ABSTRACT:

This study analyzed seismic and well log data in an attempt to interpret relationship between rock properties and acoustic impedance and to construct amplitude versus offset (AVO) models. The objective was to study sand properties and predict potential AVO classification.  Logs of Briga 84 well provided compressional and shear velocities. AVO synthetic gather models were created using various gas/brine/oil substitutions. The Fluid Replacement Modeling predicted Class 3 AVO responses from gas sands. Log calibrated Lambda Mu Rho (LMR) inversion provided a quantitative extraction of rock properties to clearly determine lithology and fluids. Beyond the standard LMR cross-plotting that isolated gas sand clusters in the log, an improved separation of high porosity sands from shale was also achieved using λρ - µρ vs. AI. When applied to the calibrated AVO/LMR attributes inverted from 3D seismic, the λρ analysis permitted a better isolation of prospective hydrocarbon zones than standard AI inversion  Thus, as an exploration tool for hydrocarbon accumulation, the Lambda Mu Rho (λµρ) technique is a good indicator of the presence of low impedance sands encased in shales which are good gas reservoirs.