Austin, TX

Fluid flow prediction in naturally fractured reservoirs is challenging, as fracture pattern attributes such as aperture, spacing, length and connectivity are difficult to obtain from core samples and logs. We combine two methods that circumvent this sampling problem to predict fracture characteristics within the Travis Peak Formation. Firstly, micro-fractures are used to estimate conductivity and orientation of macro-fractures. Secondly, a geomechanical approach is employed to estimate the other geometric properties of a fracture pattern. This model uses subcritical fracture index, a rock property, and geological boundary conditions as input.

The relationship between micro-fractures and macro-fractures has been established in literature. Likewise, subcritical fracture index has been shown to influence natural fracture pattern characteristics such as length, spacing and connectivity. However dependence of subcritical index on petrologic features is still largely unknown. Therefore, suites of subcritical fracture growth experiments were performed on the Travis Peak Formation to determine systematic variations in subcritical fracture index. Observations show that subcritical fracture index increases with decreasing grain size. Preliminary testing also suggests that subcritical index decreases with increasing carbonate cement. To investigate further, tests were run adding artificial cement to previously tested samples, resulting in increased strength, but decreased subcritical index. We postulate that this kind of artificial cementing of the sample can be equated to secondary carbonate cementation. Using these techniques and understanding the depositional and diagenetic history of a reservoir allows for natural fracture pattern prediction without extensive sampling.