SciLM/ResBench-reference
ResBench reference The reference data that ResBench scores generative reservoir models against. Every volume was produced by the ResMill process simulator (commit in ENGINE.txt) under the same rules as the SiliciclasticReservoirs training dataset. You do not need to download it by hand: pip install "resbench[download]" resbench download # fetches this repository into the local cache resbench score SUBMISSION --out results.json Contents path what… See the full description on the dataset page: https://huggingface.co/datasets/SciLM/ResBench-reference.
ResBench reference
The reference data that ResBench scores generative reservoir models against. Every volume was produced by the ResMill process simulator (commit in ENGINE.txt) under the same rules as the SiliciclasticReservoirs training dataset. You do not need to download it by hand:
pip install "resbench[download]"
resbench download # fetches this repository into the local cache
resbench score SUBMISSION --out results.jsonContents
Eight environments: lobe, delta and six channel presets (PVSHOESTRING, CBLABYRINTH, CBJIGSAW, SHDISTAL, SHPROXIMAL, MEANDEROXBOW). Volumes are binary sand (1) / mud (0), int8.
Everything here can be rebuilt from the ResBench repository's tools/ (command sequence in its SPEC.md) and ResMill at the commit in ENGINE.txt. Scored against itself, this reference matches in all 31 (task, check) cells.
