Seismic identification of carbonate reservoir sweet spots using unsupervised clustering algorithms: A case study from presalt Mero Field at Santos Basin, offshore Brazil

Abstract

This work is about machine learning (ML) unsupervised clustering algorithms such as Self Organizing Maps (SOM), Generative Topographic Maps (GTM) and K-means application on seismic multi-attributes to quickly detect high productivity (based on well drill stem test data-DST) carbonate reservoirs, such as buildups and associated platform facies.