---
tags:
- seismic
- deblending
- common-receiver
- segy
- geophysics
task_categories:
- image-to-image
- other
pretty_name: Deblending Common-Receiver Dataset
viewer: false
---
# Deblending Common-Receiver Dataset
Paired common-receiver SEG-Y volumes for supervised seismic deblending.
## Task
This dataset is used for direct paired regression:
```text
denoised = model(input)
```
Where:
- `input` is the pseudo-deblended common-receiver gather volume
- `target` is the cleaner forwarding-acoustic common-receiver gather volume
This is not a noise-label regression dataset.
## Dataset Description
- **Input variants currently included**:
- `T02_comp`: `input/T02_pseudo_deblended_common_receiver_comp.sgy`
- `T02_mod`: `input/T02_pseudo_deblended_common_receiver_mod.sgy`
- `T02_simp`: `input/T02_pseudo_deblended_common_receiver_simp.sgy`
- **Shared target file(s)**:
- `target/T02_forwarding_acoustic_common_receiver.sgy`
- **Geometry used by the benchmark**: `(386, 270, 2000)`
- **Interpretation**:
- 386 common-receiver gathers
- 270 traces per gather
- 2000 time samples per trace
- **Format**: paired SEG-Y volumes with matching sequential gather layout
## Preview Images
Clean Reference
Simple Blending Input
Moderate Blending Input
Hard Blending Input
## File Structure
| Kind | Path | Variant | Size |
|------|------|---------|------|
| input | `input/T02_pseudo_deblended_common_receiver_comp.sgy` | `T02_comp` | 819.0 MB |
| input | `input/T02_pseudo_deblended_common_receiver_mod.sgy` | `T02_mod` | 819.0 MB |
| input | `input/T02_pseudo_deblended_common_receiver_simp.sgy` | `T02_simp` | 819.0 MB |
| target | `target/T02_forwarding_acoustic_common_receiver.sgy` | shared | 819.0 MB |
## Loading Data
```python
import numpy as np
import segyio
def read_common_receiver_volume(path, traces_per_gather=270):
with segyio.open(path, "r", ignore_geometry=True) as src:
n_traces_total = src.tracecount
n_time = src.samples.size
n_gathers = n_traces_total // traces_per_gather
data = segyio.tools.collect(src.trace[:]).astype(np.float32, copy=False)
data = data.reshape(n_gathers, traces_per_gather, n_time)
return data
input_volume = read_common_receiver_volume(
"input/T02_pseudo_deblended_common_receiver_mod.sgy",
traces_per_gather=270,
)
target_volume = read_common_receiver_volume(
"target/T02_forwarding_acoustic_common_receiver.sgy",
traces_per_gather=270,
)
```
With `huggingface_hub`:
```python
from huggingface_hub import hf_hub_download
input_path = hf_hub_download(
repo_id="GeoBrain/deblending-common-receiver",
filename="input/T02_pseudo_deblended_common_receiver_mod.sgy",
repo_type="dataset",
)
```
## Benchmark Split
The current benchmark uses a sequential gather split:
| Split | Gathers |
|-------|---------|
| Train | 300 |
| Val | 43 |
| Test | 43 |
The split is applied on common-receiver gather index.
## Preprocessing Recipe
The companion benchmark currently applies:
1. shared `max_abs` normalization between input and target
2. per-gather normalization through the shared `shot` normalization scope
3. overlapping 2D trace-time patches
Current patch settings:
- `patch_trace: 128`
- `patch_time: 256`
- `patch_overlap: 0.5`
## Notes
- The benchmark uses common-receiver gathers, not common-shot gathers.
- Input and target must keep identical ordering and identical shape.
- The current benchmark reads these files by fixed sequential grouping with `270` traces per gather.
- Multiple pseudo-deblended input variants can share the same forwarding-acoustic target.
## Citation
If you use this dataset, cite the dataset repository:
```bibtex
@misc{deblending_common_receiver_dataset,
title={Deblending Common-Receiver Dataset},
howpublished={https://huggingface.co/datasets/GeoBrain/deblending-common-receiver},
}
```
## References
- `segyio` library: https://github.com/equinor/segyio