def model():
geo_model = gp.create_model('test_map2Loop')
gp.init_data(
geo_model,
extent=[bbox[0], bbox[2], bbox[1], bbox[3], model_base, model_top],
resolution=[50, 50, 80],
path_o=orientations_file,
path_i=contacts_file)
# Load Topology
geo_model.set_topography(source='gdal', filepath=fp)
# Stack Processing
contents = np.genfromtxt(series_file, delimiter=',', dtype='U100')[1:,
4:-1]
map_series_to_surfaces = {}
for pair in contents:
map_series_to_surfaces.setdefault(pair[1], []).append(pair[0])
gp.map_stack_to_surfaces(geo_model,
map_series_to_surfaces,
remove_unused_series=False)
gp.plot_3d(geo_model,
ve=None,
show_topography=False,
image=True,
show_lith=False,
kwargs_plot_data={'arrow_size': 300})
return geo_model
def test_compute_model_multiple_ranges(self, interpolator):
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.create_data(
extent=[0, 2000, 0, 2000, -2000, 0],
resolution=[50, 50, 50],
path_o=input_path + "/GeoModeller/test_f/test_f_Foliations.csv",
path_i=input_path + "/GeoModeller/test_f/test_f_Points.csv")
gempy.map_stack_to_surfaces(
geo_data,
{
'fault1':
'MainFault',
'series': ('Reservoir', 'Seal', 'SecondaryReservoir',
'NonReservoirDeep'),
},
)
geo_data.set_theano_function(interpolator)
geo_data.set_is_fault('fault1')
geo_data.modify_kriging_parameters('range', [3000, 3500, 0])
geo_data._additional_data.kriging_data.set_default_c_o()
# Compute model
sol = gempy.compute_model(geo_data, sort_surfaces=True)
gempy.plot.plot_2d(geo_data,
cell_number=25,
direction='y',
show_data=True)
plt.show()
def create_model(resolution=[50, 50, 50]):
geo_data = gp.create_data(
'fault',
extent=[0, 1000, 0, 1000, 0, 1000],
resolution=resolution,
path_o=path_to_data + "model5_orientations.csv",
path_i=path_to_data + "model5_surface_points.csv")
geo_data.get_data()
gp.map_stack_to_surfaces(geo_data, {
"Fault_Series": 'fault',
"Strat_Series": ('rock2', 'rock1')
})
geo_data.set_is_fault(['Fault_Series'])
interp_data = gp.set_interpolator(geo_data,
theano_optimizer='fast_compile')
sol = gp.compute_model(geo_data)
geo = gp.plot_2d(geo_data,
direction='y',
show_data=True,
show_lith=True,
show_boundaries=False)
geo.axes[0].set_title("")
plt.tight_layout()
plt.close()
return geo.axes[0].figure
def test_issue_569(data_path):
surface_points_df = df = pd.read_csv(data_path + "/coordinates_mwe.csv")
orientations_df = pd.read_csv(data_path + "/orientations_mwe.csv")
geo_model = gp.create_model("Deltatest")
gp.init_data(geo_model, [
df.X.min() - 50,
df.X.max() + 50,
df.Y.min() - 50,
df.Y.max() + 50,
df.Z.min() - 50,
df.Z.max() + 50,
], [50, 50, 50],
surface_points_df=surface_points_df,
orientations_df=orientations_df,
default_values=True)
fault_list = []
series = {
"Strat_Series":
surface_points_df.loc[
~surface_points_df["formation"].str.contains("fault"),
"formation"].unique().tolist()
}
for fault in surface_points_df.loc[
surface_points_df["formation"].str.contains("fault"),
"formation"].unique():
series[fault] = fault
fault_list.append(fault)
gp.map_stack_to_surfaces(geo_model, series, remove_unused_series=True)
geo_model.set_is_fault(fault_list)
geo_model.reorder_features(['fault_a', 'fault_b', 'Strat_Series'])
geo_model.add_surfaces("basement")
plot = gp.plot_2d(geo_model,
show_lith=False,
show_boundaries=True,
direction=['z'])
plt.show(block=False)
gp.set_interpolator(
geo_model,
compile_theano=True,
theano_optimizer='fast_compile',
)
gp.get_data(geo_model, 'kriging')
sol = gp.compute_model(geo_model, sort_surfaces=True)
gp.plot_2d(geo_model, show_scalar=True, series_n=0)
gp.plot_2d(geo_model, series_n=0)
gp.plot_3d(geo_model, image=True)
def test_pile_geomodel_2(interpolator):
ve = 3
extent = [451e3, 456e3, 6.7820e6, 6.7840e6, -2309 * ve, -1651 * ve]
geo_model = gp.create_model('Topology-Gullfaks')
gp.init_data(geo_model,
extent, [30, 30, 30],
path_o=input_path + "/filtered_orientations.csv",
path_i=input_path + "/filtered_surface_points.csv",
default_values=True)
series_distribution = {
"fault3": "fault3",
"fault4": "fault4",
"unconformity": "BCU",
"sediments": ("tarbert", "ness", "etive"),
}
gp.map_stack_to_surfaces(geo_model,
series_distribution,
remove_unused_series=True)
geo_model.reorder_features(
