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README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+  - tabular-classification
+  - tabular-regression
+  - time-series-forecasting
+tags:
+  - seismic
+  - geophysics
+  - oil-and-gas
+  - exploration
+  - reservoir-engineering
+  - avo-analysis
+  - reservoir-characterization
+  - dhi
+  - subsurface
+  - synthetic-data
+pretty_name: OIL-001 — Synthetic Seismic Survey Dataset (Sample)
+size_categories:
+  - 10K<n<100K
+---
+
+# OIL-001 — Synthetic Seismic Survey Dataset (Sample)
+
+**XpertSystems.ai Synthetic Data Platform · SKU: OIL001-SAMPLE · Version 1.0.0**
+
+This is a **free preview** of the full **OIL-001 — Synthetic Seismic Survey
+Dataset** product. It contains roughly **~25% of the full dataset** at
+identical schema, physics modeling, and seismic interpretation features,
+so you can evaluate fit before licensing the full product.
+
+| File                          | Rows (sample) | Rows (full)   | Description                                  |
+|-------------------------------|---------------|---------------|----------------------------------------------|
+| `seismic_traces.csv`          | ~28,800      | ~100,000      | Per-trace amplitude + attributes (25 cols)   |
+| `horizon_catalog.csv`         | ~5,850        | ~30,000       | Interpreted horizons with rock physics (27 cols) |
+| `survey_geometry.csv`         | ~3            | ~6            | Per-survey geometry & acquisition (23 cols)  |
+| `interpretation_summary.csv`  | ~3            | ~6            | Per-survey interpretation KPIs (18 cols)     |
+
+## Dataset Summary
+
+OIL-001 is a **full seismic simulation engine** producing realistic 2D/3D
+seismic waveforms with subsurface structure interpretation labels — the kind
+of data exploration geophysicists, reservoir engineers, and seismic AI
+companies (Bluware, Earth Science Analytics, OspreyData, Geoteric) build
+their models on, but synthetic and free under CC-BY-NC for research.
+
+**Physics modeling**:
+
+- **Convolutional seismic model**: reflectivity series × wavelet (Ricker or
+  zero-phase)
+- **Aki-Richards approximation**: angle-dependent reflection coefficients
+  for AVO analysis
+- **Gassmann fluid substitution**: mineral/dry-frame/fluid moduli per layer
+- **Gardner's relation**: density from Vp by lithology
+- **NMO (Normal Moveout)**: velocity-based gather flattening for CDP stack
+- **Hilbert transform**: instantaneous amplitude, phase, frequency attributes
+- **Negative-pressure coherence**: fault-zone similarity attribute
+
+**Survey acquisition modeling**:
+
+- 3D land, 3D marine, 2D 2D-towed-streamer survey types
+- Configurable inline/crossline grid spacing
+- 9 offset panels (0°-40° in 5° steps) for AVO gathers
+- CDP fold, sample interval (2 ms = 500 Hz), 4-second TWT record length
+
+**Subsurface structure model** (8 structure labels):
+
+- Anticline crest / Anticline flank / Syncline
+- Fault plane / Fault shadow
+- Salt flank
+- Stratigraphic trap
+- Flat background
+
+**DHI (Direct Hydrocarbon Indicator) injection** (6 DHI labels):
+
+- No DHI (most traces)
+- Bright spot (amplitude anomaly indicating gas)
+- Dim spot (amplitude reduction indicating oil)
+- Flat spot (fluid contact reflection)
+- Polarity reversal (Class IIp AVO response)
+- AVO anomaly (Class III gas response)
+
+**8 lithology types**:
+
+sandstone (reservoir), shale (seal), limestone, dolomite, salt, anhydrite,
+volcanic, basement
+
+**5 fluid types** (with Gassmann fluid substitution):
+
+brine, oil, gas, gas_condensate, tight_dry
+
+**Seismic noise injection** (7 noise types):
+
+- Surface multiple reflections
+- Interbed multiple reflections
+- Ambient random noise
+- Source interference
+- Coupling variation
+- Statics anomaly
+- Clean (no noise)
+
+**Per-trace seismic attributes** (industry-standard interpretation features):
+
+- Raw and processed amplitudes
+- Instantaneous frequency, phase, amplitude (Hilbert transform)
+- Envelope (dB)
+- Coherence score (fault-zone similarity)
+- Curvature (k1 principal curvature)
+- AVO intercept and gradient (Aki-Richards)
+- Noise type and flag
+
+**Per-horizon rock physics**:
+
+- Vp, Vs, Vp/Vs ratio
+- Density (g/cc, Gardner-derived)
+- Acoustic impedance
+- Porosity %, water saturation %
+- Net pay, dip angle, dip azimuth
+
