| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - tabular-classification |
| - tabular-regression |
| - time-series-forecasting |
| language: |
| - en |
| tags: |
| - tsfile |
| - timeseries |
| - synthetic |
| - oil-and-gas |
| - upstream |
| - iot |
| - rig-telemetry |
| - predictive-maintenance |
| - condition-monitoring |
| - remaining-useful-life |
| - sensor-fusion |
| - anomaly-detection |
| - xpertsystems |
| - time-series |
| - format:tsfile |
| pretty_name: OIL-012 — Synthetic Rig Sensor IoT Dataset (Sample) (TsFile) |
| size_categories: |
| - 100K<n<1M |
| configs: |
| - config_name: default |
| data_files: |
| - split: alarm_events |
| path: alarm_events.tsfile |
| - split: drilling_parameters |
| path: drilling_parameters.tsfile |
| - split: environmental_conditions |
| path: environmental_conditions.tsfile |
| - split: hydraulic_systems |
| path: hydraulic_systems.tsfile |
| - split: maintenance_records |
| path: maintenance_records.tsfile |
| - split: power_systems |
| path: power_systems.tsfile |
| - split: rigs_master |
| path: rigs_master.tsfile |
| - split: rul_labels |
| path: rul_labels.tsfile |
| - split: sensor_fusion_features |
| path: sensor_fusion_features.tsfile |
| - split: sensor_health |
| path: sensor_health.tsfile |
| - split: sensors_master |
| path: sensors_master.tsfile |
| - split: telemetry_streams |
| path: telemetry_streams.tsfile |
| - split: thermal_monitoring |
| path: thermal_monitoring.tsfile |
| - split: vibration_analysis |
| path: vibration_analysis.tsfile |
| --- |
| |
| # OIL-012 — Synthetic Rig Sensor IoT Dataset (Sample) (TsFile) |
|
|
| Apache TsFile version of [`xpertsystems/oil012-sample`](https://huggingface.co/datasets/xpertsystems/oil012-sample). |
|
|
| ## Overview |
|
|
| A free, schema-identical preview of XpertSystems.ai's enterprise drilling rig IoT telemetry dataset for predictive-maintenance ML, condition-monitoring ML, sensor-fusion modeling, and remaining-useful-life forecasting. The sample covers **30 rigs** across **10 global basins** and **8 rig types**, with **134,622 rows** including **94,745 sparse-format telemetry events** linked across **15 tables**. |
|
|
| - **Tables:** 14 TsFile table(s), 134,622 rows in total. |
| - `alarm_events`: 278 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.002000 (UTC) |
| - `drilling_parameters`: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC) |
| - `environmental_conditions`: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC) |
| - `hydraulic_systems`: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC) |
| - `maintenance_records`: 29 rows, 2026-01-01 00:10:00 → 2026-01-01 14:40:00 (UTC) |
| - `power_systems`: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC) |
| - `rigs_master`: 30 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.029000 (UTC) |
| - `rul_labels`: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC) |
| - `sensor_fusion_features`: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC) |
| - `sensor_health`: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC) |
| - `sensors_master`: 660 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.659000 (UTC) |
| - `telemetry_streams`: 94,745 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.656000 (UTC) |
| - `thermal_monitoring`: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC) |
| - `vibration_analysis`: 4,320 rows, 2026-01-01 00:00:00 → 2026-01-01 23:50:00.029000 (UTC) |
|
|
| ## Schema (TsFile structure) |
|
|
| ### `alarm_events.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (8): `alarm_id` (string), `rig_id` (string), `alarm_code` (string), `severity` (string), `subsystem` (string), `duration_sec` (int64), `anomaly_score` (double), `acknowledged_flag` (int64) |
|
|
| ### `drilling_parameters.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (11): `event_id` (string), `rig_id` (string), `operating_state` (string), `wob_klbs` (double), `torque_ftlb` (double), `rpm` (double), `rop_ft_hr` (double), `standpipe_pressure_psi` (double), `flow_rate_gpm` (double), `hook_load_klbs` (double), `stick_slip_index` (double) |
|
|
| ### `environmental_conditions.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (6): `rig_id` (string), `ambient_temp_f` (double), `humidity_pct` (double), `wind_speed_mph` (double), `environmental_stress_index` (double), `weather_impact_factor` (double) |
|
|
| ### `hydraulic_systems.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (6): `rig_id` (string), `pump_pressure_psi` (double), `hydraulic_pressure_psi` (double), `hydraulic_temp_f` (double), `flow_rate_gpm` (double), `cavitation_risk_score` (double) |
|
|
| ### `maintenance_records.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (9): `maintenance_id` (string), `rig_id` (string), `component_id` (string), `maintenance_type` (string), `subsystem` (string), `failure_mode` (string), `labor_hours` (double), `repair_cost_usd` (double), `post_maintenance_health_index` (double) |