["unconformity", "fault3", "fault4", "sediments", "Basement"])
geo_model.set_is_fault(["fault3"])
geo_model.set_is_fault(["fault4"])
rel_matrix = np.array([[0, 0, 0, 0, 0], [0, 0, 0, 1, 1], [0, 0, 0, 1, 1],
[0, 0, 0, 0, 0], [0, 0, 0, 0, 0]])
geo_model.set_fault_relation(rel_matrix)
surf_groups = pd.read_csv(input_path +
"/filtered_surface_points.csv").group
geo_model._surface_points.df["group"] = surf_groups
orient_groups = pd.read_csv(input_path +
"/filtered_orientations.csv").group
geo_model._orientations.df["group"] = orient_groups
geo_model._surface_points.df.reset_index(inplace=True, drop=True)
geo_model._orientations.df.reset_index(inplace=True, drop=True)
geo_model.set_theano_function(interpolator)
gp.compute_model(geo_model)
gp.plot.plot_2d(geo_model, cell_number=25, direction='y', show_data=True)
from gempy.plot.plot_api import plot_2d
p = plot_2d(geo_model, cell_number=[25])
plt.savefig(os.path.dirname(__file__) + '/../figs/test_pile_lith_block')
return geo_model
def map_sequential_pile(load_model):
geo_model = load_model
# TODO decide what I do with the layer order
gp.map_stack_to_surfaces(geo_model, {"Fault_Series": 'Main_Fault',
"Strat_Series": ('Sandstone_2', 'Siltstone',
'Shale', 'Sandstone_1', 'basement')},
remove_unused_series=True)
geo_model.set_is_fault(['Fault_Series'])
return geo_model
def one_fault_model_no_interp():
"""This only makes sense for running small test fast"""
model = gp.create_data('one_fault_model', [0, 2000, 0, 2000, 0, 2000], [50, 50, 50],
path_o=input_path2 + 'tut_chapter1/simple_fault_model_orientations.csv',
path_i=input_path2 + 'tut_chapter1/simple_fault_model_points.csv')
# Assigning series to surface as well as their order (timewise)
gp.map_stack_to_surfaces(model, {"Fault_Series": 'Main_Fault',
"Strat_Series": ('Sandstone_2', 'Siltstone',
'Shale', 'Sandstone_1')},
)
model.set_is_fault(['Fault_Series'])
return model
def model_complex(interpolator):
model = gempy.create_data(extent=[0, 2500, 0, 1000, 0, 1000], resolution = [50, 20, 20],
path_o=input_path2 + "jan_models/fixture_model_orientations.csv",
path_i=input_path2 + "jan_models/fixture_model_surfaces.csv")
# Assigning series to surface as well as their order (timewise)
gp.map_stack_to_surfaces(model, {"Fault_Series": ('fault'), "Strat_Series1": ('rock3'),
"Strat_Series2": ('rock2', 'rock1'),
"Basement_Series": ('basement')})
model.set_is_fault(['Fault_Series'])
model.set_theano_function(interpolator)
return model
def unconformity_model(interpolator):
geo_model = gp.create_data(
'unconformity_model', [0, 1000, 0, 1000, 0, 1000],
resolution=[50, 42, 33],
path_o=input_path2 + "jan_models/model6_orientations.csv",
path_i=input_path2 + "jan_models/model6_surface_points.csv")
gp.map_stack_to_surfaces(
geo_model, {
"Strat_Series1": ('rock3'),
"Strat_Series2": ('rock2', 'rock1'),
"Basement_Series": ('basement')
})
# with open("input_data/geomodel_jan_sol.p", "rb") as f:
# geo_model.solutions = load(f)
geo_model.set_theano_function(interpolator)
gp.compute_model(geo_model)
return geo_model
def test_add_point():
extend = [0.0, 1.0, 0.0, 1.0, 0.0, 1.1]
discretization = [5, 20, 20]
x, y, z, f = 0.0, 0.0, 0.5, 'surface2'
# %%
geo_model = gp.create_model('test')
gp.init_data(geo_model, extend, discretization)
geo_model.set_default_surfaces()
geo_model.set_default_orientation()
strats = ['surface1', 'surface2', 'basement']
gp.map_stack_to_surfaces(geo_model, {'Strat_Series': strats})
geo_model.add_surface_points(x, y, z, f)
geo_model.add_orientations(x, y, z, f, pole_vector=(1,0,0))
def test_issue_564(data_path):
geo_model = gp.create_model('SBPM')
gp.init_data(geo_model, [550, 730, -200, 1000, 20, 55], [50, 50, 50],
path_i=data_path + "/564_Points.csv",
path_o=data_path + "/564_Orientations_.csv",
default_values=True)
gp.map_stack_to_surfaces(geo_model, {
"Q": 'Quartaer',
"vK": 'verwKeuper',
"Sa": 'Sandstein',
"Sc": 'Schluffstein',
"b": 'basement'
},
remove_unused_series=True)
gp.set_interpolator(geo_model,
compile_theano=True,
theano_optimizer='fast_compile')
sol = gp.compute_model(geo_model)
gp.plot_2d(geo_model)
gpv = gp.plot_3d(geo_model,
image=True,
plotter_type='basic',
ve=5,
show_lith=False)
geo_model.set_bottom_relation(
["Q", "vK", "Sa", "Sc", "b"],
