Initial release: OIL-007 sample, 100 wells / 110K timeseries rows, Grade A+ (10/10)
1ca9dc8 verified | license: cc-by-nc-4.0 | |
| task_categories: | |
| - tabular-classification | |
| - tabular-regression | |
| - time-series-forecasting | |
| language: | |
| - en | |
| tags: | |
| - synthetic | |
| - oil-and-gas | |
| - upstream | |
| - drilling | |
| - drilling-parameters | |
| - mwd | |
| - lwd | |
| - rop-optimization | |
| - mse | |
| - bit-wear | |
| - drilling-dysfunctions | |
| - xpertsystems | |
| pretty_name: "OIL-007 — Synthetic Drilling Parameters Dataset (Sample)" | |
| size_categories: | |
| - 100K<n<1M | |
| # OIL-007 — Synthetic Drilling Parameters Dataset (Sample) | |
| **SKU:** `OIL007-SAMPLE` · **Vertical:** Oil & Gas / Upstream Drilling Operations | |
| **License:** CC-BY-NC-4.0 (sample) · **Schema version:** `oil007.v1` | |
| **Generator version:** `1.0.0` · **Default seed:** `42` | |
| A free, schema-identical preview of XpertSystems.ai's enterprise drilling- | |
| parameters dataset for ROP optimization, MSE analysis, dysfunction detection, | |
| and drilling-process ML. The sample covers **100 wells** across | |
| **11 global basins** and **12 well types** with | |
| **220,871 rows** of high-cadence drilling telemetry linked across | |
| **9 tables**. | |
| --- | |
| ## What's in the box | |
| | File | Rows | Cols | Description | | |
| |---|---:|---:|---| | |
| | `wells_master.csv` | 100 | 13 | Well spine: type, basin, trajectory, rig, mud system, casing | | |
| | `drilling_timeseries.csv` | 109,870 | 10 | High-cadence per-stand ROP / WOB / torque / RPM / SPP / hook load | | |
| | `mud_properties.csv` | 21,974 | 10 | Mud weight, PV, YP, ECD, gels, mud temp | | |
| | `hydraulics_log.csv` | 21,974 | 9 | Flow, pump pressure, annular pressure, annular velocity, bit HHP | | |
| | `vibration_spectra.csv` | 54,935 | 8 | Axial / lateral / torsional g's, stick-slip index, whirl index | | |
| | `mse_log.csv` | 10,987 | 6 | Per-stand MSE (Teale formulation), bit efficiency, formation UCS | | |
| | `bit_wear_log.csv` | 344 | 9 | IADC dull grades, footage, bit size/type (PDC/RC/hybrid) | | |
| | `drilling_events.csv` | 587 | 7 | 11-class dysfunction events (stick-slip, stuck pipe, washout, mud loss, etc.) | | |
| | `drilling_labels.csv` | 100 | 6 | ML labels: optimal ROP, dysfunction risk, MSE efficiency, drilling grade | | |
| Total: **220,871 rows** across 9 CSVs, ~14.0 MB on disk. | |
| --- | |
| ## Calibration: industry-anchored, honestly reported | |
| Validation uses a **10-metric scorecard** with targets sourced exclusively to | |
| **named industry standards**: SPE 178850, SPE 96652 (Dupriest & Koederitz), | |
| Teale (1965) MSE foundational paper, API RP-7G (drill stem design), API | |
| RP-13B-1 (drilling fluids), IADC Drilling Manual, IADC dull grading, | |
| Bourgoyne et al. (1986) Applied Drilling Engineering, Rystad Energy global | |
| rig fleet, and Spears & Associates bit market reports. | |
| **Sample run** (seed `42`, n_wells=100): | |
| | # | Metric | Observed | Target | Tolerance | Status | Source | | |
| |---|---|---:|---:|---:|---|---| | |
| | 1 | avg rop ft hr | 83.8562 | 85.0 | ±25.0 | ✓ PASS | SPE 178850 + Rystad Energy — global mean ROP across mixed onshore/offshore land/platform portfolio | | |
| | 2 | avg wob klbs | 33.7322 | 32.0 | ±8.0 | ✓ PASS | API RP-7G + SPE Drilling Handbook — global mean WOB across PDC/RC mixed bit portfolio | | |
| | 3 | avg surface torque klbft | 13.7738 | 14.5 | ±4.0 | ✓ PASS | API RP-7G + SPE Drilling Engineering — global mean surface torque across mixed trajectory portfolio | | |
| | 4 | avg mud weight ppg | 11.4375 | 11.2 | ±1.5 | ✓ PASS | API RP-13B-1 + SPE drilling fluids literature — global mean mud weight across conventional/HPHT/deepwater mix | | |
| | 5 | ecd margin ppg | 0.3709 | 0.45 | ±0.15 | ✓ PASS | SPE 178850 + IADC Drilling Manual — ECD margin (ecd minus static MW) maintained during circulation | | |
| | 6 | avg mse psi | 37376.3374 | 38000.0 | ±9000.0 | ✓ PASS | Teale (1965) + SPE 96652 (Dupriest & Koederitz) — global mean MSE across mixed-formation drilling portfolio | | |
| | 7 | pv yp correlation | 0.7833 | 0.78 | ±0.15 | ✓ PASS | API RP-13B-1 + Bourgoyne et al. (1986) — plastic viscosity / yield point shared-rheology correlation in field-mixed mud systems (typically 0.70-0.85) | | |
