Impact of Petrophysical and Geomechanical Modelling on Brittleness Index

Abstract

Abstract Rock fabric and physical properties are known indicator of the fracturing potential of unconventional reservoirs under hydraulic fracturing stimulation. However, very limited study is documented on reservoir cut offs to find fracturing potential. Therfore, systematic workflow adopted to estimate reservoir properties and their relationship with brittleness index. For this purpose, the One-Dimensional Mechanical Earth Model (MEM) and multi-mineral petrophysical models is developed to estimate reservoir properties based on laboratory experiments and well logs. Rock brittleness (BI_T) is estimated using petrophysical properties and elastic properties. The reservoir cut offs determined to classify reservoir into brittle and ductile zones. The correlations indicated that higher concentration of minerals quartz and siderite, and young's modulus (YM_Cali) enhance brittle nature of rock, while higher concentration of organic richness (TOC), porosity (φT), clay contents, and Poisson's ratio enhance ductile nature of rock. The gamma ray log indicated a decreasing trend with an increase in brittleness index. However, there is no significant relationship observed between BI_T, pore pressure and strength/failure parameters except few zones, where BI_T decrease with an increase in pore pressure that is attributed to higher clay minerals in such zones. There is significant decrease in BI_T observed with an increase in fracturing pressure. It implies that brittle rock requires less fracturing pressure to induce hydraulic fractures or open natural fractures. Both shale formations had an organic richness of 3% to 5%, total porosity, φT, of 5% to 20%, and a BI_T of 0.15 to 0.7. It is observed that calibrated values lied between static and dynamic geomechanical properties, which is considered actual reservoir properties. The stress regime is strike slip due to higher magnitude of maximum horizontal stress (σH). Furthermore, the several correlations could be used to classify reservoir into brittle and ductile zones, which would enable the better selection of intervals for fracturing. The model indicated that the Roseneath shale was potentially better than the Murteree shale for stimulation purposes because of its high BI_T, and favourable stress concentration, which is attributed to its high content of quartz and siderite, and relatively less organic matter. However, generally, both shale formations fall in the region of "less brittle". It is recommended that reservoir properties could be computed from top to bottom of interval by integrating core and well logs data due to good agreement between core and well logs which could be used to assess fracturing potential of reservoir. The reservoir cut offs can be used as a proxy to find fracturing potential in unconvemntional reservoirs.