Field-Scale Dataset: 3D SOS-smoothed velocity volumes, 2D slices,

acoustic wavefields, and 8s shot-gather cubes across 5 frequency bands.

Paired velocity volumes / slices / wavefields / shot-gathers for ML
benchmarks in subsurface geophysics. See README.md for schema, splits,
and simulation parameters.

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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
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+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
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README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - image-to-image
+tags:
+  - benchmark
+  - geoscience
+  - seismology
+  - geophysics
+  - subsurface
+  - velocity-model
+  - acoustic-wavefield
+  - wave-propagation
+  - scientific-computing
+  - physics-informed
+  - HDF5
+pretty_name: Field-Scale Dataset
+size_categories:
+  - 10K<n<100K
+configs:
+  - config_name: default
+    data_files:
+      - split: all
+        path: "data/all.parquet"
+      - split: train
+        path: "data/train.parquet"
+      - split: test_in_dist
+        path: "data/test_in_dist.parquet"
+      - split: test_out_dist
+        path: "data/test_out_dist.parquet"
+dataset_info:
+  features:
+    - name: slice_id
+      dtype: string
+    - name: model_id
+      dtype: string
+    - name: data_type
+      dtype: string
+    - name: model_type
+      dtype: string
+    - name: split
+      dtype: string
+    - name: file_path
+      dtype: string
+    - name: orientation
+      dtype: string
+    - name: slice_index
+      dtype: int32
+    - name: slice_location_m
+      dtype: float32
+    - name: slice_axis
+      dtype: int32
+    - name: volume_shape
+      dtype: string
+    - name: depth_samples
+      dtype: int32
+    - name: width_samples
+      dtype: int32
+    - name: propagation_time_s
+      dtype: float32
+    - name: frequency_band
+      dtype: string
+    - name: f_min_hz
+      dtype: float32
+    - name: f_max_hz
+      dtype: float32
+    - name: velocity_min_m_per_s
+      dtype: float32
+    - name: velocity_max_m_per_s
+      dtype: float32
+    - name: velocity_mean_m_per_s
+      dtype: float32
+    - name: velocity_std_m_per_s
+      dtype: float32
+    - name: source_x_km
+      dtype: float32
+    - name: source_z_km
+      dtype: float32
+    - name: source_x_idx
+      dtype: int32
+    - name: source_z_idx
+      dtype: int32
+---
+
+# Field-Scale Dataset
+
+A large-scale benchmark dataset of **field-scale 3D subsurface velocity
+volumes** (SOS-smoothed, depth-truncated to 619 samples) paired with 2D
+velocity slices, their corresponding acoustic wavefields, and multi-source
+shot-gather cubes. The dataset spans multiple geological settings and covers
+five frequency bands (3-6, 3-8.5, 3-12, 3-17.5, 3-25 Hz), supporting wavefield
+prediction, seismic inversion, source-aware training from the 64-source
+shot-gather cubes, and out-of-distribution evaluation across held-out
+geology and broader frequency bandwidths.
+
+Maintained by the **SubsurfaceGen** project. Author affiliations withheld for double-blind review.
+
+## Dataset Summary
+
+| Metric | Value |
+|--------|-------|
+| **Total index rows** | 47078 |
+| **Total HDF5 files** | 47078 |
+| **3D SOS velocity volumes** (619×1000×1000) | 42 |
+| **3D volume breakdown by model type** | f3: 10, fault: 5, gom: 10, penobscot: 1, salt_canopy: 4, seam: 12 |
+| **2D velocity slices** | 4276 |
+| **Wavefields** (5s) | 21380 |
+| **Shot-gather cubes** (8s, 64 sources each) | 21380 |
+| **Train samples** (slice rows) | 4096 |
+| **Test in-distribution** (slice rows) | 100 |
+| **Test out-of-distribution** (slice rows) | 80 |
+| **Model types** | `f3`, `fault`, `gom`, `penobscot`, `salt_canopy`, `seam` |
+| **Frequency bands** | `3-12Hz`, `3-17.5Hz`, `3-25Hz`, `3-6Hz`, `3-8.5Hz` |
+
+## Dataset Structure
+
+### Parquet Index
+
+The `data/all.parquet` file is a **sidecar index** that catalogs every HDF5 file
+in the dataset. Each row represents one HDF5 file. The `slice_id` column links
+related files together --- a velocity slice, its wavefield(s), and its shot
+gather(s) all share the same `slice_id`.
