Seismic data can provide useful information for prospect identification and reservoir characterization. Combining seismic attributes helps identify different patterns, thus improving geological characterization. Machine learning applied to seismic interpretation is very useful in assisting with data classification limitations.

This article discusses the use of machine learning to characterize carbonate facies in a wildcat prospect in the Santos basin, offshore Brazil.