Lithofacies identification using anisotropic parameters from logging data:A case study on Muglad Basin, South Sudan

Summary The formation identification of reservoirs using seismic reflection data and log data for anisotropic reservoirs has tendencies in differences to the true formation. Considering on the anisotropic parameters is the one of methods for reducing this difference. For the reservoir formation discrimination of lithofacies, surface geological survey, geophysical exploration, drill core, and log data are analysed. In this study we tried to find out anisotropic parameters from log data using Backus averaging, then applied it to lithofacies discrimination. We calculated Lame’s constant and shear modulus from the log data in the Muglad Basin. After applying Backus averaging to these, we obtained the stiffness coefficients then calculated the anisotropic parameters. The lithofacies for reservoirs were classified by 11 layers based on the anisotropic parameters. If there is no drill core data or drilling-cuttings, the anisotropic parameters from log data is efficient for lithofacies discrimination. The classification of sedimentary layers without drill core or drill-cuttings, this approach will be useful for discrimination of lithofacies using anisotropic parameters from Vp, Vs and density log.