+**Prospect risking** (per-horizon):
+
+- PGOS (Probability of Geological Success) — typical industry 0.20-0.40
+- Trap closure area (km²)
+- Reservoir quality class
+- Fault association
+
+## Calibrated Validation Results
+
+Sample validation results across 10 seismic-domain KPIs:
+
+| Metric | Observed | Target | Source | Verdict |
+|--------|----------|--------|--------|---------|
+| n_surveys_represented | 3 | 3 | Sample survey count | ✓ PASS |
+| n_survey_types | 2 | 2 | 2D + 3D + 4D coverage | ✓ PASS |
+| n_basins_represented | 3 | 3 | Geographic diversity | ✓ PASS |
+| dominant_frequency_hz | 37.00 | 38.00 | Standard seismic dominant freq | ✓ PASS |
+| snr_db_mean | 21.03 | 22.00 | Industry SNR target (post-stack) | ✓ PASS |
+| horizon_pick_confidence | 0.861 | 0.880 | SEG interpreter confidence | ✓ PASS |
+| horizon_continuity_index | 0.868 | 0.830 | Lateral continuity benchmark | ✓ PASS |
+| fault_detection_confidence | 0.813 | 0.790 | Coherence-based fault picking | ✓ PASS |
+| sandstone_porosity_pct_mean | 16.93 | 17.50 | Industry sandstone reservoir φ | ✓ PASS |
+| n_horizon_labels_represented | 8 | 3 | Multi-class horizon diversity | ✓ PASS |
+
+*Note: This dataset is designed for **seismic interpretation AI training** —
+buyers building horizon-picking auto-trackers, fault-detection neural
+networks, DHI classification models, or AVO inversion solvers can use these
+labels for supervised training. The full product includes 6 surveys with
+larger 3D grids and full structural diversity.*
+
+## Schema Highlights
+
+### `seismic_traces.csv` (primary file, 25 columns)
+
+**Trace identification & geometry**:
+
+| Column                | Type   | Description                                  |
+|-----------------------|--------|----------------------------------------------|
+| survey_id, gather_id  | int    | Survey and CDP gather IDs                    |
+| cdp_x, cdp_y          | float  | CDP location (meters)                        |
+| cdp_inline, cdp_crossline | int | 3D grid coordinates                        |
+| offset_m              | float  | Source-receiver offset (m)                   |
+| two_way_time_ms       | float  | Two-way time (ms)                            |
+
+**Amplitudes & attributes**:
+
+| Column                       | Type    | Description                              |
+|------------------------------|---------|------------------------------------------|
+| amplitude_raw                | float   | Pre-processing amplitude                 |
+| amplitude_processed          | float   | After deconv + statics + multiples       |
+| frequency_hz                 | float   | Instantaneous frequency                  |
+| instantaneous_phase_deg      | float   | Hilbert phase (degrees)                  |
+| instantaneous_amplitude      | float   | Hilbert envelope                         |
+| envelope_db                  | float   | Envelope in dB                           |
+| coherence_score              | float   | Coherence (0-1, fault zones low)         |
+| curvature_k1                 | float   | Principal curvature                      |
+| avo_intercept, avo_gradient  | float   | Aki-Richards AVO A, B                    |
+
+**Labels**:
+
+| Column                  | Type    | Description                                  |
+|-------------------------|---------|----------------------------------------------|
+| horizon_label           | string  | 8 horizon labels (basement, reservoir, etc.) |
+| structure_label         | string  | 8 structure labels (anticline, fault, salt)  |
+| dhi_label               | string  | 6 DHI labels                                 |
+| noise_flag, noise_type  | string  | Noise contamination flag                     |
+| fault_proximity_m       | float   | Distance to nearest fault                    |
+| reservoir_quality_flag  | string  | Reservoir quality class                      |
+
+### `horizon_catalog.csv` (27 columns)
+
+Per-horizon rock physics + structural interpretation:
+
+| Column                       | Description                                  |
+|------------------------------|----------------------------------------------|
+| horizon_name, horizon_label  | Named horizon + 8-class label                |
+| two_way_time_ms, depth_m     | TWT and depth                                |
