By using these techniques, you can predict curves based on existing log data, correlate core analysis to log data, and model complex porosity and permeability relationships.
With specialized modules in the GeoSoftware portfolio, you can apply ML and DL techniques to solve some of your most difficult petrophysical challenges, such as:
ML techniques can deliver significant benefits for facies classification. Facies clusters defined for a play using unsupervised analysis on a few selected wells can be applied rapidly via supervised classification to large numbers of wells across the play, bringing new scale and accuracy to these activities.
For unsupervised facies classification, PowerLog Python Extensions let you run ML algorithms using a workflow that:
Shear Velocity is often required for seismic modeling, and accurate modeling of missing Delta T Shear curves is a critical part of the process. DL workflows can help you predict these missing curves.
You can easily adapt the workflows provided by GeoSoftware to meet your specific needs. In addition, Python-knowledgeable interpreters can build custom DL workflows. You can also take advantage of open-source Python utilities and programs, which include hundreds of scientific calculations, data analysis, and visualization libraries and programs.