Model 4 - Pinchout

Forcing GemPy to create a layer of varying thickness. We start by importing the necessary dependencies:

Importing GemPy

import gempy as gp

import pandas as pd
pd.set_option('precision', 2)

Creating the model by importing the input data and displaying it:

data_path = 'https://raw.githubusercontent.com/cgre-aachen/gempy_data/master/'

path_to_data = data_path + "/data/input_data/jan_models/"
geo_data = gp.create_data('pinchout',
                          extent=[0, 1000, 0, 1000, 0, 1000], resolution=[50, 50, 50],
                          path_o=path_to_data + "model4_orientations.csv",
                          path_i=path_to_data + "model4_surface_points.csv")

Out:

Active grids: ['regular']

geo_data.get_data()

		X	Y	Z	smooth	surface	G_x	G_y	G_z
surface_points	0	0	200	300	2.00e-06	rock1	NaN	NaN	NaN
	1	0	800	300	2.00e-06	rock1	NaN	NaN	NaN
	2	500	200	375	2.00e-06	rock1	NaN	NaN	NaN
	3	500	800	375	2.00e-06	rock1	NaN	NaN	NaN
	4	1000	200	450	2.00e-06	rock1	NaN	NaN	NaN
	5	1000	800	450	2.00e-06	rock1	NaN	NaN	NaN
	6	0	200	700	2.00e-06	rock2	NaN	NaN	NaN
	7	0	800	700	2.00e-06	rock2	NaN	NaN	NaN
	8	500	200	625	2.00e-06	rock2	NaN	NaN	NaN
	9	500	800	625	2.00e-06	rock2	NaN	NaN	NaN
	10	1000	200	550	2.00e-06	rock2	NaN	NaN	NaN
	11	1000	800	550	2.00e-06	rock2	NaN	NaN	NaN
orientations	3	500	500	375	1.00e-02	rock1	-0.15	1.00e-12	0.99
	4	500	200	375	1.00e-02	rock1	-0.15	1.00e-12	0.99
	5	500	800	375	1.00e-02	rock1	-0.15	1.00e-12	0.99
	0	500	500	625	1.00e-02	rock2	0.15	1.00e-12	0.99
	1	500	200	625	1.00e-02	rock2	0.15	1.00e-12	0.99
	2	500	800	625	1.00e-02	rock2	0.15	1.00e-12	0.99

Setting and ordering the units and series:

gp.map_stack_to_surfaces(geo_data,
                         {"Strat_Series": ('rock2', 'rock1'),
                          "Basement_Series": ('basement')})

	surface	series	order_surfaces	color	id
0	rock1	Strat_Series	1	#015482	1
1	rock2	Strat_Series	2	#9f0052	2
2	basement	Basement_Series	1	#ffbe00	3

gp.plot_2d(geo_data, direction=['y'])

Out:

<gempy.plot.visualization_2d.Plot2D object at 0x7f3197bd1970>

Calculating the model:

interp_data = gp.set_interpolator(geo_data, theano_optimizer='fast_compile')

Out:

Setting kriging parameters to their default values.
Compiling theano function...
Level of Optimization:  fast_compile
Device:  cpu
Precision:  float64
Number of faults:  0
Compilation Done!
Kriging values:
                    values
range             1732.05
$C_o$            71428.57
drift equations    [3, 3]

sol = gp.compute_model(geo_data)

Displaying the result in x and y direction:

gp.plot_2d(geo_data, cell_number=[25],
           direction=['x'], show_data=True)

Out:

<gempy.plot.visualization_2d.Plot2D object at 0x7f326f5a4a00>

sphinx_gallery_thumbnail_number = 3

gp.plot_2d(geo_data, cell_number=[25],
           direction=['y'], show_data=True)

Out:

<gempy.plot.visualization_2d.Plot2D object at 0x7f321a8c9e80>

gp.save_model(geo_data)

Out:

True