["Onlap", "Onlap", "Onlap", "Onlap", "Onlap"])
sol = gp.compute_model(geo_model)
gp.plot_2d(geo_model)
gpv = gp.plot_3d(geo_model,
image=True,
plotter_type='basic',
ve=5,
show_lith=True)
def test_d(self, interpolator):
"""
Two layers 1 fault
"""
# Importing the data from csv files and settign extent and resolution
geo_data = gempy.create_data(
extent=[0, 10, 0, 10, -10, 0],
resolution=[50, 50, 50],
path_o=input_path + "/GeoModeller/test_d/test_d_Foliations.csv",
path_i=input_path + "/GeoModeller/test_d/test_d_Points.csv")
gempy.map_stack_to_surfaces(geo_data, {
'fault1': 'f1',
'series': ('A', 'B')
})
geo_data.set_is_fault('fault1')
geo_data.set_theano_function(interpolator)
# Compute model
sol = gempy.compute_model(geo_data)
gempy.plot.plot_2d(geo_data,
cell_number=25,
direction='y',
show_data=True)
plt.savefig(os.path.dirname(__file__) + '/../figs/test_d.png', dpi=200)
if update_sol:
np.save(input_path + '/test_d_sol.npy',
sol.lith_block[test_values])
# Load model
real_sol = np.load(input_path + '/test_d_sol.npy')
# We only compare the block because the absolute pot field I changed it
np.testing.assert_array_almost_equal(np.round(
sol.lith_block[test_values]),
real_sol,
decimal=0)
def geo_model(interpolator):
geo_model = gp.create_model('Test_uncomformities')
# Importing the data from CSV-files and setting extent and resolution
gp.init_data(
geo_model, [0, 10., 0, 2., 0, 5.], [100, 3, 100],
path_o=input_path + '/05_toy_fold_unconformity_orientations.csv',
path_i=input_path + '/05_toy_fold_unconformity_interfaces.csv',
default_values=True)
gp.map_stack_to_surfaces(
geo_model, {
"Flat_Series": 'Flat',
"Inclined_Series": 'Inclined',
"Fold_Series": ('Basefold', 'Topfold', 'basement')
})
# Create the theano model
geo_model.set_theano_function(interpolator)
return geo_model
def create_gempy_model(resolution=[20, 20, 20], type=2):
if type == 1:
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(
'fold',
extent=[0, 1000, 0, 1000, 0, 1000],
resolution=resolution,
path_o=path_to_data + "model2_orientations.csv",
path_i=path_to_data + "model2_surface_points.csv")
gp.map_stack_to_surfaces(geo_data, {
"Strat_Series": ('rock2', 'rock1'),
"Basement_Series": ('basement')
})
interp_data = gp.set_interpolator(geo_data,
theano_optimizer='fast_compile')
sol = gp.compute_model(geo_data)
elif type == 2:
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(
'unconformity',
extent=[0, 1000, 0, 1000, 0, 1000],
resolution=[50, 50, 50],
path_o=path_to_data + "model6_orientations.csv",
path_i=path_to_data + "model6_surface_points.csv")
gp.map_stack_to_surfaces(
geo_data, {
"Strat_Series1": ('rock3'),
"Strat_Series2": ('rock2', 'rock1'),
"Basement_Series": ('basement')
})
interp_data = gp.set_interpolator(geo_data,
theano_optimizer='fast_compile')
sol = gp.compute_model(geo_data)
return geo_data
def test_set_orientations():
# Importing the data from CSV-files and setting extent and resolution
geo_data = gp.create_data(
extent=[0, 2000, 0, 2000, 0, 2000],
resolution=[50, 50, 50],
path_o=input_path +
'/input_data/tut_chapter1/simple_fault_model_orientations.csv',
path_i=input_path +
'/input_data/tut_chapter1/simple_fault_model_points.csv')
gp.get_data(geo_data)
# Assigning series to formations as well as their order (timewise)
gp.map_stack_to_surfaces(geo_data, {
"Fault_Series": 'Main_Fault',
"Strat_Series": ('Sandstone_2', 'Siltstone')
})
geo_data._orientations.create_orientation_from_surface_points(
geo_data.surface_points, [0, 1, 2])
gp.set_orientation_from_surface_points(geo_data, [0, 1, 2])
def test_select_nearest_surface_points():
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")
# Assigning series to formations as well as their order (timewise)
gp.map_stack_to_surfaces(geo_data, {
"Fault_Series": 'fault',
"Strat_Series": ('rock2', 'rock1')
})
geo_data.set_is_fault(['Fault_Series'])
# detect fault names
f_id = geo_data._faults.df.index.categories[
geo_data._faults.df.isFault.values]
# find fault points
fault_poi = geo_data._surface_points.df[
geo_data._surface_points.df.series.isin(f_id)]
# find neighbours
knn = gp.select_nearest_surfaces_points(geo_data, fault_poi, 1)
radius = gp.select_nearest_surfaces_points(geo_data, fault_poi, 200.)
