terranigma-solutions / subsurface

Core data exchange library for subsurface science and engineering

subsurface

DataHub for geoscientific data in Python. Two main purposes:

• Unify geometric data into data objects (using numpy arrays as memory representation) that all the packages of the stack understand

• Basic interactions with those data objects:

  • Write/Read
  • Categorized/Meta data
  • Visualization

Data Levels

The difference between data levels is not which data they store but which data they parse and understand. The rationale for this is to be able to pass along any object while keeping the I/O in subsurface:

HUMAN

‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾/ = = = = = = = = = = = = = = /. -> Additional context/meta information about the data

= = = = geo_format= = = = /. . = = = = = = = = = = = = /. . . -> Elements that represent some

= = = geo_object= = = /. . . . geological concept. E.g: faults, seismic

= = = = = = = = = = /. . . . ./

= = element = = = /. . . . / -> type of geometric object: PointSet,

= = = = = = = = /. . . ./ TriSurf, LineSet, Tetramesh

primary_struct/. . . / -> Set of arrays that define a geometric object:

= = = = = = /. . ./ e.g. StructuredData, UnstructuredData

DF/Xarray /. . / -> Label numpy.arrays

= = = = /. ./

array /. / -> Memory allocation

= = /./

= //

/

COMPUTER

Documentation (WIP)

Note that subsurface is still in early days; do expect things to change. We welcome contributions very much, please get in touch if you would like to add support for subsurface in your package.

An early version of the documentation can be found here:

https://softwareunderground.github.io/subsurface/

Direct links:

• Developers-guide
• Changelog

Installation

pip install subsurface

or

conda install -c conda-forge subsurface

Be aware that to read different formats you will need to manually install the specific dependency (e.g. welly to read well data).