Distance-based localiztion test script for testing full update workflow using ERT storage with ensemble experiments #230
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dafeda
reviewed
Aug 19, 2025
distance_based_on_real_case.py
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| groups = list(param_config_all.keys()) | ||
| realizations = ensemble.get_realization_list_with_responses() | ||
| group_number = 0 | ||
| for group_name in groups: |
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You can use enumerate to avoid having to increment group_number manually.
for group_number, group_name in enumerate(groups)
dafeda
reviewed
Aug 19, 2025
distance_based_on_real_case.py
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| smoother = DistanceESMDA( | ||
| covariance=C_D, observations=observations, alpha=alpha, seed=seed | ||
| ) | ||
| smoother.prepare_assimilation(Y, truncation=0.99) |
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I think we can as part of the assimilate_batch function and only do the actual calculations if self.X3 and self.D` are not already set.
dafeda
reviewed
Aug 21, 2025
| # Turn on/off export of field parameters into 3D parameter files in ROFF format to be read by RMS. | ||
| WRITE_STATS_PARAMS = True | ||
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| # Common definition of ERTBOX for all zones in Drogon |
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Does the grid file specified using the GRID keyword in the Drogon project contain all this information?
dafeda
reviewed
Aug 21, 2025
| OBS_FILE_PATH = ( | ||
| "/project/fmu/users/olia/drogon_20250623_11-50/resmod/ff/25.0.0/rms/model/" | ||
| ) | ||
| OBS_FILE = "summary_obs_with_localization_attributes.csv" |
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Can you push this file to the repo as well or is it perhaps too big?
dafeda
reviewed
Aug 21, 2025
distance_based_on_real_case.py
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| OBS_SUMMARY_WITH_LOCAL_ATTRIBUTES_FILE = OBS_FILE_PATH + OBS_FILE | ||
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| # Hard-coded a classification of parameter groups into scalars, 2D or 3D field parameters | ||
| # NOTE: This should be available from ERT storage (ERT knows about the source the keyword FIELD, SURFACE GEN_KW) |
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Here's one way to get the parameter type:
with open_storage(storage_path, "r") as storage:
experiment = storage.get_experiment_by_name(experiment_name)
print(experiment.parameter_configuration["COND"].type)
# >> field
print(experiment.parameter_configuration["INIT_TEMP_SCALE"].type)
# >> gen_kw
dafeda
reviewed
Aug 21, 2025
distance_based_on_real_case.py
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| # (e.g for permeabilit or porosity) could be <zone_name>_<facies>_<petro_name> | ||
| # for petrophysical fields to be updated simultaneously with facies update from APS. | ||
| # For reservoir zones without facies modelling, the convention could be <zone_name>_<petro_name> | ||
| # NOTE: An additional parameter in FIELD keyword with zone name can solve the problem if naming convention |
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oddvarlia
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I suggest we generate .csv files that are comma delimited and not delimited by space. This can avoid potential bugs if for example a zone name has a space in its name. |
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…ning on a case from ERT storage
update distance_based_on_real_case.py
Added seismic obs and RFT obs Attempt to save update to ERT storage Added tracer obs Added tracer obs file Added ESMDA update to scalars Modified the path to where on scratch to find the ensemble Ensure that updated ensemble in storage has iteration greater than 0 Added new scaling function Changed seismic_range Update scalar parameters Updated document lines
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The script is initially using Drogon case from this summer.
The distance-based localization depends on having position for observations (well prod observations and seismic points for 4D)
This is currently not available in ERT and storage directories created by ERT so the information must be taken from the FMU setup for seismic observations and the RMS forward model.
A script to extract position data from wells using RMS project is included
The plan is to get position data for the seismic observations as well by loading files with seismic data points including position from ERT project.
Main goal of this branch is to test and evaluate performance of distance-based localization before the method is implemented in ERT code.
This branch is built on the branch Distance-based localization per 15.08.2025