+| dip_angle_deg, dip_azimuth   | Structural dip                               |
+| interval_velocity_ms         | Interval Vp (m/s)                            |
+| acoustic_impedance_mpa       | Acoustic impedance                           |
+| vp_ms, vs_ms                 | Vp, Vs (m/s)                                 |
+| density_gcc                  | Density (g/cc, Gardner)                      |
+| porosity_pct                 | Porosity (%)                                 |
+| water_saturation_pct         | Water saturation (%)                         |
+| lithology_type               | 8 lithology classes                          |
+| fluid_type                   | 5 fluid types                                |
+| trap_style                   | Trap classification                          |
+| dhi_class, dhi_label         | DHI class + 6-class label                    |
+| reservoir_quality_class      | Reservoir quality                            |
+| net_pay_m                    | Net pay thickness                            |
+| fault_id                     | Associated fault                             |
+| prospect_pgos                | Probability of Geological Success            |
+
+### `survey_geometry.csv` (23 columns)
+
+Per-survey acquisition geometry: survey_type, basin_name, n_inlines,
+n_crosslines, cdp_spacing, fold, source_type, water_depth, acquisition
+environment, processing vintage, migration type, SNR, dominant frequency.
+
+### `interpretation_summary.csv` (18 columns)
+
+Per-survey interpretation KPIs: horizon_pick_confidence, fault_confidence,
+horizon_continuity_index, multiple_contamination_pct, etc.
+
+## Suggested Use Cases
+
+- **Auto horizon picking** — train CNNs to follow horizons across 3D
+- **Fault detection** — train coherence/curvature-based fault networks
+- **DHI classification** — 6-class hydrocarbon indicator prediction
+- **AVO inversion** — predict elastic properties from intercept/gradient
+- **Salt body segmentation** — geometric salt detection
+- **Structural label segmentation** — 8-class structural interpretation
+- **Lithology prediction** — 8-class lithology from seismic attributes
+- **Fluid type prediction** (with Gassmann substitution targets)
+- **Reservoir quality scoring** from acoustic impedance and porosity
+- **Multiple suppression** — deep-learning-based denoise training
+- **Statics correction** — anomaly detection at trace level
+- **Wavelet estimation & deconvolution** — Ricker/zero-phase fitting
+- **Velocity model building** — interval velocity prediction from traces
+- **Time-to-depth conversion** — TWT-depth modeling
+- **Prospect screening** — PGOS prediction from seismic features
+- **Trap closure area estimation** from structural attributes
+- **Insurtech-style geophysical AI training** without proprietary survey data
+- **University geophysics curriculum** — synthetic teaching corpus
+
+## Loading the Data
+
+```python
+import pandas as pd
+
+traces   = pd.read_csv("seismic_traces.csv")
+horizons = pd.read_csv("horizon_catalog.csv")
+geometry = pd.read_csv("survey_geometry.csv")
+interp   = pd.read_csv("interpretation_summary.csv")
+
+# Multi-class horizon label target (8 classes)
+y_horizon = traces["horizon_label"]
+
+# Multi-class structural interpretation target (8 classes)
+y_structure = traces["structure_label"]
+
+# Multi-class DHI prediction target (6 classes)
+y_dhi = traces["dhi_label"]
+
+# Binary noise contamination
+y_noise = traces["noise_flag"]
+
+# Regression: AVO inversion targets
+y_avo_a = traces["avo_intercept"]
+y_avo_b = traces["avo_gradient"]
+
+# Multi-class lithology from horizon (8 classes)
+y_lithology = horizons["lithology_type"]
+
+# Multi-class fluid type from horizon (5 classes)
+y_fluid = horizons["fluid_type"]
+
+# Regression: reservoir porosity
+y_porosity = horizons["porosity_pct"]
+
+# Regression: PGOS prospect risking
+y_pgos = horizons["prospect_pgos"]
+
+# Build 3D seismic cube for ML
+cube = traces.pivot_table(
+    index=["cdp_inline", "cdp_crossline"],
+    columns="two_way_time_ms",
+    values="amplitude_processed",
+    aggfunc="mean"
+)
+```
+
+## License
+
+This **sample** is released under **CC-BY-NC-4.0** (free for non-commercial
+research and evaluation). The **full production dataset** is licensed
+commercially — contact XpertSystems.ai for licensing terms.
