APPLICATION OF ANISOTROPIC ELASTIC INVERSION ON LITHO-FLUID FACIES PREDICTION USING MACHINE LEARNING IN X-FIELD, CENTRAL MALAY BASIN - MOHAMMED GOUDA, MOHAMMED FATHY MAHFOUZ (2020)
Reservoir characterization is an essential step that contributes to the final drilling decision in hydrocarbon-development projects. Seismic data is considered a crucial source of data that helps to identify the litho-fluid facies distribution in reservoir rocks. Accordingly, this study aims at inverting for the zero-offset acoustic and shear-impedance volumes and transforming them into elastic attributes which act as inputs to the facies model. The second objective is to predict the litho-fluid facies distribution from the optimum set of lithology and fluid predictors. This study shows how to reduce the ambiguity in facies discrimination and mitigate the effect of seismic anisotropy in order to enhance the facies model’s accuracy.