--> Abstract: Predicting Fracability in Shale Reservoirs, by John A. Breyer, Helge Alsleben, and Milton B. Enderlin; #90124 (2011)

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Making the Next Giant Leap in Geosciences
April 10-13, 2011, Houston, Texas, USA

Predicting Fracability in Shale Reservoirs

John A. Breyer1; Helge Alsleben1; Milton B. Enderlin2

(1) School of Geology, Energy and the Environment, Texas Christian University, Fort Worth, TX.

(2) Energy Institute, Texas Christian University, Fort Worth, TX.

Effectiveness of fracture stimulation techniques is controlled by the heterogeneous and anisotropic nature of rocks. Sedimentologic and stratigraphic models, the interaction of present-day and induced stress, and rock material properties, which are constrained by composition and mineral distribution, nature of primary sedimentary fabric, and presence and orientation of preexisting planes of weakness, can explain rock behavior.

The Barnett Shale in the Fort Worth basin is dominated by siliceous mudstone to claystone with a clay mineral and cryptocrystalline quartz matrix. Laminated argillaceous lime mudstone and skeletal, argillaceous lime packstone are also abundant and several other facies are less common. Facies distributions in the central and eastern part of the basin are related to their location relative to advancing shale wedges and differ between proximal, distal, axial, and fringe depositional settings.

Fracability is a function of material brittleness and ductility, which can be inferred from Young’s modulus and Poisson’s ratio. We calculate values from bulk density and acoustic slowness well log measurements and incorporate unconfined compressive strength (UCS) and internal friction angle (IFA) strength parameters with these constants. Hand-held penetrometer and micro-rebound hammer (MRH) measurements are used to estimate UCS and IFA. These measurements are performed at a frequency and scale as to be reconcilable with well logs and detailed petrographic, fabric and TOC data and allow calibration of petrographic data and indices of brittleness and ductility with log readings.

To address the behavior of shale reservoirs, we integrate qualitative and quantitative data. These data include core and thin section descriptions, penetrometer and MRH readings, description of present-day stress field using a stress-strength equilibrium stress polygon approach, which includes estimates of overburden stress, maximum horizontal stress, minimum horizontal stress, and direction of maximum horizontal stress. Using stress estimates, fracture orientation data from borehole image logs, and pore pressure estimates, we calculate pressures needed to reactivate favorably oriented preexisting planes of weakness in shear. This approach establishes a means of calibrating lithology with well log response, allows correlation between lithology and rock strength, and predicts fracability based on these features and the nature of the in situ stress field.