Geostatistics is a subfield of statistics accounts for the spatial correlations encountered in many applications of e.g. Earth Sciences. Valuable information can be extracted from these correlations, also helping to address the often encountered burden of data scarcity.

Despite the value of additional data, the use of geostatistics still falls short of its potential. This problem is often connected to the lack of user-friendly software hampering the use and application of geostatistics.

We, therefore, present GSTools, a Python-based software suite for solving a wide range of geostatistical problems. We chose Python due to its unique balance between usability, flexibility, and efficiency and due to its adoption in the scientific community. GSTools provides methods for generating random fields, it can perform kriging and variogram estimation, and much more. We demonstrate its abilities by virtue of a series of example applications detailing their use.

Instructor

  • Sebastian Müller

Things you’ll need

T22 - GSTools, a toolbox for geostatistical modeling in Python
intro