Note

Click here to download the full example code

1.2b: The Implicit coKriging class¶

Importing GemPy

import gempy as gp

# Importing auxiliary libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

pd.set_option('precision', 2)

The description of the methods nomenclature remains the same as for the data.py module with the particularity that update is slitted in:

update_from
- update current object with the rest of dependencies. This is useful if you change an object and you want to update the fields with the rest of the objects. E.g after a set_surface_points
update_to
- update dataframes from the current object. This is useful if you modify one of the model dependencies and you want to update all the other dependencies

When we initialize a gempy.core.model.Project class we create all the necessary objects already linked with each other.

model = gp.Project()

As expected these dependencies are empty:

model.surface_points

	X	Y	Z	smooth	surface

model.surfaces

	surface	series	order_surfaces	color	id

model.stack

	order_series	BottomRelation	isActive	isFault	isFinite
Default series	1	Erosion	False	False	False

The pandas DataFrames are already configured properly to categories:

model._surfaces.df['series'], model._surfaces.df['surface']

Out:

(Series([], Name: series, dtype: category
Categories (1, object): ['Default series']), Series([], Name: surface, dtype: object))

And additional data has everything pretty much empty:

model._additional_data

		values
Structure	isLith	True
	isFault	False
	number faults	0
	number surfaces	0
	number series	1
	number surfaces per series	[0]
	len surfaces surface_points	[]
	len series surface_points	[0]
	len series orientations	[0]
Options	dtype	float64
	output	geology
	theano_optimizer	fast_compile
	device	cpu
	verbosity	None
Kriging	range	0.0
	$C_o$	0.0
	drift equations	[3]
Rescaling	rescaling factor	NaN
Rescaling	centers	[nan, nan, nan]

Reading data¶

Usually data will be imported from external files. GemPy uses pandas.read_table powerful functionality for that. The default format is XYZ surface_name:

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

model.read_data(path_i=data_path + "/data/input_data/tut_chapter1/simple_fault_model_points.csv",
                path_o=data_path + "/data/input_data/tut_chapter1/simple_fault_model_orientations.csv")

Out:

True

model.orientations

	X	Y	Z	G_x	G_y	G_z	smooth	surface
0	1000	1000	950.0	0.32	1.00e-12	0.95	0.01	Shale
1	400	1000	1400.0	0.32	1.00e-12	0.95	0.01	Sandstone_2
2	500	1000	864.6	-0.95	1.00e-12	0.32	0.01	Main_Fault

model.map_stack_to_surfaces({"Fault_Series": ('Main_Fault', 'Silstone'),
                             "Strat_Series": ('Sandstone_2', 'Sandstone_1', 'Siltstone',
                                              'Shale',)}, )

	surface	series	order_surfaces	color	id
4	Main_Fault	Fault_Series	1	#443988	1
0	Shale	Strat_Series	1	#015482	2
1	Sandstone_1	Strat_Series	2	#9f0052	3
2	Siltstone	Strat_Series	3	#ffbe00	4
3	Sandstone_2	Strat_Series	4	#728f02	5
5	basement	Basement	1	#ff3f20	6

model.stack

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

model.surfaces

	surface	series	order_surfaces	color	id
4	Main_Fault	Fault_Series	1	#443988	1
0	Shale	Strat_Series	1	#015482	2
1	Sandstone_1	Strat_Series	2	#9f0052	3
2	Siltstone	Strat_Series	3	#ffbe00	4
3	Sandstone_2	Strat_Series	4	#728f02	5
5	basement	Basement	1	#ff3f20	6

