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  • Loading and Displaying Well Log Data from LAS Files with Python
    In this tutorial, we are going to use the lasio library developed by Kent Inverarity, to load a las file into Python and then explore its contents before making a quick look well log plot using matplotlib
  • python - Modify cells metadata - Stack Overflow
    You can create a class that extends nbconvert preprocessors ExecutePreprocessor In the preprocess (or preprocess_cell) method, add logic for storing the relevant output in the cell metadata Something like: def preprocess_cell(self, cell, resources, index): # Execute the cell normally
  • Add metadata to your book pages - Jupyter Book
    First change directories into the root of your book folder, and then run the script below as a Python script or within a Jupyter Notebook (modifying as necessary for your use case) Finally, check the changes that will be made and commit them to your repository
  • Basic Well Log Interpretation with python, pandas, matplotlib . . . - GitHub
    Basic Well Log Interpretation with python, pandas, matplotlib Added lasio to handle LASfile input Simplyfying vshale calculation Added Indonesian and Simandoux equation
  • cegal-welltools 0. 1. 0 - PyPI
    Based on open source tools such as plotly, pandas and lasio, Cegal Tools allow for simple loading, manipulation and visualising of well logs from las files Several built in plotting methods provides an easy to use, out of the box well log tool for geoscientists using or wanting to learn python
  • Loading Well Log Data From DLIS using Python - Andy McDonald
    dsstb = f object('TOOL', 'DSSTB') dsstb_params = summary_dataframe(dsstb parameters, name='Name', long_name='Long Name', values='Values') dsstb_params From the returned table, we can view each of the parameters that relate to the tool and the processing of the data
  • Wells - welly documentation - Agile
    Alternatively, you can use the Well from_las() method to load a well by passing a filename as a str This is really just a wrapper for lasio but instantiates a Header, Curve s, etc
  • python - how to programmatically add slides cell metadata in jupyter . . .
    Jupyter notebooks has a way of visualizing cell metadata so that you are able to parametrize how will cells look like when you export the notebook into slides using nbconvert Example: For instance, I would like to programmatically add that metadata into cells without using the GUI, so that I can automate slide creation, specially from google
  • welly 0. 5. 2 - PyPI
    welly facilitates the loading, processing, and analysis of subsurface wells and well data, such as striplogs, formation tops, well log curves, and synthetic seismograms For developers, there are pip options for installing test, docs or dev (docs plus test) dependencies





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