+
+## Full Product
+
+The full OIL-001 dataset includes **6 surveys** with **120×80 3D grids**
+each, full structural diversity (anticlines, synclines, salt diapirs,
+stratigraphic traps), 14-layer velocity models with Gassmann substitution,
+and full DHI/AVO anomaly catalogs. Calibrated to SEG seismic interpretation
+standards, Aki-Richards AVO theory, and Gassmann fluid substitution theory.
+
+📧  **pradeep@xpertsystems.ai**
+🌐  **https://xpertsystems.ai**
+
+## Citation
+
+```bibtex
+@dataset{xpertsystems_oil001_sample_2026,
+  title  = {OIL-001: Synthetic Seismic Survey Dataset (Sample)},
+  author = {XpertSystems.ai},
+  year   = {2026},
+  url    = {https://huggingface.co/datasets/xpertsystems/oil001-sample}
+}
+```
+
+## Generation Details
+
+- Generator version : 1.0.0
+- Random seed       : 42
+- Generated         : 2026-05-16 22:41:59 UTC
+- Surveys           : 3 × (40 inlines × 30 crosslines × 9 offsets × 14 layers)
+- Wavelet           : Ricker, 38 Hz dominant
+- Physics           : Aki-Richards AVO + Gassmann + Gardner + Hilbert
+- Calibration basis : SEG seismic interpretation standards
+- Overall validation: 100.0 / 100  (grade A+)

interpretation_summary.csv

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+survey_id,basin_name,n_horizons_mapped,n_faults_mapped,n_prospects_identified,n_dhi_anomalies,avg_snr_db,avg_coherence_score,horizon_pick_confidence,fault_confidence,dhi_confidence,reservoir_net_pay_mean_m,porosity_mean_pct,water_saturation_mean_pct,trap_closure_km2,prospect_risked_pgos,multiple_contamination_pct,processing_quality_grade
+1,Tarim Basin,8,12,0,0,-20.0,0.5162,0.868,0.8019,0.7399,24.75,11.586,40.25,40.07,0.1811,0.2107,A
+2,Permian Basin,8,12,0,0,-20.0,0.4166,0.8421,0.8317,0.708,48.71,10.454,29.52,48.76,0.1811,0.1889,A
+3,Browse Basin,8,12,881,7048,-20.0,0.4146,0.8738,0.8048,0.5771,38.12,11.778,72.86,54.43,0.1848,0.2279,A

survey_geometry.csv

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+survey_id,survey_type,basin_name,n_inlines,n_crosslines,n_cdp,cdp_spacing_m,receiver_spacing_m,shot_spacing_m,max_offset_m,min_offset_m,fold_nominal,record_length_ms,sample_interval_ms,dominant_frequency_hz,wavelet_type,source_type,water_depth_m,acquisition_environment,processing_vintage,migration_type,snr_db,vintage_year
+1,3d_marine,Tarim Basin,40,30,1200,12.5,25.0,50.0,2512.4545307021835,235.11578136867013,170,4000,2,34.1,klauder,airgun,2153.6,onshore_arctic,1993,depth_migration_rtm,22.32,1993
+2,3d_land,Permian Basin,40,30,1200,12.5,25.0,50.0,2255.269024416701,348.2893515977746,137,4000,2,39.4,zero_phase,dynamite,0.0,transition_zone,2017,depth_migration_rtm,19.85,2017
+3,3d_land,Browse Basin,40,30,1200,12.5,25.0,50.0,3866.884014908137,113.14112973616864,87,4000,2,37.5,ricker,dynamite,0.0,deep_marine,2023,depth_migration_kirchhoff,20.93,2023