model.surface_points

	X	Y	Z	smooth	surface
52	700	1000	900	2.00e-06	Main_Fault
53	600	1000	600	2.00e-06	Main_Fault
54	500	1000	300	2.00e-06	Main_Fault
55	800	1000	1200	2.00e-06	Main_Fault
56	900	1000	1500	2.00e-06	Main_Fault
0	800	50	750	2.00e-06	Shale
1	800	150	700	2.00e-06	Shale
2	800	300	700	2.00e-06	Shale
3	800	500	800	2.00e-06	Shale
4	800	1000	1000	2.00e-06	Shale
5	800	1500	700	2.00e-06	Shale
6	800	1700	600	2.00e-06	Shale
7	800	1950	650	2.00e-06	Shale
8	0	1000	1100	2.00e-06	Shale
9	300	1000	1000	2.00e-06	Shale
10	450	1000	950	2.00e-06	Shale
11	1100	1000	900	2.00e-06	Shale
12	1400	1000	850	2.00e-06	Shale
13	1700	1000	900	2.00e-06	Shale
14	1500	500	800	2.00e-06	Shale
15	1500	1500	750	2.00e-06	Shale
16	800	50	450	2.00e-06	Sandstone_1
17	800	150	400	2.00e-06	Sandstone_1
18	800	300	400	2.00e-06	Sandstone_1
19	800	500	500	2.00e-06	Sandstone_1
20	800	1000	700	2.00e-06	Sandstone_1
21	800	1500	400	2.00e-06	Sandstone_1
22	800	1700	300	2.00e-06	Sandstone_1
23	800	1950	350	2.00e-06	Sandstone_1
24	0	1000	800	2.00e-06	Sandstone_1
25	300	1000	700	2.00e-06	Sandstone_1
26	1100	1000	600	2.00e-06	Sandstone_1
27	1400	1000	550	2.00e-06	Sandstone_1
28	1700	1000	600	2.00e-06	Sandstone_1
29	1500	500	500	2.00e-06	Sandstone_1
30	1500	1500	450	2.00e-06	Sandstone_1
31	900	150	920	2.00e-06	Siltstone
32	900	300	920	2.00e-06	Siltstone
33	900	1500	920	2.00e-06	Siltstone
34	900	1700	820	2.00e-06	Siltstone
35	900	1950	870	2.00e-06	Siltstone
36	0	1000	1300	2.00e-06	Siltstone
37	300	1000	1200	2.00e-06	Siltstone
38	600	1000	1100	2.00e-06	Siltstone
39	1100	1000	1100	2.00e-06	Siltstone
40	1400	1000	1050	2.00e-06	Siltstone
41	1700	1000	1100	2.00e-06	Siltstone
42	1500	500	1000	2.00e-06	Siltstone
43	1500	1500	950	2.00e-06	Siltstone
44	0	1000	1500	2.00e-06	Sandstone_2
45	300	1000	1400	2.00e-06	Sandstone_2
46	600	1000	1300	2.00e-06	Sandstone_2
47	1100	1000	1300	2.00e-06	Sandstone_2
48	1400	1000	1250	2.00e-06	Sandstone_2
49	1700	1000	1300	2.00e-06	Sandstone_2
50	1500	500	1200	2.00e-06	Sandstone_2
51	1500	1500	1150	2.00e-06	Sandstone_2

model._orientations.df.head()

	X	Y	Z	X_c	Y_c	Z_c	G_x	G_y	G_z	dip	azimuth	polarity	surface	series	id	order_series	smooth
2	500	1000	864.6	0.41	0.5	0.49	-0.95	1.00e-12	0.32	71.56	270.0	1.0	Main_Fault	Fault_Series	1	1	0.01
0	1000	1000	950.0	0.54	0.5	0.51	0.32	1.00e-12	0.95	18.43	90.0	1.0	Shale	Strat_Series	2	2	0.01
1	400	1000	1400.0	0.38	0.5	0.63	0.32	1.00e-12	0.95	18.43	90.0	1.0	Sandstone_2	Strat_Series	5	2	0.01

Next we need to categorize each surface into the right series. This will update all the Dataframes depending on Formations and Series to the right categories:

model.map_stack_to_surfaces({"Fault_Series": 'Main_Fault',
                             "Strat_Series": ('Sandstone_2', 'Siltstone',
                                              'Shale', 'Sandstone_1')})

	surface	series	order_surfaces	color	id
4	Main_Fault	Fault_Series	1	#443988	1
0	Shale	Strat_Series	1	#015482	2
1	Sandstone_1	Strat_Series	2	#9f0052	3
2	Siltstone	Strat_Series	3	#ffbe00	4
3	Sandstone_2	Strat_Series	4	#728f02	5
5	basement	Basement	1	#ff3f20	6

model._surfaces.df['series']

Out:

  Fault_Series
  Strat_Series
  Strat_Series
  Strat_Series
  Strat_Series
      Basement
Name: series, dtype: category
Categories (3, object): ['Fault_Series', 'Strat_Series', 'Basement']

model.surfaces

	surface	series	order_surfaces	color	id
4	Main_Fault	Fault_Series	1	#443988	1
0	Shale	Strat_Series	1	#015482	2
1	Sandstone_1	Strat_Series	2	#9f0052	3
2	Siltstone	Strat_Series	3	#ffbe00	4
3	Sandstone_2	Strat_Series	4	#728f02	5
5	basement	Basement	1	#ff3f20	6

gp.get_data(model, 'surface points')

