Feature Engineering

Accurate well-log interpretation is important for reservoir evaluation near well bores. However, conventional well-log interpretation techniques do not give accurate results in heterogeneous reservoirs.
We develop a workflow using feature engineering and machine learning methods to incorporate the spatial continuity and geological concepts of the reservoir into the interpretation process.
We find that machine learning methods successfully learn the geological concepts (patterns) and use them to give more accurate well-log interpretation results and better capture the flow conduits and barriers along the well.
We recommend the use the new workflow when accurate well-log interpretation is needed, and core data are available for validation.
Development of new features that integrate spatial information into machine learning and other  types of models.