| | 8 | pdc bit share | 0.7384 | 0.72 | ±0.1 | ✓ PASS | Spears & Associates + IADC bit market reports — global PDC bit share in modern drilling (2020-2024) | | |
| | 9 | mse ucs correlation | 0.7453 | 0.65 | ±0.2 | ✓ PASS | Teale (1965) + Dupriest (2005) SPE — MSE per-well average correlated with formation UCS; physics: MSE bounds approach UCS at perfect bit efficiency | | |
| | 10 | well type diversity entropy | 0.8279 | 0.85 | ±0.15 | ✓ PASS | Rystad Energy global rig fleet + IADC drilling activity tracker — 12-class well-type diversity benchmark (conventional, HPHT, deepwater, ERD, multilateral, etc.), normalized Shannon entropy | | |
| **Overall: 100.0/100 — Grade A+** | |
| (10 PASS · 0 MARGINAL · 0 FAIL of 10 metrics) | |
| --- | |
| ## Schema highlights | |
| **`wells_master.csv`** — one row per well, the relational spine. | |
| Key columns: `well_id`, `well_type` (12-class: vertical_conventional, | |
| directional, horizontal_shale, extended_reach, deepwater_offshore, hpht, | |
| geothermal, managed_pressure, underbalanced, salt_section, multilateral, | |
| slim_hole), `basin` (11-class: Permian, Eagle Ford, Bakken, Marcellus-Utica, | |
| Gulf of Mexico, North Sea, Middle East, Brazil Pre-Salt, Canada Oil Sands, | |
| Geothermal Basins, Other), `total_depth_ft`, `well_trajectory_type`, | |
| `mud_system` (water/oil/synthetic/cesium formate). | |
| **MSE follows the Teale (1965) formulation** with bit-size-aware area: | |
| > MSE = (WOB / A_bit) + (120·π·RPM·T_bit) / (A_bit · ROP) | |
| where `A_bit` varies by hole section (17.5" surface, 12.25" intermediate, | |
| 8.5" production, 6.125" lateral), and `T_bit` is downhole bit torque | |
| estimated as 25-45% of surface torque depending on trajectory and depth — | |
| a critical detail for accurate MSE in long-reach and horizontal wells. | |
| **Formation strength profiles** (`mse_log.formation_strength_psi`) follow | |
| basin-specific UCS bands with stochastic formation transitions every | |
| 500-2000 ft: Permian 8-22 kpsi, Marcellus-Utica 11-25 kpsi, Brazil Pre-Salt | |
| 15-35 kpsi, Geothermal Basins 18-40 kpsi. | |
| **Rheology coupling** — PV and YP share an underlying rheology level | |
| correlated with mud weight, producing the field-realistic PV-YP correlation | |
| of ~0.70-0.85 (Bourgoyne et al. 1986). | |
| **ECD margin** (`ecd_ppg - mud_weight_ppg`) is calibrated to maintain the | |
| ~0.45 ppg overpressure circulation envelope per IADC guidance, with | |
| depth-scaled annular friction and ROP-dependent cuttings loading. | |
| **Bit wear** uses the **IADC dull grading taxonomy** (8 codes spanning | |
| worn-teeth, broken-teeth, lost-teeth, ring-out, balled-up patterns), with | |
| dull grade escalation driven by cumulative footage and average formation | |
| strength per bit run. | |
| --- | |
| ## Suggested use cases | |
| 1. **ROP optimization regression** — predict ROP from WOB, RPM, torque, | |
| mud weight, formation UCS using the 109,870-row time-series spine. | |
| 2. **MSE efficiency classification** — train models on `bit_efficiency` | |
| to identify low-energy-efficient drilling sections. | |
| 3. **Dysfunction detection** — multi-class classifier on `dysfunction_class` | |
| (11-class: stick-slip, lateral vibration, stuck pipe, washout, twist-off, | |
| mud loss/gain, bit balling, pack-off, whirl, axial bounce) from vibration | |
| + mechanical telemetry. | |
| 4. **Stuck pipe early warning** — binary classification with the | |
| `stuck_pipe_precursor` events as positive labels, ROP/WOB/torque time- | |
| series as features. | |
| 5. **Bit dull grade prediction** — regress IADC dull grade from cumulative | |
| footage and formation strength exposure per bit run. | |
| 6. **Drilling efficiency grading** — multi-class classification on the | |
| `drilling_efficiency_grade` (A+/A/B/C/D) target from per-well aggregated | |
| features. | |
| 7. **Time-series forecasting** — predict next-stand ROP / MSE / vibration | |
| from the prior stand's drilling parameters (sequence models, transformers). | |
| 8. **Multi-table relational ML** — entity-resolution and graph-based | |
| learning across the 9 joinable tables via `well_id`. | |
| --- | |
| ## Loading | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("xpertsystems/oil007-sample", data_files="drilling_timeseries.csv") | |
| print(ds["train"][0]) | |
| ``` | |
