--- 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

clean reference

Simple Blending Input

simple blending input

Moderate Blending Input

moderate blending input

Hard 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