| --- |
| 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 |
| - decline-curve-analysis |
| - arps-decline |
| - production-forecasting |
| - eur-estimation |
| - reserve-classification |
| - spe-prms |
| - xpertsystems |
| - time-series |
| - format:tsfile |
| pretty_name: OIL-016 — Synthetic Well Decline Curve Dataset (Sample) (TsFile) |
| size_categories: |
| - 100K<n<1M |
| configs: |
| - config_name: default |
| data_files: |
| - split: artificial_lift_events |
| path: artificial_lift_events.tsfile |
| - split: decline_parameters |
| path: decline_parameters.tsfile |
| - split: eur_forecasts |
| path: eur_forecasts.tsfile |
| - split: pressure_depletion |
| path: pressure_depletion.tsfile |
| - split: production_interruptions |
| path: production_interruptions.tsfile |
| - split: production_timeseries |
| path: production_timeseries.tsfile |
| - split: wells_master |
| path: wells_master.tsfile |
| --- |
| |
| # OIL-016 — Synthetic Well Decline Curve Dataset (Sample) (TsFile) |
|
|
| Apache TsFile version of [`xpertsystems/oil016-sample`](https://huggingface.co/datasets/xpertsystems/oil016-sample). |
|
|
| ## Overview |
|
|
| A free, schema-identical preview of XpertSystems.ai's enterprise well decline- curve dataset for Arps DCA ML, EUR forecasting, reserve classification, and long-horizon production analytics. The sample covers **500 wells** across **6 global basins**, simulated over **360 months (30 years)**, with **361,809 rows** including **180,000 monthly production records** linked across **7 tables**. |
|
|
| - **Tables:** 7 TsFile table(s), 361,809 rows in total. |
| - `artificial_lift_events`: 213 rows, 2010-09-22 00:00:00 → 2027-03-27 00:00:00 (UTC) |
| - `decline_parameters`: 500 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.499000 (UTC) |
| - `eur_forecasts`: 500 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.499000 (UTC) |
| - `pressure_depletion`: 180,000 rows, 2010-01-04 00:00:00 → 2053-08-09 00:00:00 (UTC) |
| - `production_interruptions`: 96 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.095000 (UTC) |
| - `production_timeseries`: 180,000 rows, 2010-01-04 00:00:00 → 2053-08-09 00:00:00 (UTC) |
| - `wells_master`: 500 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.499000 (UTC) |
|
|
| ## Schema (TsFile structure) |
|
|
| ### `artificial_lift_events.tsfile` |
|
|
| - **Time** (INT64, milliseconds) — the source `install_date` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (3): `well_id` (string), `lift_type` (string), `efficiency_factor` (double) |
|
|
| ### `decline_parameters.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** (5): `well_id` (string), `decline_model` (string), `qi_bpd` (double), `di` (double), `b_factor` (double) |
| |
| ### `eur_forecasts.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** (3): `well_id` (string), `eur_oil_bbl` (double), `reserve_class` (string) |
|
|
| ### `pressure_depletion.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `production_date` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (3): `well_id` (string), `reservoir_pressure_psi` (double), `flowing_bhp_psi` (double) |
|
|
| ### `production_interruptions.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** (3): `well_id` (string), `event_type` (string), `downtime_days` (int64) |
|
|
| ### `production_timeseries.tsfile` |
| |
| - **Time** (INT64, milliseconds) — the source `production_date` column. |
| - **TAG**: none — the table is stored as a single device. |
| - **FIELD** (4): `well_id` (string), `oil_bbl` (double), `gas_mcf` (double), `water_bbl` (double) |
|
|
| ### `wells_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): `well_id` (string), `basin_name` (string), `formation_name` (string), `completion_date` (string), `lateral_length_ft` (int64), `decline_model` (string), `qi_bpd` (double), `di` (double), `b_factor` (double) |
|
|
| ## Conversion notes |
|
|
| - One TsFile per source CSV (7 tables) for this well decline and pressure 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. |
|
|
| ## 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("artificial_lift_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/oil016-sample`](https://huggingface.co/datasets/xpertsystems/oil016-sample) |
| - Source card title / publisher: OIL-016 — Synthetic Well Decline Curve Dataset (Sample) |
| - License: cc-by-nc-4.0 (as declared by the original dataset). |
|
|
