THULab/oil016_sample

OIL-016 — Synthetic Well Decline Curve Dataset (Sample) (TsFile)

Apache TsFile version of 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:

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
• Source card title / publisher: OIL-016 — Synthetic Well Decline Curve Dataset (Sample)
• License: cc-by-nc-4.0 (as declared by the original dataset).