Comments (3)
The posterior parameters from an AHM run is automatically stored, and is already being used in prediction runs:
flownet/src/flownet/prediction/_run_pred.py
Lines 53 to 54 in 6447c6d
The same file could probably be used when solving this task.
A possible workflow could be:
- Grab the previously saved posterior parameter values (from the stored file mentioned above, already in use by
pred
). - Fit to some prior distribution parameters.
- Modify* the setup here, where the prior parameters are currently initialized:
flownet/src/flownet/ahm/_run_ahm.py
Lines 358 to 376 in 2107fc5
The modification would include then not only supporting creating dataframes with prior distributions (with distribution parameters from the config), but also from the stored posterior parameters. The dataframes already have support for defining prior distributions e.g. per tube, so the change necessary should not be huge 🎉
from flownet.
All prior parameter distributions are currently defined by min and max (or one of these and a mean) and a boolean indicating if the distribution is loguniform or uniform. These prior distribution parameters are save in the file parameters.pickle. Actual values are sampled by ERT and updated values are written to a parquet file. In prediction mode, these values are read by the ERT job CREATE_FLOWNET_MODEL (_render_realization.py). Proposed solution: the parquet file for the final iteration of the previous history match should be read, the mean should be calculated, and new distribution parameters should overwrite the values in the pickle file.
from flownet.
A new optional entry can be added to the config file under model_parameters (ahm_case) that specifies the path to a previous HM experiment:
The file parameters_iteration-latest.parquet.gzip should be located in ahm_case.
The ensemble-mean parameter values are computed and used to find a new extreme value for a uniform or loguniform distribution through optimization (the maximum value from the prior distribution is kept fixed if the mean has moved towards the minimum and vice versa).
from flownet.
Related Issues (20)
- Unexpected behaviour for very simple box-type models
- Layer-based attribution of water and oil phase volumes to FlowNet HOT 2
- Add well connection factors as HM parameter HOT 4
- Refactor _simulation_keywords.py
- Problems running Norne with tracers with OPM-Flow
- Support I,J,K-based definition of fault segment orientation
- Brine should be better specified under phases item in input yml file
- Treatment of duplicate wells HOT 3
- Valid FlowNet without additional nodes and removal of well nodes
- Export FlowNet predictions required for ML workflow
- Check if FlowNet still runs smoothly with LSF
- Processing of schedule information taking too long
- Incorrect initialization of saturations
- Allow for specifying grid properties
- Coarse 3D grids: a general discussion
- combine options for additional node placement
- Support ert option ensemble_experiment
- Read existing network and schedule from file
- Possible inconsistency in region numbering
- Zero-rate measurements not used
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from flownet.