|
|
| ### `power_systems.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (6): `rig_id` (string), `voltage` (double), `amperage` (double), `motor_current` (double), `load_pct` (double), `current_harmonic_distortion` (double) |
|
|
| ### `rigs_master.tsfile` |
| |
| - **Time** (INT64, milliseconds) — synthetic row index over the stable source order; this table has no clock column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (13): `rig_id` (string), `rig_type` (string), `operator_name` (string), `basin_name` (string), `country_region` (string), `rig_age_years` (double), `automation_level` (double), `offshore_flag` (int64), `hthp_flag` (int64), `environmental_stress_index` (double), `base_health_index` (double), `daily_operating_hours` (double), `commissioned_year` (int64) |
|
|
| ### `rul_labels.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (6): `rig_id` (string), `component_id` (string), `remaining_useful_life_hr` (double), `failure_probability` (double), `failure_horizon_days` (int64), `subsystem_health_score` (double) |
|
|
| ### `sensor_fusion_features.tsfile` |
|
|
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (6): `rig_id` (string), `fusion_vector_id` (string), `anomaly_score` (double), `health_index` (double), `sensor_fusion_consistency` (double), `maintenance_priority_score` (double) |
|
|
| ### `sensor_health.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (5): `rig_id` (string), `calibration_score` (double), `sensor_drift_pct` (double), `packet_loss_pct` (double), `edge_latency_ms` (double) |
|
|
| ### `sensors_master.tsfile` |
| |
| - **Time** (INT64, milliseconds) — synthetic row index over the stable source order; this table has no clock column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (9): `sensor_id` (string), `rig_id` (string), `sensor_type` (string), `subsystem` (string), `unit` (string), `sensor_age_years` (double), `sampling_profile` (string), `calibration_score` (double), `edge_device_id` (string) |
|
|
| ### `telemetry_streams.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (8): `rig_id` (string), `sensor_id` (string), `sensor_type` (string), `subsystem` (string), `unit` (string), `sensor_value` (double), `quality_flag` (string), `operating_state` (string) |
|
|
| ### `thermal_monitoring.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (5): `rig_id` (string), `component_temp_f` (double), `bearing_temp_f` (double), `thermal_gradient` (double), `thermal_stress_index` (double) |
|
|
| ### `vibration_analysis.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `event_ts` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (7): `rig_id` (string), `vibration_rms` (double), `axial_vibration` (double), `torsional_vibration` (double), `harmonic_index` (double), `stick_slip_index` (double), `shock_event_flag` (int64) |
|
|
| ## Conversion notes |
|
|
| - One TsFile per source CSV (14 tables) for this drilling-rig telemetry sample; each table is stored as a single device, so the rig/well/tank/sensor ids stay ordinary FIELDs. |
| - Time = the table's own timestamp column as INT64 milliseconds (event timestamps, daily record/production dates, or test dates). Master/inventory tables that carry no clock (`rigs_master`, `sensors_master`, `wells_master`, `tank_master`, the label tables and `scada_telemetry`) use a synthetic row index as Time. |
| - No column is dropped. Rows that share a timestamp are ordered by a 1 ms step in stable source order; daily tables keep their exact calendar day. |
| - Not converted: `equipment_failures.csv` — the file ships with a header only and zero data rows. |
|
|
| ## Usage |
|
|
| Install the Apache TsFile Python SDK (`pip install tsfile`) and read a converted file: |
|
|
| ```python |
| from pathlib import Path |
| from tsfile import TsFileReader |
| |
| path = Path("alarm_events.tsfile") |
| with TsFileReader(str(path)) as reader: |
| schemas = reader.get_all_table_schemas() |
| print("tables:", list(schemas)) |
| table_name = next(iter(schemas)) |
| table = schemas[table_name] |
| columns = [column.get_column_name() for column in table.get_columns()] |
| print("columns:", columns) |
| field_names = [ |
| column.get_column_name() |
| for column in table.get_columns() |
| if column.get_column_name() not in {"Time", "time"} |
| ] |
| if field_names: |
| with reader.query_table(table_name, field_names[:3], batch_size=1024) as result: |
| batch = result.read_arrow_batch() |
| if batch is not None: |
| print(batch.to_pandas().head()) |
| ``` |
|
|
| ## Source & license |
|
|
| - Original dataset: [`xpertsystems/oil012-sample`](https://huggingface.co/datasets/xpertsystems/oil012-sample) |
| - Source card title / publisher: OIL-012 — Synthetic Rig Sensor IoT Dataset (Sample) |
| - License: cc-by-nc-4.0 (as declared by the original dataset). |
|
|