+
+**Browse the index using the Dataset Viewer above** to explore all 25 columns interactively.
+
+### Data Types
+
+| `data_type` | Description | HDF5 Key | Shape | Count |
+|-------------|-------------|----------|-------|-------|
+| `model` | 3D SOS-smoothed velocity volume (depth-truncated to 619) | `velocity` | `(619, 1000, 1000)` | 42 |
+| `slice` | 2D velocity slice — training input **x** | `velocity` | `(nz, nx)` | 4276 |
+| `wavefield` | 2D acoustic wavefield — training target **y** (5s) | `wavefield` | `(nt, nz, nx)` | 21380 |
+| `gather` | Multi-source shot-gather cube (8s, 64 sources) | `shot_gather_cube` | `(n_sources, n_time, n_receivers)` | 21380 |
+
+### Splits
+
+| Split | Description |
+|-------|-------------|
+| `train` | Training data (all model types) |
+| `test_in_dist` | In-distribution test (same model types as train, different slices) |
+| `test_out_dist` | Out-of-distribution test (held-out geology) |
+
+Splits are assigned to 2D `slice` rows and inherited by their derived
+`wavefield` and `gather` rows (same `slice_id` ⇒ same split). The 42 3D
+`model` rows are not split-assigned and have `split = null` — use them
+for diagnostics, conditioning, or downstream studies rather than as
+train/test samples directly.
+
+### Propagation Time
+
+- **Wavefields** exist at **5s propagation time only**.
+- **Shot-gather cubes** exist at **8s propagation time only** (64 sources
+  stacked per slice).
+
+### Schema (25 columns)
+
+| # | Column | Type | Description |
+|---|--------|------|-------------|
+| 1 | `slice_id` | string | Links related files (e.g., `f3_042_il0123`). Null for 3D models |
+| 2 | `model_id` | string | Source 3D model (e.g., `f3_042`) |
+| 3 | `data_type` | string | `model` \| `slice` \| `wavefield` \| `gather` |
+| 4 | `model_type` | string | Geological category (e.g., `f3`, `gom`, `fault`) |
+| 5 | `split` | string | `train` \| `test_in_dist` \| `test_out_dist` |
+| 6 | `file_path` | string | Relative path to HDF5 file |
+| 7 | `orientation` | string | `inline` or `crossline` |
+| 8 | `slice_index` | int32 | Index in original 3D volume |
+| 9 | `slice_location_m` | float32 | Physical position in meters |
+| 10 | `slice_axis` | int32 | 1 (inline) or 2 (crossline) |
+| 11 | `volume_shape` | string | Source volume dims (e.g., `960x1000x1000`) |
+| 12 | `depth_samples` | int32 | nz of this array (varies by model type) |
+| 13 | `width_samples` | int32 | nx of this array |
+| 14 | `propagation_time_s` | float32 | Wavefields=5.0, shot-gather cubes=8.0 |
+| 15 | `frequency_band` | string | e.g., `3-25Hz` |
+| 16 | `f_min_hz` | float32 | Band minimum frequency |
+| 17 | `f_max_hz` | float32 | Band maximum frequency |
+| 18 | `velocity_min_m_per_s` | float32 | Min velocity (m/s) |
+| 19 | `velocity_max_m_per_s` | float32 | Max velocity (m/s) |
+| 20 | `velocity_mean_m_per_s` | float32 | Mean velocity (m/s) |
+| 21 | `velocity_std_m_per_s` | float32 | Std velocity (m/s) |
+| 22 | `source_x_km` | float32 | Source X position (km) |
+| 23 | `source_z_km` | float32 | Source Z depth (km) |
+| 24 | `source_x_idx` | int32 | Source X grid index |
