Estimation of Net-to-Gross from P and S Impedance: Integration of Petrophysics and 3D Seismic Inversion

Estimation of net-to-gross (N/G) on a field wide scale was accomplished by integrating rock property trends and high quality 3D seismic data. Edited and anisotropy-corrected sonic logs from deepwater Gulf of Mexico (GoM) were used in combination with core velocity measurements and Biot-Gassmann modeling to determine shale and oil sand trends in low-frequency Vp-Vs space. These trends equally apply in the acoustic impedance (AI) and shear impedance (SI) crossplot. Shale and oil saturated sand trends in the Horn Mountain field, deepwater GoM, are basically parallel in the AI-SI crossplot and effectively bracket the reservoir facies distribution. Accurate estimates of sand volume fraction (1-Vsh) are obtainable from a simple linear interpolation between the AI-SI trends. Four angle range stacks from a 3D survey over the field were calibrated and constrained by available well control and simultaneously inverted to AI and SI. The impedance volumes closely match the upscaled log data and were combined using linear interpolation between the sand and shale trends to create a sand fraction volume. Integration of the sand fraction over the gross reservoir thickness provides an estimate of N/G at any x-y location. N/G maps can be used to predict netto-gross, predominant lithofacies and net sand thickness away from well control. The quantitative results obtained using N/G mapping markedly enhanced reservoir description of the Horn Mountain field.