Model 5 - Fault

A simple fault model with constant offset. 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('fault', extent=[0, 1000, 0, 1000, 0, 1000], resolution=[50, 50, 50],
                          path_o=path_to_data + "model5_orientations.csv",
                          path_i=path_to_data + "model5_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	600	2.00e-06	rock1	NaN	NaN	NaN
	1	0	800	600	2.00e-06	rock1	NaN	NaN	NaN
	2	200	200	600	2.00e-06	rock1	NaN	NaN	NaN
	3	200	800	600	2.00e-06	rock1	NaN	NaN	NaN
	4	800	200	200	2.00e-06	rock1	NaN	NaN	NaN
	5	800	800	200	2.00e-06	rock1	NaN	NaN	NaN
	6	1000	200	200	2.00e-06	rock1	NaN	NaN	NaN
	7	1000	800	200	2.00e-06	rock1	NaN	NaN	NaN
	8	0	200	800	2.00e-06	rock2	NaN	NaN	NaN
	9	0	800	800	2.00e-06	rock2	NaN	NaN	NaN
	10	200	200	800	2.00e-06	rock2	NaN	NaN	NaN
	11	200	800	800	2.00e-06	rock2	NaN	NaN	NaN
	12	800	200	400	2.00e-06	rock2	NaN	NaN	NaN
	13	800	800	400	2.00e-06	rock2	NaN	NaN	NaN
	14	1000	200	400	2.00e-06	rock2	NaN	NaN	NaN
	15	1000	800	400	2.00e-06	rock2	NaN	NaN	NaN
	16	500	500	500	2.00e-06	fault	NaN	NaN	NaN
	17	450	500	600	2.00e-06	fault	NaN	NaN	NaN
	18	500	200	500	2.00e-06	fault	NaN	NaN	NaN
	19	450	200	600	2.00e-06	fault	NaN	NaN	NaN
	20	500	800	500	2.00e-06	fault	NaN	NaN	NaN
	21	450	800	600	2.00e-06	fault	NaN	NaN	NaN
orientations	1	100	500	600	1.00e-02	rock1	1.00e-12	1.00e-12	1.0
	3	900	500	200	1.00e-02	rock1	1.00e-12	1.00e-12	1.0
	0	100	500	800	1.00e-02	rock2	1.00e-12	1.00e-12	1.0
	2	900	500	400	1.00e-02	rock2	1.00e-12	1.00e-12	1.0
	4	500	500	500	1.00e-02	fault	8.66e-01	1.00e-12	0.5

Setting and ordering the units and series:

gp.map_stack_to_surfaces(geo_data, {"Fault_Series": 'fault',
                                    "Strat_Series": ('rock2', 'rock1')})
geo_data.set_is_fault(['Fault_Series'])

Out:

Fault colors changed. If you do not like this behavior, set change_color to False.

	order_series	BottomRelation	isActive	isFault	isFinite
Fault_Series	1	Fault	True	True	False
Strat_Series	2	Erosion	True	False	False
Basement	3	Erosion	False	False	False

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

Out:

<gempy.plot.visualization_2d.Plot2D object at 0x7fcc6bb43b20>

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:  1
Compilation Done!
Kriging values:
                     values
range              1732.05
$C_o$             71428.57
drift equations  [3, 3, 3]

sol = gp.compute_model(geo_data)

Displaying the result in x and y direction:

sphinx_gallery_thumbnail_number = 2

gp.plot_2d(geo_data, cell_number=25,
           direction='y', show_data=False, show_all_data=True)

Out:

<gempy.plot.visualization_2d.Plot2D object at 0x7fcc3012afa0>

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

Out:

<gempy.plot.visualization_2d.Plot2D object at 0x7fcc6bb43be0>

gp.plot_2d(geo_data, cell_number=25,
           direction='y', show_data=True, show_scalar=True, series_n=1)


gp.save_model(geo_data)

Out:

True