Machine Learning with Python Extensions

• Powerful and easy to use Rock Physics Models

  Build accurate rock physics models from log data and petrophysical interpretation results with PowerLog Rock Physics Module (RPM).

  This tool integrates PowerLog well-log analysis with rock physics elastic modeling. RPM enables a fundamental modeling approach — a petrophysical rock model is used to derive rock structure information and effective elastic rock properties from fluid and mineral parameters.

  You can easily analyze fluid-substitution studies and invasion correction once a rock model is constructed. The rock model also enables the prediction of elastic curves for lithology parameters that are not present in the wells.

  The RPM advantage
  RPM is the bridge between PowerLog and other Jason applications. This user-friendly module is integrated with PowerLog so you can iterate your petrophysical parameters using rock physics models in RPM and improve your petrophysics interpretation.

  Key features

  • Provides multiple models of fluid and mineral compositions
  • Integrated with petrophysics
  • Workflow-oriented
  • Easy to learn and use
  • Easy to share the workflow with others

  StatMin

• Proven technology
  StatMin is based on a technique first presented at the 1988 Society of Professional Well Log Analysts Symposium and later reprinted in the June 1991 edition of World Oil in an article entitled “A Practical Approach to Statistical Log Analysis” by William K. Mitchell and Richard J. Nelson.

  The PowerLog advantage
  StatMin is an add-on module to PowerLog®, the industry-standard petrophysical interpretation package known for its functionality and ease of use.

  StatMin solves balanced, over-determined, and underdetermined models. Under-determined models are more common where insufficient log data is available to compute all the needed minerals in one pass. StatMin provides multiple methods to deal with this important issue.

  Key features

  • Linear response equations for fast results
  • Sequential models
  • User-defined minerals
  • Alternate matrix for complex solutions
  • Solve for up to 25 minerals and fluids
  • Access to common data model for curves and zones
  • Handles multiple wells simultaneously
  • Water saturation computations also determined
  • Multiple iterations for convergent solutions