# sort neighbours, necessary for equal testing
knn = [k.sort_values() for k in knn]
radius = [r.sort_values() for r in radius]
# define reference
reference = [[16, 17], [16, 17], [18, 19], [18, 19], [20, 21], [20, 21]]
assert np.array_equal(reference, knn) and np.array_equal(reference, radius)
def test_set_orientation_from_neighbours():
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")
# Assigning series to formations as well as their order (timewise)
gp.map_stack_to_surfaces(geo_data, {
"Fault_Series": 'fault',
"Strat_Series": ('rock2', 'rock1')
})
geo_data.set_is_fault(['Fault_Series'])
# detect fault names
f_id = geo_data._faults.df.index.categories[
geo_data._faults.df.isFault.values]
# find fault points
fault_poi = geo_data._surface_points.df[
geo_data._surface_points.df.series.isin(f_id)]
# find neighbours
neighbours = gp.select_nearest_surfaces_points(geo_data, fault_poi, 5)
# calculate one fault orientation
gp.set_orientation_from_neighbours(geo_data, neighbours[1])
# find the calculated orientation
test = geo_data._orientations.df.sort_index().iloc[-1][['dip',
'azimuth']].values
# calculate reference
reference = [90 - np.arctan(0.5) / np.pi * 180, 90]
assert np.array_equal(reference, test)
# %%
data_path = 'https://raw.githubusercontent.com/cgre-aachen/gempy_data/master/'
geo_model = gp.create_data(
'viz_3d', [0, 2000, 0, 2000, 0, 1600], [50, 50, 50],
path_o=data_path + "data/input_data/lisa_models/foliations" + str(7) +
".csv",
path_i=data_path + "data/input_data/lisa_models/interfaces" + str(7) +
".csv")
gp.map_stack_to_surfaces(
geo_model, {
"Fault_1":
'Fault_1',
"Fault_2":
'Fault_2',
"Strat_Series":
('Sandstone', 'Siltstone', 'Shale', 'Sandstone_2', 'Schist', 'Gneiss')
})
geo_model.set_is_fault(['Fault_1', 'Fault_2'])
geo_model.set_topography()
gp.set_interpolator(geo_model)
gp.compute_model(geo_model, compute_mesh=True)
# %%
# Basic plotting API
# ------------------
#
#
# %%
geo_model.surfaces
# %%
geo_model.orientations.df.dtypes
# %%
# We will need to separate with surface belong to each series:
#
# %%
gp.map_stack_to_surfaces(geo_model, {
'Fault1': 'f1',
'Fault2': 'f2',
'Fault3': 'f3'
})
# %%
# However if we want the faults to offset the “Default series”, they will
# need to be more recent (higher on the pile). We can modify the order by:
#
# %%
geo_model.modify_order_series(4, 'Default series')
# %%
# Lastly, so far we did not specify which series/faults are actula faults:
#
def test_map2loop_model_no_faults():
# Location box
bbox = (500000, 7490000, 545000, 7520000)
model_base = -3200 # Original 3200
model_top = 800
# Input files
geo_model = gp.create_model('test_map2Loop')
gp.init_data(
geo_model,
extent=[bbox[0], bbox[2], bbox[1], bbox[3], model_base, model_top],
resolution=[50, 50, 80],
path_o=orientations_file,
path_i=contacts_file
)
gp.set_interpolator(geo_model)
# Load Topology
geo_model.set_topography(source='gdal', filepath=fp)
# Stack Processing
contents = np.genfromtxt(series_file,
delimiter=',', dtype='U100')[1:, 4:-1]
map_series_to_surfaces = {}
for pair in contents:
map_series_to_surfaces.setdefault(pair[1], []).append(pair[0])
gp.map_stack_to_surfaces(geo_model, map_series_to_surfaces,
remove_unused_series=False)
gp.plot_2d(geo_model, ve=10, show_topography=False)
plt.show()
# Plot in 3D
gp.plot_3d(geo_model, ve=10, show_topography=False, image=True)
# Stack Processing
contents = np.genfromtxt(series_file,
delimiter=',', dtype='U100')[1:, 4:-1]
map_series_to_surfaces = {}
for pair in contents:
map_series_to_surfaces.setdefault(pair[1], []).append(pair[0])
gp.map_stack_to_surfaces(geo_model, map_series_to_surfaces,
remove_unused_series=False)
# Adding axial rescale
#geo_model._rescaling.toggle_axial_anisotropy()
# Increasing nugget effect
geo_model.modify_surface_points(
geo_model.surface_points.df.index,
smooth=0.001
)
geo_model.modify_kriging_parameters('drift equations', [9, 9, 9, 9, 9])
gp.compute_model(geo_model)
gp.plot_2d(geo_model,
section_names=['topography'],
show_topography=True,
)
plt.show()
gp.plot_3d(geo_model, ve=10, show_topography=True,
image=True,
show_lith=False,
)
def test_complex_model():
geo_model = gp.create_model('Geological_Model1')
geo_model = gp.init_data(geo_model,
extent=[0, 4000, 0, 2775, 200, 1500],
resolution=[100, 10, 100])
gp.set_interpolator(geo_model, theano_optimizer='fast_run', verbose=[])
geo_model.add_features(['Fault2', 'Cycle2', 'Fault1', 'Cycle1'])
geo_model.delete_features('Default series')
geo_model.add_surfaces(['F2', 'H', 'G', 'F1', 'D', 'C', 'B', 'A'])
gp.map_stack_to_surfaces(geo_model, {
'Fault1': 'F1',
'Fault2': 'F2',
'Cycle2': ['G', 'H']
})
geo_model.set_is_fault(['Fault1', 'Fault2'])
###Cycle 1
