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SiliciclasticReservoirs dataset by AnonymouScientist
⭐ 59.4
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Dataset

SiliciclasticReservoirs

by AnonymouScientist anonymouscientist/siliciclasticreservoirs
Free2AITools Nexus Index
59.4
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 62
P: Popularity 52
R: Recency 85
Q: Quality 50
Tech Context
Vital Performance —
Source β†’
Data Integrity 59.4 FNI Score
- Size
- Rows
- Tokens
Dataset Information Summary
Entity Passport
Registry ID anonymouscientist/siliciclasticreservoirs
License CC-BY-4.0
Provider huggingface
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Cite this dataset

Academic & Research Attribution

BibTeX 
@misc{hf_dataset_anonymouscientist_siliciclasticreservoirs,
  author = {AnonymouScientist},
  title = {SiliciclasticReservoirs Dataset},
  year = {2026},
  howpublished = {\url{https://huggingface.co/datasets/AnonymouScientist/SiliciclasticReservoirs}},
  note = {Accessed via Free2AITools.}
}
APA Style
AnonymouScientist. (2026). SiliciclasticReservoirs [Dataset]. Free2AITools. https://huggingface.co/datasets/AnonymouScientist/SiliciclasticReservoirs

πŸ”¬Technical Deep Dive

Full Specifications [+]

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 62
Popularity (P) 52
Recency (R) 85
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for SiliciclasticReservoirs: Authority (A:62), Popularity (P:52), Recency (R:85), Quality (Q:50). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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Downloads
35,110

🎯 Task Categories

image-segmentation image-classification text-to-image other

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Dataset Specification

SiliciclasticReservoirs

1,000,000 synthetic 3D siliciclastic-reservoir geology cubes generated from rule-based sedimentological simulations (turbidite lobes + 6 fluvial-channel architectures + delta-fan distributary). Cubes are voxelized at (64, 64, 32) cells. Each sample carries facies, porosity, permeability, and a structured set of geological conditioning parameters.

Designed to train conditional generative models (flow matching, diffusion, etc.) of subsurface geology under interpretable physical conditioning.

Quick stats

  • 1,000,000 samples across 8 reservoir architectures
  • Cube shape: (64, 64, 32) voxels β€” (x, y, z), z is depth (0 = base)
  • 4 voxel arrays per sample: binary facies, 6-class facies, porosity, permeability
  • Compact slim parquet (9–12 cols) and full reproducibility parquet (25–75 cols)
  • Captions for text-conditioning experiments
  • Fully reproducible β€” every sample regenerable from (seed, params)

File structure

text 
SiliciclasticReservoirs/
β”œβ”€β”€ README.md                   ← this file
β”œβ”€β”€ DATASHEET.md                ← Datasheet for Datasets (Gebru et al. 2018)
β”œβ”€β”€ splits/                     ← deterministic 90/5/5 split, stratified by layer_type
β”‚   β”œβ”€β”€ train.parquet           ← 900,000 rows
β”‚   β”œβ”€β”€ validation.parquet      ←  50,000 rows
β”‚   └── test.parquet            ←  50,000 rows
β”œβ”€β”€ lobe/                       ← 200,000 samples
β”‚   β”œβ”€β”€ sha

Social Proof

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Source summary: Based on Hugging Face metadata. Not a recommendation.

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πŸ›‘οΈ Dataset Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-dataset--anonymouscientist--siliciclasticreservoirs
slug
anonymouscientist--siliciclasticreservoirs
source
huggingface
author
AnonymouScientist
license
CC-BY-4.0
tags
task_categories:image-segmentation, task_categories:image-classification, task_categories:text-to-image, task_categories:other, language:en, license:cc-by-4.0, size_categories:1m<n<10m, format:parquet, modality:text, modality:3d, library:datasets, library:pandas, library:polars, library:mlcroissant, region:us, geology, earth-sciences, reservoir, synthetic, voxel, 3d, flow-matching, diffusion, generative-modeling, subsurface, petroleum, groundwater, carbon-storage, conditional-generation

βš™οΈ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag

πŸ“Š Engagement & Metrics

downloads
35,110
stars
null
forks
null

Data indexed from public sources. Updated daily.