	X	Y	Z	smooth	surface
52	700	1000	900	2.00e-06	Main_Fault
53	600	1000	600	2.00e-06	Main_Fault
54	500	1000	300	2.00e-06	Main_Fault
55	800	1000	1200	2.00e-06	Main_Fault
56	900	1000	1500	2.00e-06	Main_Fault
0	800	50	750	2.00e-06	Shale
1	800	150	700	2.00e-06	Shale
2	800	300	700	2.00e-06	Shale
3	800	500	800	2.00e-06	Shale
4	800	1000	1000	2.00e-06	Shale
5	800	1500	700	2.00e-06	Shale
6	800	1700	600	2.00e-06	Shale
7	800	1950	650	2.00e-06	Shale
8	0	1000	1100	2.00e-06	Shale
9	300	1000	1000	2.00e-06	Shale
10	450	1000	950	2.00e-06	Shale
11	1100	1000	900	2.00e-06	Shale
12	1400	1000	850	2.00e-06	Shale
13	1700	1000	900	2.00e-06	Shale
14	1500	500	800	2.00e-06	Shale
15	1500	1500	750	2.00e-06	Shale
16	800	50	450	2.00e-06	Sandstone_1
17	800	150	400	2.00e-06	Sandstone_1
18	800	300	400	2.00e-06	Sandstone_1
19	800	500	500	2.00e-06	Sandstone_1
20	800	1000	700	2.00e-06	Sandstone_1
21	800	1500	400	2.00e-06	Sandstone_1
22	800	1700	300	2.00e-06	Sandstone_1
23	800	1950	350	2.00e-06	Sandstone_1
24	0	1000	800	2.00e-06	Sandstone_1
25	300	1000	700	2.00e-06	Sandstone_1
26	1100	1000	600	2.00e-06	Sandstone_1
27	1400	1000	550	2.00e-06	Sandstone_1
28	1700	1000	600	2.00e-06	Sandstone_1
29	1500	500	500	2.00e-06	Sandstone_1
30	1500	1500	450	2.00e-06	Sandstone_1
31	900	150	920	2.00e-06	Siltstone
32	900	300	920	2.00e-06	Siltstone
33	900	1500	920	2.00e-06	Siltstone
34	900	1700	820	2.00e-06	Siltstone
35	900	1950	870	2.00e-06	Siltstone
36	0	1000	1300	2.00e-06	Siltstone
37	300	1000	1200	2.00e-06	Siltstone
38	600	1000	1100	2.00e-06	Siltstone
39	1100	1000	1100	2.00e-06	Siltstone
40	1400	1000	1050	2.00e-06	Siltstone
41	1700	1000	1100	2.00e-06	Siltstone
42	1500	500	1000	2.00e-06	Siltstone
43	1500	1500	950	2.00e-06	Siltstone
44	0	1000	1500	2.00e-06	Sandstone_2
45	300	1000	1400	2.00e-06	Sandstone_2
46	600	1000	1300	2.00e-06	Sandstone_2
47	1100	1000	1300	2.00e-06	Sandstone_2
48	1400	1000	1250	2.00e-06	Sandstone_2
49	1700	1000	1300	2.00e-06	Sandstone_2
50	1500	500	1200	2.00e-06	Sandstone_2
51	1500	1500	1150	2.00e-06	Sandstone_2

model.stack

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

In the case of having faults we need to assign wich series are faults:

