xtgeo

To help you get started, we've collected the most common ways that xtgeo is being used within popular public projects.

equinor / xtgeo / tests / test_grid3d / test_grid_properties.py View on Github

def test_import_init():
    """Import INIT Reek"""

    g = Grid()
    g.from_file(GFILE1, fformat="egrid")

    x = GridProperties()

    names = ['PORO', 'PORV']
    x.from_file(IFILE1, fformat="init",
                names=names, grid=g)

    # get the object
    poro = x.get_prop_by_name('PORO')
    logger.info("PORO avg {}".format(poro.values.mean()))

    porv = x.get_prop_by_name('PORV')
    logger.info("PORV avg {}".format(porv.values.mean()))
    assert poro.values.mean() == pytest.approx(0.1677402, abs=0.00001)

View more ways to use xtgeo

Introduction

XTGeo is a LGPL licensed Python library with C backend to support manipulation of (oil industry) subsurface reservoir modelling. Typical users are geoscientist and reservoir engineers working with reservoir modelling, in relation with RMS. XTGeo is developed in Equinor.

Detailed documentation for XTGeo at Read the Docs

Feature summary

• Python 3.8+ support
• Focus on high speed, using numpy and pandas with C backend
• Regular surfaces, i.e. 2D maps with regular sampling and rotation
• 3D grids (corner-point), supporting several formats such as RMS and Eclipse
• Support of seismic cubes, using segyio as backend for SEGY format
• Support of well data, line and polygons (still somewhat immature)
• Operations between the data types listed above; e.g. slice a surface with a seismic cube
• Optional integration with ROXAR API python for several data types (see note later)
• Linux is main development platform, but Windows and MacOS (64 bit) are supported and PYPI wheels for all three platforms are provided.

Installation

For Linux, Windows and MacOS 64bit, PYPI installation is enabled:

pip install xtgeo

For detailed installation instructions (implies C compiling), see the documentation.

Getting started

import xtgeo

# create an instance of a surface, read from file
mysurf = xtgeo.surface_from_file("myfile.gri")  # Irap binary as default

print(f"Mean is {mysurf.values.mean()}")

# change date so all values less than 2000 becomes 2000
# The values attribute gives the Numpy array

mysurface.values[mysurface.values < 2000] = 2000

# export the modified surface:
mysurface.to_file("newfile.gri")

Note on RMS Roxar API integration

The following applies to the part of the XTGeo API that is connected to Roxar API (RMS):

> RMS is neither an open source software nor a free software and > any use of it needs a software license agreement in place.