# surface B - before F1
geo_model.add_surface_points(X=584, Y=285, Z=500, surface='B')
geo_model.add_surface_points(X=494, Y=696, Z=500, surface='B')
geo_model.add_surface_points(X=197, Y=1898, Z=500, surface='B')
geo_model.add_surface_points(X=473, Y=2180, Z=400, surface='B')
geo_model.add_surface_points(X=435, Y=2453, Z=400, surface='B')
# surface C - before F1
geo_model.add_surface_points(X=946, Y=188, Z=600, surface='C')
geo_model.add_surface_points(X=853, Y=661, Z=600, surface='C')
geo_model.add_surface_points(X=570, Y=1845, Z=600, surface='C')
geo_model.add_surface_points(X=832, Y=2132, Z=500, surface='C')
geo_model.add_surface_points(X=767, Y=2495, Z=500, surface='C')
# Surface D - Before F1
geo_model.add_surface_points(X=967, Y=1638, Z=800, surface='D')
geo_model.add_surface_points(X=1095, Y=996, Z=800, surface='D')
# Adding orientation to Cycle 1
geo_model.add_orientations(X=832,
Y=2132,
Z=500,
surface='C',
orientation=[76, 17.88, 1])
# surface B - After F1
geo_model.add_surface_points(X=1447, Y=2554, Z=500, surface='B')
geo_model.add_surface_points(X=1511, Y=2200, Z=500, surface='B')
geo_model.add_surface_points(X=1549, Y=629, Z=600, surface='B')
geo_model.add_surface_points(X=1630, Y=287, Z=600, surface='B')
# surface C - After F1
geo_model.add_surface_points(X=1891, Y=2063, Z=600, surface='C')
geo_model.add_surface_points(X=1605, Y=1846, Z=700, surface='C')
geo_model.add_surface_points(X=1306, Y=1641, Z=800, surface='C')
geo_model.add_surface_points(X=1476, Y=979, Z=800, surface='C')
geo_model.add_surface_points(X=1839, Y=962, Z=700, surface='C')
geo_model.add_surface_points(X=2185, Y=893, Z=600, surface='C')
geo_model.add_surface_points(X=2245, Y=547, Z=600, surface='C')
# Surface D - After F1
geo_model.add_surface_points(X=2809, Y=2567, Z=600, surface='D')
geo_model.add_surface_points(X=2843, Y=2448, Z=600, surface='D')
geo_model.add_surface_points(X=2873, Y=876, Z=700, surface='D')
# Surface D - After F2
geo_model.add_surface_points(X=3056, Y=2439, Z=650, surface='D')
geo_model.add_surface_points(X=3151, Y=1292, Z=700, surface='D')
### Fault 1
# Surface F1
geo_model.add_surface_points(X=1203, Y=138, Z=600, surface='F1')
geo_model.add_surface_points(X=1250, Y=1653, Z=800, surface='F1')
# orientation to Fault 1
geo_model.add_orientations(X=1280,
Y=2525,
Z=500,
surface='F1',
orientation=[272, 90, 1])
### Cycle 2
# Surface G - Before F2
geo_model.add_surface_points(X=1012, Y=1493, Z=900, surface='G')
geo_model.add_surface_points(X=1002, Y=1224, Z=900, surface='G')
geo_model.add_surface_points(X=1579, Y=1376, Z=850, surface='G')
geo_model.add_surface_points(X=2489, Y=336, Z=750, surface='G')
geo_model.add_surface_points(X=2814, Y=1848, Z=750, surface='G')
# Surface H - Before F2
geo_model.add_surface_points(X=2567, Y=129, Z=850, surface='H')
geo_model.add_surface_points(X=3012, Y=726, Z=800, surface='H')
# Orientation to cycle 2
geo_model.add_orientations(X=1996,
Y=47,
Z=800,
surface='G',
orientation=[92, 5.54, 1])
# Surface G - After F2
geo_model.add_surface_points(X=3031, Y=2725, Z=800, surface='G')
geo_model.add_surface_points(X=3281, Y=2314, Z=750, surface='G')
geo_model.add_surface_points(X=3311, Y=1357, Z=750, surface='G')
geo_model.add_surface_points(X=3336, Y=898, Z=750, surface='G')
# Surface H - After F2
geo_model.add_surface_points(X=3218, Y=1818, Z=890, surface='H')
geo_model.add_surface_points(X=3934, Y=1207, Z=810, surface='H')
geo_model.add_surface_points(X=3336, Y=704, Z=850, surface='H')
### Fault 2
geo_model.add_surface_points(X=3232, Y=178, Z=1000, surface='F2')
geo_model.add_surface_points(X=2912, Y=2653, Z=700, surface='F2')
# Add orientation to Fault 2
geo_model.add_orientations(X=3132,
Y=951,
Z=700,
surface='F2',
orientation=[85, 90, 1])
gp.compute_model(geo_model, sort_surfaces=False)
module = GemPyModule(geo_model=geo_model,
extent=extent,
box=[1000, 800],
load_examples=False)
module.show_boundary = True
module.show_lith = True
module.show_hillshades = True
module.show_contour = True
module.show_fill_contour = False
sb_params = module.update(pytest.sb_params)
sb_params['fig'].show()
geo_model = gp.create_model('Tutorial_ch1-1_Basics')
# Importing the data from CSV-files and setting extent and resolution
data_path = 'https://raw.githubusercontent.com/cgre-aachen/gempy_data/master/'
gp.init_data(
geo_model, [0, 2000., 0, 2000., 0, 2000.], [5, 5, 5],
path_o=data_path +
"/data/input_data/tut_chapter1/simple_fault_model_orientations.csv",
path_i=data_path +
"/data/input_data/tut_chapter1/simple_fault_model_points.csv",
default_values=True)
gp.map_stack_to_surfaces(geo_model, {
"Fault_Series":
'Main_Fault',
"Strat_Series":
('Sandstone_2', 'Siltstone', 'Shale', 'Sandstone_1', 'basement')
