petrelpy.petrel
===============

.. py:module:: petrelpy.petrel

.. autoapi-nested-parse::

   Convert between Petrel and various other formats.



Functions
---------

.. autoapisummary::

   petrelpy.petrel.write_header
   petrelpy.petrel.read_header
   petrelpy.petrel.collect_perfs
   petrelpy.petrel.export_perfs_ev
   petrelpy.petrel.export_perfs_prn
   petrelpy.petrel.read_production
   petrelpy.petrel.export_vol
   petrelpy.petrel.export_injection_vol
   petrelpy.petrel.convert_properties_petrel_to_arc
   petrelpy.petrel.read_petrel_tops
   petrelpy.petrel.write_tops
   petrelpy.petrel.get_raw_table


Module Contents
---------------

.. py:function:: write_header(df, fname, fill_na=-999)

   Write header information to a Petrel-readable header file.

   :param df: header information for wells (does not pass index)
   :type df: DataFrame
   :param fname: file to write to
   :type fname: str
   :param fill_na: value to write null values to, by default -999
   :type fill_na: int, optional


.. py:function:: read_header(fname: str) -> pandas.DataFrame

   Read headers from a file.


.. py:function:: collect_perfs(df_perf: pandas.DataFrame) -> pandas.DataFrame

   Group perforations by well.

   :param df_perf: Well completion data. Expected columns include "Date Completion",
                   "Date First Report", "Depth Top", "Depth Base" and "UWI"
   :type df_perf: pd.DataFrame

   :returns: Perforations grouped by well
   :rtype: pd.DataFrame


.. py:function:: export_perfs_ev(perfs: pandas.DataFrame, output: pathlib.Path, header: str = 'UNITS FIELD\n') -> None

   Export perforations in ev (event file) format.

   :param perfs: contains perfs in columns for API,start_depth,stop_depth
   :type perfs: pd.DataFrame
   :param output: prn file to write to
   :type output: Path
   :param header: first line for file, probably explaining units
   :type header: str


.. py:function:: export_perfs_prn(perfs: pandas.DataFrame, output: pathlib.Path) -> None

   Export perforations in prn (fixed) format.

   :param perfs: contains perfs in columns for API,start_depth,stop_depth
   :type perfs: pd.DataFrame
   :param output: prn file to write to
   :type output: Path


.. py:function:: read_production(infile: str | tuple[str], yearly=False)

   Get raw data from infile (even if infile is several files).


.. py:function:: export_vol(wells: pandas.DataFrame, outfile: str | pathlib.Path, header: str | None = None)

   Export production volumes to Petrel-readable .vol format file.

   :param wells: IHS-style wells dataframe with oil, water, and gas production.
                 Expected columns are API,Date,Liquid,Water,Gas.
   :type wells: pd.DataFrame
   :param outfile: vol file to save to
   :type outfile: str | Path
   :param header: Units and column names. Defaults to None.
   :type header: str | None, optional


.. py:function:: export_injection_vol(wells, outfile, header=None)

   Export injection volumes to Petrel-readable .vol format file.

   :param wells: IHS-style wells dataframe with water, and gas injection.
                 Expected columns are API,Date,Water,Gas.
   :type wells: pd.DataFrame
   :param outfile: vol file to save to
   :type outfile: str | Path
   :param header: Units and column names. Defaults to None.
   :type header: str | None, optional


.. py:function:: convert_properties_petrel_to_arc(fin, fout, prop)

   Make Midland basin Petrel gslib file Arc-readable.


.. py:function:: read_petrel_tops(fname: str) -> pandas.DataFrame

   Read Petrel tops file.

   :param fname: path to file
   :type fname: str

   :returns: Tops, with Well indicating the well, then a column for each surface
   :rtype: pd.DataFrame


.. py:function:: write_tops(df, fname, comments='', fill_na=-999)

   Write top picks to Petrel-readable file.

   :param df: tops picks. Expects "Well" to be first column, then a column per horizon
   :type df: DataFrame
   :param fname: Path to write out
   :type fname: str
   :param comments: Any comments to include at the beginning of the file,
                    by default ""
   :type comments: str, optional
   :param fill_na: Value to assign nulls to, by default -999
   :type fill_na: int, optional


.. py:function:: get_raw_table(fname: str | pathlib.Path, sheetname: int | str = 0) -> pandas.DataFrame

   Ingest excel, prn, or csv file.

   :param fname: file to read
   :type fname: str
   :param sheetname: sheet to extract if excel. Defaults to 0.
   :type sheetname: int | str, optional

   :returns: table
   :rtype: pd.DataFrame