+| 25 | `source_z_idx` | int32 | Source Z grid index |
+
+## Directory Structure
+
+```
+dataset_root/
+├── data/
+│   ├── all.parquet                       # Sidecar index (25 columns, all rows)
+│   ├── train.parquet                     # Same schema, split=train only
+│   ├── test_in_dist.parquet
+│   └── test_out_dist.parquet
+├── models/
+│   └── {model_type}_d619/               # 42 SOS-smoothed 3D volumes
+│       └── {model_id}_sos.h5           # shape (619, 1000, 1000)
+├── slices/                                # 4,276 individual 2D slices
+│   └── slice_{slice_id}.h5
+├── wavefields/
+│   └── 5s/{freq_band}/                  # 5 bands × 4,276 = 21,380 files
+│       └── wavefield_{slice_id}_*.h5
+└── shot_gathers/
+    └── 8s/{freq_band}/                  # 5 bands × 4,276 = 21,380 cubes
+        └── shot_gather_cube_{slice_id}.h5
+```
+
+## Usage
+
+### Browse the Index
+
+```python
+import pandas as pd
+
+# Load the full index
+df = pd.read_parquet("data/all.parquet")
+
+# Filter by split and data type
+train_slices = df[(df.split == "train") & (df.data_type == "slice")]
+train_wavefields = df[
+    (df.split == "train") & (df.data_type == "wavefield")
+    & (df.frequency_band == "3-6Hz")
+]
+
+# Pair velocity slices with wavefields for training
+pairs = train_slices.merge(train_wavefields, on="slice_id", suffixes=("_vel", "_wf"))
+print(f"Training pairs: {len(pairs)}")
+```
+
+### Load Individual HDF5 Files
+
+```python
+import h5py
+
+# 3D SOS velocity volume (root-group attr "metadata" is a JSON string)
+import json
+with h5py.File("models/f3_d619/f3_042_sos.h5", "r") as f:
+    volume = f["velocity"][:]             # (619, 1000, 1000) float32
+    meta = json.loads(f.attrs["metadata"])
+    print(meta["model_type"], meta["stats_smoothed"])
+
+# 2D velocity slice
+with h5py.File("slices/slice_f3_042_il_0123.h5", "r") as f:
+    velocity = f["velocity"][:]           # (nz, nx) float32
+    model_type = f["velocity"].attrs["model_type"]
+
+# Wavefield (5s)
+with h5py.File("wavefields/5s/3-6Hz/wavefield_f3_042_il_0123_srchorizontal5.000km.h5", "r") as f:
+    wavefield = f["wavefield"][:]         # (nt, nz, nx) float32
+    freq_band = f["wavefield"].attrs["frequency_band"]
+
+# Shot-gather cube (8s, 64 sources stacked)
+with h5py.File("shot_gathers/8s/3-6Hz/shot_gather_cube_f3_042_il_0123.h5", "r") as f:
+    cube = f["shot_gather_cube"][:]       # (n_sources, n_time, n_receivers) float32
+    n_src = f["shot_gather_cube"].attrs["n_sources"]
+```
+
+## Dataset Creation
+
+### Source Data
+
+Field-scale 3D velocity models inspired by publicly available subsurface surveys:
+- **F3** (Netherlands North Sea)
+- **GOM** (Gulf of Mexico)
+- **Fault** (synthetic fault models)
+- **Salt Canopy** (synthetic salt body models)
+- **SEAM** (SEG Advanced Modeling)
+- **Penobscot** (offshore Canada, held out for OOD testing)
+
+Models are processed through **structure-oriented smoothing (SOS)**, following
+Hale (2009, CWP-635), to produce smooth background velocity fields suitable
+for acoustic wave propagation, and depth-truncated to **619 samples** so all
+volumes share a common depth.