},
remove_unused_series=True)
geo_model.set_is_fault(['Fault_Series'])
# %%
# Add sections
# ~~~~~~~~~~~~
#
# %%
# pass section dictionary with startpoint, endpoint and resolution for
# every section:
#
geo_model.delete_surfaces(del_surfaces, remove_data=True)
# %%
# %debug
# %%
geo_model.stack
# %%
gp.map_stack_to_surfaces(
geo_model, {
"fault_Abrolhos_Transfer": ["Abrolhos_Transfer"],
"fault_Coomallo": ["Coomallo"],
"fault_Eneabba_South": ["Eneabba_South"],
"fault_Hypo_fault_W": ["Hypo_fault_W"],
"fault_Hypo_fault_E": ["Hypo_fault_E"],
"fault_Urella_North": ["Urella_North"],
"fault_Urella_South": ["Urella_South"],
"fault_Darling": ["Darling"],
"Sedimentary_Series":
['Cretaceous', 'Yarragadee', 'Eneabba', 'Lesueur', 'Permian']
})
# %%
geo_model.series
# %%
order_series = [
"fault_Abrolhos_Transfer", "fault_Coomallo", "fault_Eneabba_South",
"fault_Hypo_fault_W", "fault_Hypo_fault_E", "fault_Urella_North",
"fault_Darling", "fault_Urella_South", "Sedimentary_Series", 'Basement'
resolution=[125, 50, 50],
path_o=path_to_data + "model7_orientations.csv",
path_i=path_to_data + "model7_surface_points.csv")
# %%
geo_data.get_data()
# %%
# Setting and ordering the units and series:
#
# %%
gp.map_stack_to_surfaces(
geo_data, {
"Fault_Series": ('fault'),
"Strat_Series1": ('rock3'),
"Strat_Series2": ('rock2', 'rock1'),
"Basement_Series": ('basement')
})
geo_data.set_is_fault(['Fault_Series'])
# %%
gp.plot_2d(geo_data, direction='y')
# %%
# Calculating the model:
#
# %%
interp_data = gp.set_interpolator(geo_data, theano_optimizer='fast_compile')
extent=extent,
resolution=resolution,
path_i=path_interf,
path_o=path_orient)
# %%
sdict = {'section1': ([732000, 1916000], [745000, 1916000], [200, 150])}
geo_model.set_section_grid(sdict)
# %%
# sorting of lithologies
gp.map_stack_to_surfaces(geo_model, {
'fault_left': ('fault_left'),
'fault_right': ('fault_right'),
'fault_lr': ('fault_lr'),
'Trias_Series': ('TRIAS', 'LIAS'),
'Carbon_Series': ('CARBO'),
'Basement_Series': ('basement')
},
remove_unused_series=True)
# %%
colordict = {
'LIAS': '#015482',
'TRIAS': '#9f0052',
'CARBO': '#ffbe00',
'basement': '#728f02',
'fault_left': '#2a2a2a',
'fault_right': '#545454',
'fault_lr': '#a5a391'
}
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")
# %%
geo_data.get_data()
# %%
# Setting and ordering the units and series:
#
# %%
gp.map_stack_to_surfaces(geo_data,
{"Strat_Series": ('rock2', 'rock1'),
"Basement_Series": ('basement')})
# %%
gp.plot_2d(geo_data, direction=['y'])
# %%
# Calculating the model:
#
# %%
interp_data = gp.set_interpolator(geo_data, theano_optimizer='fast_compile')
# %%
sol = gp.compute_model(geo_data)
def create_example_model(name,
extent=[0, 1000, 0, 1000, 0, 1800],
do_sections=False,
change_color=False,
data_path=path_to_data,
resolution=[20, 20, 20],
theano_optimizer='fast_compile'):
# _test_data['gempy_data'], theano_optimizer='fast_compile'):
"""
Create all the example models
Args:
name: Name of the model to create
extent: extent of the model in model units
do_sections: False
change_color: False
data_path: Path to the .csv files storing the information
theano_optimizer: 'fast_compile'
Returns:
geo_model
"""
assert name in all_models, 'possible model names are ' + str(all_models)
if name == 'Horizontal_layers':
geo_model = gp.create_data(
name,
extent=extent,
resolution=resolution,
path_o=data_path + "model1_orientations.csv",
path_i=data_path + "model1_surface_points.csv")
gp.map_stack_to_surfaces(geo_model, {
"Strat_Series": ('rock2', 'rock1'),
"Basement_Series": ('basement')
})
if change_color:
geo_model.surfaces.colors.change_colors({
"rock2": '#9f0052',
'rock1': '#e36746',
'basement': '#f9f871'
})
elif name == 'Anticline':
geo_model = gp.create_data(
name,
extent=extent,
resolution=resolution,
path_o=data_path + "model2_orientations.csv",
path_i=data_path + "model2_surface_points.csv")
gp.map_stack_to_surfaces(geo_model, {
"Strat_Series": ('rock2', 'rock1'),
"Basement_Series": ('basement')
})
elif name == 'Recumbent_fold':
geo_model = gp.create_data(
name,
extent=extent,
resolution=resolution,
path_o=data_path + "model3_orientations.csv",
path_i=data_path + "model3_surface_points.csv")
gp.map_stack_to_surfaces(geo_model, {
"Strat_Series": ('rock2', 'rock1'),
"Basement_Series": ('basement')
})
if change_color:
geo_model.surfaces.colors.change_colors({
"rock2": '#e36746',
'rock1': '#c0539f',
'basement': '#006fa8'
})
elif name == 'Pinchout':
geo_model = gp.create_data(
name,
extent=extent,
resolution=resolution,
path_o=data_path + "model4_orientations.csv",
path_i=data_path + "model4_surface_points.csv")
gp.map_stack_to_surfaces(geo_model, {
"Strat_Series": ('rock2', 'rock1'),
