A shale rock physics model and its application in the prediction of brittleness index, mineralogy, and porosity of the Barnett Shale

Abstract

Summary Rock brittleness plays a significant role in effective hydraulic fracturing for shale gas production, and is often related to mineralogy, mechanical properties, and microstructure features in shales. We construct a rock physics workflow to link elastic properties of shales to complex constituents and specific microstructure attributes. Multiple compositions and various pore geometries are considered using a self-consistent approximation (SCA) method. The laminated textures due to the preferred orientations of clay particles and possible laminated distribution of kerogen are considered using Backus averaging to model the anisotropy (transverse isotropy) of shales. Results based on the analysis of the rock physics templates reveal that the degree of clay lamination significantly affects Vp/Vs of shales, whereas it has little impact on acoustic impedance of shales along the vertical direction. An increasing degree of clay lamination will increase Vp/Vs, and therefore the Poisson’s ratio. With increasing porosity, the variation of mineralogy has less impact on acoustic impedance than on Vp/Vs, which illustrates that Vp/Vs is a better indicator for lithology detection. On the other hand, acoustic impedance is a more suitable parameter to discriminate porosity compared with Vp/Vs. Our rock physics model is calibrated on the well log data from the Barnett Shale and is used to find reasonable parameters to characterize the Barnett Shale. Based on the model, we generate rock physics templates for the interpretation and prediction of shale rock brittleness, mineral constituents, and porosity from elastic properties of shales. Seismic AVO analysis based on modeling data from the top and base of the Barnett Shale illustrates that AVO intercept and gradient have predictable trends according to the variation of brittleness index, mineralogy, and porosity, which means that we can predict variations of such factors in space from seismic responses.