Brittleness Index Prediction in 3D Bulk Volume via Seismic Inversion in Unconventional Reservoirs

The exploitation of unconventional hydrocarbons required innovative skills to allow better characterization of brittle reservoir zone. Brittleness as an important mechanical parameter of shale reservoir has a significant effect in fracture toughness and consequently in amount of pump hours-power which is required for fracture propagation. Brittleness index (BI) depends on elastic properties of rock which are based on the rock type and its “mineral component relative contents”. Elastic properties such as Young's modulus, Shear modulus, Bulk modulus, and Poisson's ratio, could be determined from log data, but such measurements are localized over some limited and small area. For computing those elastic parameters and their variations “elastic inversion” of surface seismic data has been performed, which is a geophysical process used to recover the constituent rock properties of the earth and is a critical component for the development of unconventional reservoirs. In this study the result of inversion (elastic properties and more specifically the brittleness) has been correlated by well log data to estimate lateral and spatial distribution of Brittleness index in a 3D bulk volume. Spatial distribution of predicted brittleness will allow a better estimation of the landing zones and geosteering in the shale for an optimized frac job and the best well performance even in the area which there is no drilling record.