"Basement_Series": ('basement')
})
if change_color:
geo_model.surfaces.colors.change_colors({
"rock2": '#a1b455',
'rock1': '#ffbe00',
'basement': '#006471'
})
elif name == 'Fault':
geo_model = gp.create_data(
name,
extent=extent,
resolution=resolution,
path_o=data_path + "model5_orientations.csv",
path_i=data_path + "model5_surface_points.csv")
gp.map_stack_to_surfaces(geo_model, {
"Fault_Series": 'fault',
"Strat_Series": ('rock2', 'rock1')
})
geo_model.set_is_fault(['Fault_Series'], change_color=False)
if change_color:
geo_model.surfaces.colors.change_colors({
"rock2": '#00c2d0',
'rock1': '#a43d00',
'basement': '#76a237',
'fault': '#000000'
})
elif name == 'Unconformity':
geo_model = gp.create_data(
name,
extent=extent,
resolution=resolution,
path_o=data_path + "model6_orientations.csv",
path_i=data_path + "model6_surface_points.csv")
gp.map_stack_to_surfaces(
geo_model, {
"Strat_Series1": ('rock3'),
"Strat_Series2": ('rock2', 'rock1'),
"Basement_Series": ('basement')
})
else:
raise NotImplementedError(name, "Not available in example models")
if do_sections:
geo_model.set_section_grid(
{'section' + ' ' + name: ([0, 500], [1000, 500], [30, 30])})
interp_data = gp.set_interpolator(
geo_model, # compile_theano=True,
theano_optimizer=theano_optimizer)
sol = gp.compute_model(geo_model, compute_mesh=False)
if do_sections:
gp.plot_2d(geo_model,
section_names=['section' + ' ' + name],
show_data=False)
return geo_model
def extract_borehole(geo_model: gp.core.model.Project,
geo_data: gemgis.GemPyData, loc: List[Union[int, float]],
**kwargs):
"""
Extracting a borehole at a provided location from a recalculated GemPy Model
Args:
geo_model: gp.core.model.Project - previously calculated GemPy Model
geo_data: gemgis.GemPyData - GemGIS GemPy Data class used to calculate the previous model
loc: list of x and y point pair representing the well location
Kwargs:
zmax: int/float indicating the maximum depth of the well, default is minz of the previous model
res: int indicating the resolution of the model in z-direction
Returns:
"""
# Checking if geo_model is a GemPy geo_model
if not isinstance(geo_model, gp.core.model.Project):
raise TypeError('geo_model must be a GemPy geo_model')
# Checking if geo_data is a GemGIS GemPy Data Class
if not isinstance(geo_data, gemgis.GemPyData):
raise TypeError('geo_data must be a GemPy Data object')
# Checking if loc is of type list
if not isinstance(loc, list):
raise TypeError(
'Borehole location must be provided as a list of a x- and y- coordinate'
)
# Checking if elements of loc are of type int or float
if not all(isinstance(n, (int, float)) for n in loc):
raise TypeError(
'Location values must be provided as integers or floats')
# Selecting DataFrame columns and create deep copy of DataFrame
orientations_df = geo_model.orientations.df[[
'X', 'Y', 'Z', 'surface', 'dip', 'azimuth', 'polarity'
]].copy(deep=True)
interfaces_df = geo_model.surface_points.df[['X', 'Y', 'Z',
'surface']].copy(deep=True)
# Creating formation column
orientations_df['formation'] = orientations_df['surface']
interfaces_df['formation'] = interfaces_df['surface']
# Deleting surface column
del orientations_df['surface']
del interfaces_df['surface']
# Getting maximum depth and resolution
zmax = kwargs.get('zmax', geo_model.grid.regular_grid.extent[5])
res = kwargs.get('res', geo_model.grid.regular_grid.resolution[2])
# Checking if zmax is of type int or float
if not isinstance(zmax, (int, float)):
raise TypeError('Maximum depth must be of type int or float')
# Checking if res is of type int
if not isinstance(res, (int, float, np.int32)):
raise TypeError('Resolution must be of type int')
# Creating variable for maximum depth
z = geo_model.grid.regular_grid.extent[5] - zmax
# Prevent printing
# sys.stdout = open(os.devnull, 'w')
# Create GemPy Model
well_model = gp.create_model('Well_Model')
# Initiate Data for GemPy Model
gp.init_data(well_model,
extent=[
loc[0] - 5, loc[0] + 5, loc[1] - 5, loc[1] + 5,
geo_model.grid.regular_grid.extent[4],
geo_model.grid.regular_grid.extent[5] - z
],
resolution=[5, 5, res],
orientations_df=orientations_df.dropna(),
surface_points_df=interfaces_df.dropna(),
default_values=False)
# Map Stack to surfaces
gp.map_stack_to_surfaces(well_model,
geo_data.stack,
remove_unused_series=True)
# Add Basement surface
well_model.add_surfaces('basement')
# Change colors of surfaces
well_model.surfaces.colors.change_colors(geo_data.surface_colors)
# Set Interpolator
gp.set_interpolator(well_model,
compile_theano=True,
theano_optimizer='fast_run',
dtype='float64',
update_kriging=False,
verbose=[])
# Set faults active
for i in geo_model.surfaces.df[geo_model.surfaces.df['isFault'] ==
