Petrophysical Interpretation
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Save time and resources with Machine Learning
PowerLog can connect to any open-source distribution of Python and perform in-house advanced processing to save your company time and money.
You can successfully apply machine learning and deep learning techniques with this tool including:
Machine learning in PowerLog Python Extensions enables clearer reservoir understanding and faster, more efficient data analysis so you can:
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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
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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 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
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