Interactive Jupyter notebook for automated interpretation of RFT / MDT pressure data.
Install requirements and open rft_interpretation.ipynb in VS Code or Jupyter. Run All, select a dataset and wells, then click Update interpretation. Adjust gradients and update as needed.
The only bundled example, data/dake_fig_2_21_digitized.csv, contains digitized points (Dake, 1994).
Custom CSV columns: Well, Depth_TVDSS (ft), P_res (psia), Mobility (mD/cP),Temp (°F); optional Fluid (Gas, Oil, Water). A custom CSV can be placed in data/ or loaded via path in the notebook.
Dake, L.P. (1994) The Practice of Reservoir Engineering. Elsevier, Amsterdam
The notebook includes this saved static figure for GitHub and separate interactive controls for use in VS Code/Jupyter.