Issue with Fault Interaction in 'Tutorial ch1_5_fault_relations.ipynb'

[FisPrObXu]

Dear Gempy developers,

I am currently working through the Gempy tutorial ch1_5_fault_relations.ipynb. While attempting to understand the logic behind setting up fault relationships in Gempy, I noticed an issue. In my results, it seems that fault1 and fault2 do not exhibit any interaction. They appear as independent entities rather than fault2 being deformed by the influence of fault1 as shown in the official example.

I am attaching my runtime environment details and the resulting output for reference. Could you please help me understand why my faults are not interacting as expected and how to resolve this issue?

Thank you for your assistance.

Best regards,
Jingbo Xu

APPENDIX:

1、My runtime environment
packages in environment at D:\anaconda3\envs\gempy-env:
Name Version Build Channel
asttokens 2.4.1 pyhd8ed1ab_0 conda-forge
bzip2 1.0.8 hcfcfb64_5 conda-forge
ca-certificates 2024.6.2 h56e8100_0 conda-forge
certifi 2024.6.2 pypi_0 pypi
charset-normalizer 3.3.2 pypi_0 pypi
colorama 0.4.6 pyhd8ed1ab_0 conda-forge
comm 0.2.2 pyhd8ed1ab_0 conda-forge
contourpy 1.2.1 pypi_0 pypi
cycler 0.12.1 pypi_0 pypi
debugpy 1.8.1 py312h53d5487_0 conda-forge
decorator 5.1.1 pyhd8ed1ab_0 conda-forge
exceptiongroup 1.2.0 pyhd8ed1ab_2 conda-forge
executing 2.0.1 pyhd8ed1ab_0 conda-forge
filelock 3.14.0 pypi_0 pypi
fonttools 4.53.0 pypi_0 pypi
fsspec 2024.6.0 pypi_0 pypi
gempy 2024.1.4 pypi_0 pypi
gempy-engine 2024.1.4.2 pypi_0 pypi
gempy-plugins 2024.1.0 pypi_0 pypi
gempy-viewer 2024.1.4 pypi_0 pypi
idna 3.7 pypi_0 pypi
imageio 2.34.1 pypi_0 pypi
importlib-metadata 7.1.0 pyha770c72_0 conda-forge
importlib_metadata 7.1.0 hd8ed1ab_0 conda-forge
intel-openmp 2021.4.0 pypi_0 pypi
ipykernel 6.29.3 pyha63f2e9_0 conda-forge
ipython 8.25.0 pyh7428d3b_0 conda-forge
jedi 0.19.1 pyhd8ed1ab_0 conda-forge
jinja2 3.1.4 pypi_0 pypi
jupyter_client 8.6.2 pyhd8ed1ab_0 conda-forge
jupyter_core 5.7.2 py312h2e8e312_0 conda-forge
kiwisolver 1.4.5 pypi_0 pypi
krb5 1.21.2 heb0366b_0 conda-forge
lazy-loader 0.4 pypi_0 pypi
libexpat 2.6.2 h63175ca_0 conda-forge
libffi 3.4.2 h8ffe710_5 conda-forge
libsodium 1.0.18 h8d14728_1 conda-forge
libsqlite 3.45.3 hcfcfb64_0 conda-forge
libzlib 1.3.1 h2466b09_1 conda-forge
markupsafe 2.1.5 pypi_0 pypi
matplotlib 3.9.0 pypi_0 pypi
matplotlib-inline 0.1.7 pyhd8ed1ab_0 conda-forge
mkl 2021.4.0 pypi_0 pypi
mpmath 1.3.0 pypi_0 pypi
nest-asyncio 1.6.0 pyhd8ed1ab_0 conda-forge
networkx 3.3 pypi_0 pypi
numpy 1.26.4 pypi_0 pypi
openssl 3.3.1 h2466b09_0 conda-forge
packaging 24.0 pyhd8ed1ab_0 conda-forge
pandas 2.2.2 pypi_0 pypi
parso 0.8.4 pyhd8ed1ab_0 conda-forge
pickleshare 0.7.5 py_1003 conda-forge
pillow 10.3.0 pypi_0 pypi
pip 24.0 pyhd8ed1ab_0 conda-forge
platformdirs 4.2.2 pyhd8ed1ab_0 conda-forge
plotly 5.22.0 pyhd8ed1ab_0 conda-forge
pooch 1.8.1 pypi_0 pypi
prompt-toolkit 3.0.46 pyha770c72_0 conda-forge
psutil 5.9.8 py312he70551f_0 conda-forge
pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge
pygments 2.18.0 pyhd8ed1ab_0 conda-forge
pyparsing 3.1.2 pypi_0 pypi
python 3.12.3 h2628c8c_0_cpython conda-forge
python-dateutil 2.9.0.post0 pypi_0 pypi
python-dotenv 1.0.1 pypi_0 pypi
python_abi 3.12 4_cp312 conda-forge
pytz 2024.1 pypi_0 pypi
pyvista 0.43.8 pypi_0 pypi
pywin32 306 py312h53d5487_2 conda-forge
pyzmq 26.0.3 py312hd7027bb_0 conda-forge
requests 2.32.3 pypi_0 pypi
scikit-image 0.23.2 pypi_0 pypi
scipy 1.13.1 pypi_0 pypi
scooby 0.10.0 pypi_0 pypi
setuptools 70.0.0 pyhd8ed1ab_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
sympy 1.12.1 pypi_0 pypi
tbb 2021.12.0 pypi_0 pypi
tenacity 8.3.0 pyhd8ed1ab_0 conda-forge
tifffile 2024.5.22 pypi_0 pypi
tk 8.6.13 h5226925_1 conda-forge
torch 2.3.1 pypi_0 pypi
torchaudio 2.3.1 pypi_0 pypi
torchvision 0.18.1 pypi_0 pypi
tornado 6.4 py312he70551f_0 conda-forge
traitlets 5.14.3 pyhd8ed1ab_0 conda-forge
typing_extensions 4.12.1 pyha770c72_0 conda-forge
tzdata 2024.1 pypi_0 pypi
ucrt 10.0.22621.0 h57928b3_0 conda-forge
urllib3 2.2.1 pypi_0 pypi
vc 14.3 ha32ba9b_20 conda-forge
vc14_runtime 14.38.33135 h835141b_20 conda-forge
vs2015_runtime 14.38.33135 h22015db_20 conda-forge
vtk 9.3.0 pypi_0 pypi
wcwidth 0.2.13 pyhd8ed1ab_0 conda-forge
wheel 0.43.0 pyhd8ed1ab_1 conda-forge
xz 5.2.6 h8d14728_0 conda-forge
zeromq 4.3.5 he1f189c_4 conda-forge
zipp 3.17.0 pyhd8ed1ab_0 conda-forge