True]['surface'].values.tolist():
well_model.set_is_fault([i])
# Compute Model
sol = gp.compute_model(well_model, compute_mesh=False)
# Reshape lith_block
well = sol.lith_block.reshape(well_model.grid.regular_grid.resolution[0],
well_model.grid.regular_grid.resolution[1],
well_model.grid.regular_grid.resolution[2])
# Select colors for plotting
color_dict = well_model.surfaces.colors.colordict
surface = well_model.surfaces.df.copy(deep=True)
surfaces = surface[~surface['id'].isin(np.unique(np.round(sol.lith_block))
)]
for key in surfaces['surface'].values.tolist():
color_dict.pop(key)
cols = list(color_dict.values())
# Calculate boundaries
boundaries = np.where(
np.round(well.T[:, 1])[:-1] != np.round(well.T[:, 1])[1:]
)[0][::well_model.grid.regular_grid.resolution[0]]
# Create Plot
plt.figure(figsize=(3, 10))
plt.imshow(
np.rot90(np.round(well.T[:, 1]), 2),
cmap=ListedColormap(cols),
extent=(0, (well_model.grid.regular_grid.extent[5] -
well_model.grid.regular_grid.extent[4]) / 8,
well_model.grid.regular_grid.extent[4],
well_model.grid.regular_grid.extent[5]),
)
list_values = np.unique(np.round(well.T[:, 1])[:, 0]).tolist()
# Display depths of layer boundaries
for i in boundaries:
plt.text((well_model.grid.regular_grid.extent[5] -
well_model.grid.regular_grid.extent[4]) / 7,
i * geo_model.grid.regular_grid.dz +
geo_model.grid.regular_grid.extent[4] +
geo_model.grid.regular_grid.dz,
'%d m' % (i * geo_model.grid.regular_grid.dz +
geo_model.grid.regular_grid.extent[4]),
fontsize=14)
del list_values[list_values.index(np.round(well.T[:, 1])[:, 0][i + 1])]
# Plot last depth
plt.text(
(well_model.grid.regular_grid.extent[5] -
well_model.grid.regular_grid.extent[4]) / 7,
geo_model.grid.regular_grid.extent[4] + geo_model.grid.regular_grid.dz,
'%d m' % (geo_model.grid.regular_grid.extent[4]),
fontsize=14)
list_values = np.unique(np.round(well.T[:, 1])[:, 0]).tolist()
# Display lithology IDs
for i in boundaries:
plt.text((well_model.grid.regular_grid.extent[5] -
well_model.grid.regular_grid.extent[4]) / 24,
i * geo_model.grid.regular_grid.dz +
geo_model.grid.regular_grid.extent[4] +
2 * geo_model.grid.regular_grid.dz,
'ID: %d' % (np.round(well.T[:, 1])[:, 0][i + 1]),
fontsize=14)
del list_values[list_values.index(np.round(well.T[:, 1])[:, 0][i + 1])]
# Plot last ID
plt.text((well_model.grid.regular_grid.extent[5] -
well_model.grid.regular_grid.extent[4]) / 24,
geo_model.grid.regular_grid.extent[4] +
1 * geo_model.grid.regular_grid.dz,
'ID: %d' % (list_values[0]),
fontsize=14)
# Set legend handles
patches = [
mpatches.Patch(
color=cols[i],
label="{formation}".format(formation=surface[surface['id'].isin(
np.unique(np.round(sol.lith_block)))].surface.to_list()[i]))
for i in range(
len(surface[surface['id'].isin(np.unique(np.round(
sol.lith_block)))].surface.to_list()))
]
# Remove xticks
plt.tick_params(axis='x', labelsize=0, length=0)
# Set ylabel
plt.ylabel('Depth [m]')
# Set legend
plt.legend(handles=patches, bbox_to_anchor=(3, 1))
# Create depth dict
depth_dict = {
int(np.round(well.T[:, 1])[:, 0][i + 1]):
i * geo_model.grid.regular_grid.dz +
geo_model.grid.regular_grid.extent[4]
for i in boundaries
}
depth_dict[int(list_values[0])] = geo_model.grid.regular_grid.extent[4]
depth_dict = dict(sorted(depth_dict.items()))
return sol, well_model, depth_dict
#
# %%
geo_model.surfaces
# %%
# We will need to separate with surface belong to each series:
#
# %%
stratigraphy = 'fixed'
# %%
if stratigraphy == 'original':
gp.map_stack_to_surfaces(geo_model, {'Fault': 'Claudius_fault',
'Default series': ('0', '60', '250', '330'),
})
# Ordering the events from younger to older:
geo_model.reorder_series(['Fault', 'Default series', 'Basement'])
elif stratigraphy == 'fixed':
gp.map_stack_to_surfaces(geo_model, {'Default series': ('0', '60', '250'),
'Fault': 'Claudius_fault',
'Uncomformity': '330',
})
# Ordering the events from younger to older:
geo_model.reorder_series(['Default series', 'Fault', 'Uncomformity', 'Basement'])
# %%
# So far we did not specify which series/faults are actula faults:
# %%
geo_model.set_is_fault('Fault1')
# %%
# But we also need to add a new surface:
#
# %%
geo_model.add_surfaces('fault1')
# %%
# And finally assign the new surface to the new series/fault
#
# %%
gp.map_stack_to_surfaces(geo_model, {'Fault1': 'fault1'})
# %%
# Now we can just add input data as before (remember the minimum amount of
# input data to compute a model):
#
# %%
# Add input data of the fault
geo_model.add_surface_points(X=550, Y=0, Z=-30, surface='fault1')
geo_model.add_surface_points(X=650, Y=0, Z=-200, surface='fault1')
geo_model.add_orientations(X=600,
Y=0,
Z=-100,
surface='fault1',
pole_vector=(.3, 0, .3))