Abstract

Facies volumes were obtained in southwestern Venezuela reservoirs integrating rock-physics analysis and seismic-inversion results. Facies volumes showed a sandstone-shale spatial distribution that matches log data and the conceptual sedimentologic model of the reservoir. After seismic-gather conditioning, applying a simple but robust processing sequence, the signal-to-noise ratio was increased. Two angle stacks were generated to perform a simultaneous seismic inversion to obtain P- and S-wave impedance volumes. Parallel to the inversion process, rock-physics analysis was done using rock-physics templates (RPT) for constant-cement models (CCM) to discriminate between sandstone and shale. P- and S-wave impedance bivariate probabilistic density functions (PDF) were computed from well-log data as an a priori probability. Finally, these PDFs were used to classify facies from P- and S-wave impedance volumes obtained from simultaneous inversion, using a Bayesian probabilistic approach. This classification produced two facies volumes, sandstone and shale, which honored the well information and rock-physics models.

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