| Or with pandas: | |
| ```python | |
| import pandas as pd | |
| wells = pd.read_csv("hf://datasets/xpertsystems/oil007-sample/wells_master.csv") | |
| ts = pd.read_csv("hf://datasets/xpertsystems/oil007-sample/drilling_timeseries.csv") | |
| mse = pd.read_csv("hf://datasets/xpertsystems/oil007-sample/mse_log.csv") | |
| events = pd.read_csv("hf://datasets/xpertsystems/oil007-sample/drilling_events.csv") | |
| joined = ts.merge(wells, on="well_id") | |
| ``` | |
| --- | |
| ## Reproducibility | |
| All generation is deterministic via the integer `seed` parameter through | |
| per-well `SeedSequence([master_seed, well_idx])` derivation, guaranteeing | |
| schema-stable joins across runs and seed-by-seed reproducibility. | |
| A seed sweep across `[42, 7, 123, 2024, 99, 1]` confirms Grade A+ on every | |
| seed in this sample. | |
| --- | |
| ## Honest disclosure of sample-scale limitations | |
| This is a **sample** product calibrated for ML prototyping and drilling- | |
| parameter research, not for live drilling operations. A few notes: | |
| 1. **Time-series is decimated 4× in the sample.** Full product runs at the | |
| generator's native cadence (~42 samples per stand at 1 Hz / 85 ft/hr). | |
| The sample uses `--decimate 4` to keep file sizes <15 MB while | |
| preserving stand-resolution detail. For high-frequency vibration ML, | |
| use the full product (12,000 wells, undecimated). | |
| 2. **ECD margin runs slightly below the 0.45 ppg target** (observed mean | |
| ~0.37 ppg) at sample scale, well within the ±0.15 ppg tolerance. This | |
| reflects the stochastic depth-scaled annular friction modeling; full- | |
| product scale converges closer to 0.45 ppg as the basin/well-type mix | |
| averages out. | |
| 3. **Max depth capped at 12,000 ft in the sample** (vs 22,000 ft in the | |
| full product). This caps the Pre-Salt and HPHT extreme-depth physics | |
| slightly under-represented. Wells assigned to those types still get | |
| their depth/mud-weight modifiers applied within the 12 kft envelope. | |
| 4. **Inter-stand jitter uses per-stand-seeded RNG** for intra-stand sample | |
| variation. This produces stand-coherent telemetry (good for ML) but | |
| means within-stand noise is correlated stand-to-stand at fixed offsets. | |
| For pure-noise modeling, filter out the per-stand structure first. | |
| 5. **Per-well stuck pipe / washout / dysfunction event rates are | |
| per-stand Bernoulli probabilities**, so total event counts per well | |
| are Poisson-distributed (~6 events/well average at sample scale). | |
| Production runs (longer wells, more stands) will see proportionally | |
| more events per well. | |
| --- | |
| ## Full product | |
| The **full OIL-007 dataset** ships at **12,000 wells**, **22,000 ft max | |
| depth**, undecimated 1Hz timeseries, full 12-class well-type coverage with | |
| HPHT and Pre-Salt extreme-depth physics, and full per-stand dysfunction | |
| event modeling — licensed commercially. Contact XpertSystems.ai for | |
| licensing terms. | |
| 📧 **pradeep@xpertsystems.ai** | |
| 🌐 **https://xpertsystems.ai** | |
| --- | |
| ## Citation | |
| ```bibtex | |
| @dataset{xpertsystems_oil007_sample_2026, | |
| title = {OIL-007: Synthetic Drilling Parameters Dataset (Sample)}, | |
| author = {XpertSystems.ai}, | |
| year = {2026}, | |
| url = {https://huggingface.co/datasets/xpertsystems/oil007-sample} | |
| } | |
| ``` | |
| ## Generation details | |
| - Generator version : 1.0.0 | |
| - Sample version : 1.0.0 | |
| - Random seed : 42 | |
| - Generated : 2026-05-21 22:54:12 UTC | |
| - Wells : 100 | |
| - Max depth : 12,000 ft (capped for sample; full product: 22,000 ft) | |
| - Timeseries decim. : 4× (sample); full product: 1× native | |
| - Basins : 11 (Permian, Eagle Ford, Bakken, Marcellus-Utica, | |
| Gulf of Mexico, North Sea, Middle East, Brazil Pre-Salt, | |
| Canada Oil Sands, Geothermal Basins, Other) | |
| - Well types : 12 (vertical, directional, horizontal_shale, | |
| extended_reach, deepwater, HPHT, geothermal, | |
| managed_pressure, underbalanced, salt_section, | |
| multilateral, slim_hole) | |
| - Calibration basis : SPE 178850, SPE 96652, Teale (1965), API RP-7G, | |
| API RP-13B-1, IADC Drilling Manual, IADC dull grading, | |
| Bourgoyne et al. (1986), Rystad Energy, Spears & Associates | |
| - Overall validation: 100.0/100 — Grade A+ | |