---
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: SubsurfaceBench
size_categories:
  - 1K<n<10K
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
---

# SubsurfaceBench

A large-scale benchmark dataset of field-scale 3D subsurface velocity models
inspired by real geological surveys, paired with 2D velocity slices and their
corresponding acoustic wavefields and shot gathers. The dataset spans multiple
geological settings and contains thousands of paired samples, providing a
comprehensive benchmark for machine learning tasks in computational geophysics.

While currently tested with Fourier Neural Operators (FNOs) for predicting
seismic wave propagation, SubsurfaceBench is designed to support a broad range
of ML architectures and research directions in subsurface modeling.

## Dataset Summary

| Metric | Value |
|--------|-------|
| **Total index rows** | 12828 |
| **Total HDF5 files** | 12828 |
| **3D velocity models** | 0 |
| **2D velocity slices** | 4276 |
| **Wavefields** | 4276 |
| **Shot gathers** | 4276 |
| **Train samples** | 4096 |
| **Test in-distribution** | 100 |
| **Test out-of-distribution** | 80 |
| **Model types** | `f3`, `fault`, `gom`, `penobscot`, `salt_canopy`, `seam` |
| **Frequency bands** | `3-6Hz` |

## 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 | Count |
|-------------|-------------|----------|-------|
| `model` | 3D SOS-smoothed velocity volume | `velocity` | 0 |
| `slice` | 2D velocity slice (training input **x**) | `velocity` | 4276 |
| `wavefield` | 2D acoustic wavefield (training target **y**) | `wavefield` | 4276 |
| `gather` | Shot gather (alternative target **y**) | `shot_gather` | 4276 |

### 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) |

### Propagation Time Constraint

- **Wavefields** exist at **5s propagation time only**
- **Shot gathers** exist at both **5s and 8s** propagation time

### 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 | Simulation time: 5.0 or 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)
├── models/                              # 3D SOS velocity volumes (flat)
├── slices/                              # 2D velocity slices (individual HDF5)
├── wavefields/
│   └── {split}/5s/{freq_band}/       # Nested: 5s propagation ONLY
└── shot_gathers/
    └── {split}/{5s|8s}/{freq_band}/ # Nested: 5s AND 8s propagation
```

## 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

# 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"]
    orientation = f["velocity"].attrs["orientation"]

# Wavefield
with h5py.File("wavefields/train/5s/3-6Hz/wavefield_f3_042_il_0123.h5", "r") as f:
    wavefield = f["wavefield"][:]         # (nt, nx, nz) float32
    freq_band = f["wavefield"].attrs["frequency_band"]

# Shot gather
with h5py.File("shot_gathers/train/5s/3-6Hz/shot_gather_f3_042_il_0123.h5", "r") as f:
    gather = f["shot_gather"][:]          # (nt, nx) float32
    prop_time = f["shot_gather"].attrs["propagation_time_s"]
```

## 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 SOS (Sum of Squares) structural smoothing to
create smooth background velocity fields suitable for acoustic wave
propagation.

### Wavefield Generation

2D acoustic wavefields are generated by solving the acoustic wave equation on
each velocity slice using finite-difference time-domain (FDTD) simulation,
with a Ricker wavelet source at the surface center.

## Citation

```bibtex
@dataset{subsurfacebench,
  title={SubsurfaceBench},
  author={Stanford Exploration Project},
  year={2026},
  url={https://huggingface.co/datasets/jdstitt/subsurfacebench},
}
```

## License

This dataset is released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).

## Contact

Stanford Exploration Project (SEP), Stanford University.