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Sensitivity analysis in ERT #8457
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Just to clarify after some discussion with @sondreso: |
Minutes from today's meeting related to mainly step 2 in the current milestone.
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More minutes after discussion with @oyvindeide (just unsorted ideas, not necessarily action points) :
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Minutes from the meeting: The topics were (among others) parameter group names and merging strategies of GEN_KW and DESIGN_MATRIX
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This issue is a work in progress!
Description
Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs. This is usually achieved by varying the input parameters and analyzing how much the model response changes.
Current usage
The input usually starts with the design of the analysis case that contains different scenarios introduced in an
<design_input.xlsx>
file, which is sequentially processed byfmudesign
tool to produce an output matrix<output_matrix.xlsl>
containing list of parameter realizations.Forward model
DESIGN2PARAMS
reads this file and appends the parameter values into<parameters.txt>
which is then read by ert.Step 1: Making ERT capable of reading, storing and outputting sensitivity parameters
Step 2: Sensitivity analysis in ERT
This milestone should alleviate running and using the
fmudesign
tool by providing a dedicatedsensitivity wizard
(GUI) in ert capable of specifying custom analysis scenarios yielding parameter specification for ert.Definition of done
Step 1:
DESIGN_MATRIX
keyword can be used to specify the .xlsx sheet to load sensitivity data from- [ ] It should be possible to load .xlsl sheet directly from the GUI in a new run model (starting withensemble experiment
with the possibility to choose "load from")DESIGN2PARAMS
is no longer need when using theDESIGN_MATRIX
keywordparameters.json
andparameters.txt
contains the same parameters when using theDESIGN_MATRIX
keyword.DESIGN_MATRIX
can be used whenDESIGN2PARAMS
is used in configStep 2:
Issues
This should also include validation of the setup such that as many as possible of the following errors should not occur when running the forward models on the compute cluster:
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