- Prerequisite: install eCalc.
- Use: run
run-eCalc.py
. Read output fromemissions_total.csv
.
- Pre-process the simulator output (production data)
- Runs eCalc
- Extract emission results
- Write results
- Plot (optionally)
The difficult part is knowing how to do the configuration in
"some-model.yaml"
, which contains all-caps keywords- the various constituent relation files (
*.csv
).
The configuration herein is mainly sourced from the examples in the eCalc docs. But I cannot guarantee that the absolute numbers make sense, or that all factors that impact emissions are logically configured, or even taken into account.
Fortunately, for our purposes, the absolute numbers are only of secondary importance.
What is important, before trying to optimise anything,
it to check that indeed the emissions exhibit sensitivity
to the control parameters that you wish to optimise for.
You should perform this check
by manipulating df
in run-eCalc.py:preprocess_prod()
or the raw .csv
time series,
to reflect the relevant parameters, and then run this script with "plot" as an argument.
- Gas lift
- Different pump setup (no common manifold)
Before run-eCalc.py
, ERT must write the relevant input variables:
- Copy this dir into the member dir
- Overwrite whatever
infile
points to (currently"from_geir.csv"
) with ECLIPSE or OPM output. - Overwrite whatever else gets specified from the ensemble member (state/param.\ vector).
For ideas, see
model_path
(currently"reek-model.yaml"
).