+
+### Wavefield Generation
+
+2D acoustic wavefields are generated by solving the constant-density acoustic
+wave equation on each velocity slice using finite-difference time-domain
+(FDTD) simulation, implemented with **Devito** — a Python DSL that compiles
+optimized stencil kernels from symbolic PDEs (Louboutin et al., 2019). Each
+slice is simulated for 5 seconds per frequency band.
+
+**Numerical simulation parameters (all bands):**
+
+| Parameter | Value |
+|---|---|
+| Solver / kernels | Devito `examples.seismic` AcquisitionGeometry + Model |
+| Grid spacing | 10 m × 10 m |
+| Time step | 1.0 ms |
+| FD stencil space order | 8 |
+| Absorbing boundary | 60-cell sponge (Devito `bcs="damp"`) |
+| Top boundary | Free surface (`fs=True`) |
+| Wavefield temporal subsample | factor 14 (stored every 14th step) |
+| Receivers | 1,000 per slice, streamer at 10 m depth |
+| Source depth | 10 m |
+
+**Source wavelet — band-limited Ricker.** The injected source time function
+is a Ricker wavelet (negative normalized second derivative of a Gaussian),
+then band-passed with a 4th-order Butterworth filter (forward-backward,
+zero-phase) and amplitude-normalized by `sqrt(bandwidth / 24 Hz)` so that
+wider-band sources carry physically consistent energy. Peak frequency
+`f0` is chosen per band for spectral centering:
+
+| Band | f0 (Hz) | Bandpass |
+|---|---:|---|
+| 3-6 Hz | 4.5 | 3.0 – 6.0 |
+| 3-8.5 Hz | 5.75 | 3.0 – 8.5 |
+| 3-12 Hz | 7.5 | 3.0 – 12.0 |
+| 3-17.5 Hz | 10.25 | 3.0 – 17.5 |
+| 3-25 Hz | 14.0 | 3.0 – 25.0 |
+
+For each wavefield file, the source x-position is sampled uniformly at random
+along the slice (with a 0.5 km margin from each edge). Seeds are fixed
+(`random_seed=42`) so source placements are reproducible from the metadata.
+
+### Shot-Gather Cubes
+
+For seismic inversion and source-aware studies, each slice is additionally
+simulated for **8 seconds** with **64 equally-spaced sources** (same 0.5 km
+edge margins), producing a stacked shot-gather cube per slice per band.
+Each cube has shape `(64, n_time, 1000)` (sources × decimated time samples ×
+receivers), is stored under HDF5 key `shot_gather_cube`, and is time-
+decimated by factor 14. Simulation parameters are otherwise identical to
+the wavefield runs above.
+
+## References
+
+- **Devito (finite-difference solver)** — Louboutin, M., Lange, M., Luporini,
+  F., Kukreja, N., Witte, P. A., Herrmann, F. J., Velesko, P., & Gorman, G. J.
+  (2019). *Devito (v3.1.0): an embedded domain-specific language for finite
+  differences and geophysical exploration.* Geoscientific Model Development,
+  12(3), 1165-1187. <https://doi.org/10.5194/gmd-12-1165-2019>
+- **Structure-oriented smoothing (3D velocity preprocessing)** — Hale, D.
+  (2009). *Structure-oriented smoothing and semblance.* CWP-635, Center for
+  Wave Phenomena, Colorado School of Mines.
+
+## Citation
+
+```bibtex
+@dataset{subsurfacegen_field_scale_dataset,
+  title={Field-Scale Dataset: SOS-smoothed velocity volumes, 2D slices, wavefields, and 8s shot-gather cubes},
+  author={Anonymous},
+  year={2026},
+  url={https://huggingface.co/datasets/subsurfacegen/field-scale-dataset},
+}
+```
+
+## License
+
+This dataset is released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
+
+## Contact
+
+Removed for anonymous review.

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