model.faults

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

model.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

model.surface_points

	X	Y	Z	smooth	surface
52	700	1000	900	2.00e-06	Main_Fault
53	600	1000	600	2.00e-06	Main_Fault
54	500	1000	300	2.00e-06	Main_Fault
55	800	1000	1200	2.00e-06	Main_Fault
56	900	1000	1500	2.00e-06	Main_Fault
0	800	50	750	2.00e-06	Shale
1	800	150	700	2.00e-06	Shale
2	800	300	700	2.00e-06	Shale
3	800	500	800	2.00e-06	Shale
4	800	1000	1000	2.00e-06	Shale
5	800	1500	700	2.00e-06	Shale
6	800	1700	600	2.00e-06	Shale
7	800	1950	650	2.00e-06	Shale
8	0	1000	1100	2.00e-06	Shale
9	300	1000	1000	2.00e-06	Shale
10	450	1000	950	2.00e-06	Shale
11	1100	1000	900	2.00e-06	Shale
12	1400	1000	850	2.00e-06	Shale
13	1700	1000	900	2.00e-06	Shale
14	1500	500	800	2.00e-06	Shale
15	1500	1500	750	2.00e-06	Shale
16	800	50	450	2.00e-06	Sandstone_1
17	800	150	400	2.00e-06	Sandstone_1
18	800	300	400	2.00e-06	Sandstone_1
19	800	500	500	2.00e-06	Sandstone_1
20	800	1000	700	2.00e-06	Sandstone_1
21	800	1500	400	2.00e-06	Sandstone_1
22	800	1700	300	2.00e-06	Sandstone_1
23	800	1950	350	2.00e-06	Sandstone_1
24	0	1000	800	2.00e-06	Sandstone_1
25	300	1000	700	2.00e-06	Sandstone_1
26	1100	1000	600	2.00e-06	Sandstone_1
27	1400	1000	550	2.00e-06	Sandstone_1
28	1700	1000	600	2.00e-06	Sandstone_1
29	1500	500	500	2.00e-06	Sandstone_1
30	1500	1500	450	2.00e-06	Sandstone_1
31	900	150	920	2.00e-06	Siltstone
32	900	300	920	2.00e-06	Siltstone
33	900	1500	920	2.00e-06	Siltstone
34	900	1700	820	2.00e-06	Siltstone
35	900	1950	870	2.00e-06	Siltstone
36	0	1000	1300	2.00e-06	Siltstone
37	300	1000	1200	2.00e-06	Siltstone
38	600	1000	1100	2.00e-06	Siltstone
39	1100	1000	1100	2.00e-06	Siltstone
40	1400	1000	1050	2.00e-06	Siltstone
41	1700	1000	1100	2.00e-06	Siltstone
42	1500	500	1000	2.00e-06	Siltstone
43	1500	1500	950	2.00e-06	Siltstone
44	0	1000	1500	2.00e-06	Sandstone_2
45	300	1000	1400	2.00e-06	Sandstone_2
46	600	1000	1300	2.00e-06	Sandstone_2
47	1100	1000	1300	2.00e-06	Sandstone_2
48	1400	1000	1250	2.00e-06	Sandstone_2
49	1700	1000	1300	2.00e-06	Sandstone_2
50	1500	500	1200	2.00e-06	Sandstone_2
51	1500	1500	1150	2.00e-06	Sandstone_2

Again as we can see, as long we use the model methods, all the dependent objects change inplace accordingly. If for any reason you do not want this behaviour you can always use the individual methods of the objects (e.g. model.faults.set_is_fault)

model.additional_data

		values
Structure	isLith	True
	isFault	True
	number faults	1
	number surfaces	5
	number series	3
	number surfaces per series	[1, 4, 0]
	len surfaces surface_points	[5, 16, 15, 13, 8]
	len series surface_points	[5, 52, 0]
	len series orientations	[1, 2, 0]
Options	dtype	float64
	output	geology
	theano_optimizer	fast_compile
	device	cpu
	verbosity	None
Kriging	range	0.0
	$C_o$	0.0
	drift equations	[3, 3, 3]
Rescaling	rescaling factor	3800.0
Rescaling	centers	[850.0, 1000.0, 900.0]

Setting grid¶

So far we have worked on data that depends exclusively of input (i.e. sequential pile, surface_points, orientations, etc). With things like grid the idea is the same:

model.grid

Out:

Grid Object. Values:
array([], shape=(0, 3), dtype=float64)

model.set_regular_grid([0, 10, 0, 10, 0, 10], [50, 50, 50])

Out:

Active grids: ['regular']

Grid Object. Values:
array([[0.1, 0.1, 0.1],
       [0.1, 0.1, 0.3],
       [0.1, 0.1, 0.5],
       ...,
       [9.9, 9.9, 9.5],
       [9.9, 9.9, 9.7],
       [9.9, 9.9, 9.9]])

Getting data¶

Alternatively we can access the dataframe by:

gp.get_data(model, 'surfaces')

	surface	series	order_surfaces	color	id
4	Main_Fault	Fault_Series	1	#527682	1
0	Shale	Strat_Series	1	#015482	2
1	Sandstone_1	Strat_Series	2	#9f0052	3
2	Siltstone	Strat_Series	3	#ffbe00	4
3	Sandstone_2	Strat_Series	4	#728f02	5
5	basement	Basement	1	#ff3f20	6

The class gempy.core.model.Model works as the parent container of our project. Therefore the main step of any project is to create an instance of this class. In the official documentation we use normally geo_model (geo_data in the past) as name of this instance.

When we instantiate a Model object we full data structure is created. By using gp.init_data and set_series we set the default values – given the attributes – to all of fields. Data is stored in pandas dataframes. With gp.get_data and the name of the data object it is possible to have access to the dataframes:

str[‘all’, ‘surface_points’, ‘orientations’, ‘formations’, ‘series’, ‘faults’, ‘faults_relations’, additional data]

These dataframes are stored in specific objects. These objects contain the specific methods to manipulate them. You access these objects with the specific getter or as a attribute of Model

Total running time of the script: ( 0 minutes 1.232 seconds)

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1.2b: The Implicit coKriging class¶

Reading data¶

Setting grid¶

Getting data¶

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