Abstract

Rock physics modelling (RPM) constitutes a foundational methodology in quantitative reservoir characterization, enabling the linkage between petrophysical properties—such as porosity, mineral composition, and fluid saturation and seismic elastic parameters, notably P-wave (Vp) and S-wave (Vs) velocities, Density, Impedance, and derived attributes like Vp/Vs ratio. A robust multi-mineral petrophysical model, incorporating quartz, mixed clay, orthoclase, calcite and pyrite (from core-log and advanced logs integration) was implemented to manage mineralogical complexity across Albian and Barremian formations in Cauvery ultra deepwater wells, having water depth in range of 1600-2500m . Given the dominance of sand-shale sequences, based on KusterToksöz(1974) and Gassmann theory frameworks, Xu-White model (1995) was employed to simulate compressional and shear wave velocities in wells with available dipole sonic data. The model explicitly considers distinct pore aspect ratios for clays and sands, making it particularly well-suited for shaly sand reservoirs. Study area, Cauvery Ultradeep water block, poses a complex depositional environment and lithology, including challenging sequences of Albian and Barremian formations. Integrating advanced petrophysical analysis with RPM, high confidence calibration and validation with measured log data, notably achieved good alignment in P-impedance and Vp/Vs cross-plots. This approach facilitated effective discrimination of reservoir facies (Vp/Vs range: 1.56–1.75) and non-reservoir facies (Vp/Vs range: 1.75–2.4) in complex settings. Overall, the study demonstrates that customized and formation-specific RPM using core to advanced logs integrated petrophysical models can reliably inform facies classification and reservoir prediction, even in geologically complex areas.