2、Part of resulting outputs

[javoha]

Hi,
thanks for your question. You are definitely right - this tutorial is a little confusing. I have to go through it in more detail to see where it goes wrong and it is noted as something we need to improve. For now: Can you run the following piece of code. This should give you the desired result with a more straightforward setup. After initiating the model we define the structural frame, assign two groups as faults and set the fault relationships.

import gempy as gp
import gempy_viewer as gpv
from gempy_engine.core.data.stack_relation_type import StackRelationType

# Aux imports
import numpy as np
import os

#data_path = os.path.abspath('../../')

# Initiate geomodel
geo_model: gp.data.GeoModel = gp.create_geomodel(
    project_name='Faults_relations',
    extent=[0, 1000, 0, 1000, -1000, -400],
    resolution=[20, 20, 20],
    refinement=4,  # * For this model is better not to use octrees because we want to see what is happening in the scalar fields
    importer_helper=gp.data.ImporterHelper(
        path_to_orientations="tut_ch1-5_orientations.csv",
        path_to_surface_points="tut_ch1-5_points.csv",
    )
)

# Map geological series to surfaces
gp.map_stack_to_surfaces(
    gempy_model=geo_model,
    mapping_object={
        "Fault_Series1" : ('fault1'),
        "Fault_Series2": ('fault2'),
        "Strat_Series1": ('rock1', 'rock2', 'rock3', 'rock4'),
    }
)
# Defining two structural groups as faults
geo_model.structural_frame.structural_groups[0].structural_relation = StackRelationType.FAULT
geo_model.structural_frame.structural_groups[1].structural_relation = StackRelationType.FAULT

# Setting the relations
geo_model.structural_frame.fault_relations = np.array(
    [[0, 1, 1],
     [0, 0, 1],
     [0, 0, 0]]
)

# compute model
gp.compute_model(geo_model)

gpv.plot_2d(geo_model)

Let me know if this works for you and if you have any questions.
Cheers
Jan

[FisPrObXu]

Hi Jan,

Thank you very much for your response. After running the code you provided, I was able to observe the ideal fault relationships.

I also noticed something interesting when I ran the following code in original tutorial ch1_5_fault_relations.ipynb:

gp.add_structural_group(
    model=geo_model,
    group_index=1,
    structural_group_name="fault_series_2",
    elements=[fault2],
    structural_relation=gp.data.StackRelationType.FAULT,
    fault_relations=gp.data.FaultsRelationSpecialCase.OFFSET_ALL
)
print(geo_model.structural_frame)

from gempy_engine.core.data.kernel_classes.solvers import Solvers

geo_model.interpolation_options.kernel_options.kernel_solver = Solvers.SCIPY_CG
geo_model.interpolation_options.kernel_options.compute_condition_number = True
gp.compute_model(gempy_model=geo_model)

When I set the computation backend to PYTORCH, I also obtained the ideal results.But when I use the numpy backend, the previous issues reappear.

gp.compute_model(
    gempy_model=geo_model,
    engine_config=gp.data.GemPyEngineConfig(backend=gp.data.AvailableBackends.PYTORCH)
)

Since I'm a novice in both geology and computing, I'm not sure if this observation is useful. I hope it helps.

Thank you again for your assistance!

Best regards,

Jingbo Xu