1h. Unconformities and fault

This tutorial will demonstrate how to add unconformities to a mode using LoopStructural.

<matplotlib.contour.QuadContourSet object at 0x7f6e38a1dba0>

import numpy as np
import pandas as pd
from LoopStructural import GeologicalModel
import matplotlib.pyplot as plt

data = pd.DataFrame(
    [
        [100, 100, 150, 0.17, 0, 0.98, 0, "strati"],
        [100, 100, 170, 0, 0, 0.86, 0, "strati3"],
        [100, 100, 100, 0, 0, 1, 0, "strati2"],
        [100, 100, 50, 0, 0, 1, 0, "nconf"],
        [100, 100, 50, 0, 0, 1, 0, "strati4"],
        [700, 100, 190, 1, 0, 0, np.nan, "fault"],
    ],
    columns=["X", "Y", "Z", "nx", "ny", "nz", "val", "feature_name"],
)

model = GeologicalModel(np.zeros(3), np.array([1000, 1000, 200]))
model.data = data
model.create_and_add_foliation("strati2", buffer=0.0)
model.add_unconformity(model["strati2"], 0)
model.create_and_add_fault(
    "fault",
    50,
    minor_axis=300,
    major_axis=500,
    intermediate_axis=300,
    fault_center=[700, 500, 0],
)

model.create_and_add_foliation("strati", buffer=0.0)
model.add_unconformity(model["strati"], 0)
model.create_and_add_foliation("strati3", buffer=0.0)
model.create_and_add_foliation("nconf", buffer=0.0)
model.add_onlap_unconformity(model["nconf"], 0)
model.create_and_add_foliation("strati4")


stratigraphic_columns = {
    "strati4": {"series4": {"min": -np.inf, "max": np.inf, "id": 5}},
    "strati2": {
        "series1": {"min": 0.0, "max": 2.0, "id": 0, "colour": "red"},
        "series2": {"min": 2.0, "max": 5.0, "id": 1, "colour": "red"},
        "series3": {"min": 5.0, "max": 10.0, "id": 2, "colour": "red"},
    },
    "strati": {
        "series2": {"min": -np.inf, "max": -100, "id": 3, "colour": "blue"},
        "series3": {"min": -100, "max": np.inf, "id": 4, "colour": "blue"},
    },
}


model.set_stratigraphic_column(stratigraphic_columns)

xx, zz = np.meshgrid(np.linspace(0, 1000, 100), np.linspace(0, 200, 100))
yy = np.zeros_like(xx) + 500
points = np.array([xx.flatten(), yy.flatten(), zz.flatten()]).T
val = model["strati"].evaluate_value(points)
val2 = model["strati2"].evaluate_value(points)
val3 = model["strati3"].evaluate_value(points)
val4 = model["strati4"].evaluate_value(points)
uf = model["strati4"].regions[0](points)
fval = model['fault'].evaluate_value(points)

plt.contourf(val.reshape((100, 100)), extent=(0, 1000, 0, 200), cmap='viridis')
plt.contourf(val2.reshape((100, 100)), extent=(0, 1000, 0, 200), cmap='Reds')
plt.contourf(val3.reshape((100, 100)), extent=(0, 1000, 0, 200), cmap='Blues')
plt.contourf(val4.reshape((100, 100)), extent=(0, 1000, 0, 200), cmap='Greens')
plt.contour(fval.reshape((100, 100)), [0], extent=(0, 1000, 0, 200))