Path_i = './Txt/simple_fault_model_points.csv') # importing point-positional interface data gp.get_data(geo_data).loc].head() Path_o = './Txt/simple_fault_model_orientations.csv', # importing orientation (foliation) data # Importing the data from CSV-files and setting extent and resolution Its important to mentions that faults have to be inserted independently, where the youngest is the first entry. Then the geological series (faults / formations) are defined as well as the geological formation sequence. The orientation and geological contacts are imported from CSV files and converted into a Pandas dataframe. The coordinate system is of local coordinates, comming tutorial will evaluate the performace of Gempy with UTM coordinates. Higher resolutions are posible but the computational time will be higher. The tutorial creates a grid of 100 col x 100 rows x 100 layers over a extension of 2km x 2km x 2km. Import matplotlib.pyplot as plt Creation of the geological model object and statigraphy definition # Embedding matplotlib figures in the notebooks Since this tutorial is on Windows some complementary libraries were unable to install but the overall performance of the geological modeling code is complete. Notice the that warnings are only messages that the user have to take in mind when running the script, they do not mean a failure of the code. We configure a Jupyter option for the interactive representation of Matplotlib graphics after the script cells (%matplotlib inline). The script requires Gempy as well as Numpy and Matplotlib. In this part we import the required libraries for the tutorial. The tutorial has two parts: Part 1: Instalation of Gempy in Windows In order to make the tutorial fully accessible to the majority of users, we have created a complementary tutorial about how to install Gempy on Windows with a repository distribution of Anaconda. This tutorial is a basic example of a stratified geological setup with 5 layers and one fault. Gempy creates a grid model that can be visualized as 2D sections with Matplotlib or as 3D geometrical objects as VTK objects that allow the representation of the geologic models on Paraview for custom slicing, filtering, transparencies, and styling. The library is a complete development to create geological models from interfases, faults, and layer orientations, it also relates the sequence of geological layers to represent rock intrusions and faults order.Īlgorithm for geological modeling is based on universal cokriging interpolation with the support of high-end Python mathematical libraries as Numpy, PyMC3 and Theano. Gempy is as open source Python library for generating full 3D structural geological models.

Python 3d plot package