Using Self Organizing Maps to Expose Direct Hydrocarbon Indicators

Using Self Organizing Maps to Expose Direct Hydrocarbon Indicators

Utilizing machine learning in Paradise to define and reveal features not seen in conventional interpretation in an offshore Gulf of Mexico oil/gas field. The SOM analyses using DHI characteristics and seismic attributes to reveal hydrocarbon contacts, amplify attenuation features and define ampliltude conformance in a Class 3 AVO.

Eagle Ford Case Study

Eagle Ford Case Study

Latest Technology for Seismic Interpretation: Direct detection & delineation of facies architecture in the Eagle Ford Group or How did the Eagle Ford GP get Made? A presentation by Patricia Santogrossi at the 2016 SEG Annual Convention.