Datasets:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
scan = self._scan_metadata(all_files)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
with self._open_reader(file) as reader:
~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
return TsFileReader(file)
File "tsfile/tsfile_reader.pyx", line 364, in tsfile.tsfile_reader.TsFileReaderPy.__init__
File "tsfile/tsfile_reader.pyx", line 367, in tsfile.tsfile_reader.TsFileReaderPy.init_reader
File "tsfile/tsfile_py_cpp.pyx", line 789, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
File "tsfile/tsfile_py_cpp.pyx", line 55, in tsfile.tsfile_py_cpp.check_error
tsfile.exceptions.FileOpenError: 28: Failed to open file
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
OIL-013 — Synthetic Production Time-Series Dataset (Sample) (TsFile)
Apache TsFile version of xpertsystems/oil013-sample.
Overview
A free, schema-identical preview of XpertSystems.ai's enterprise production time-series dataset for decline curve ML, artificial-lift optimization, workover-candidate prediction, and water-breakthrough forecasting. The sample covers 250 wells across 10 global basins and 8 asset types, simulated over 365 days, with 116,154 rows including 91,250 daily production records linked across 11 tables.
- Tables: 11 TsFile table(s), 116,154 rows in total.
artificial_lift: 13,250 rows, 2020-01-14 00:00:00 → 2022-12-25 00:00:00 (UTC)daily_production: 91,250 rows, 2020-01-14 00:00:00 → 2022-12-25 00:00:00 (UTC)downtime_events: 491 rows, 2020-02-04 00:00:00 → 2022-11-24 00:00:00 (UTC)facility_constraints: 200 rows, 2020-01-01 00:00:00 → 2020-01-01 00:00:00.199000 (UTC)flow_assurance_events: 47 rows, 2020-03-20 00:00:00 → 2022-09-09 00:00:00 (UTC)injection_support: 40 rows, 2020-09-06 00:00:00 → 2022-08-10 00:00:00 (UTC)production_allocations: 625 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.624000 (UTC)production_labels: 3,250 rows, 2020-01-14 00:00:00 → 2022-12-21 00:00:00 (UTC)reservoir_pressure: 6,750 rows, 2020-01-14 00:00:00 → 2022-12-25 00:00:00 (UTC)stimulation_events: 1 rows, 2020-09-11 00:00:00 → 2020-09-11 00:00:00 (UTC)wells_master: 250 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.249000 (UTC)
Schema (TsFile structure)
artificial_lift.tsfile
- Time (INT64, milliseconds) — the source
record_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (8):
lift_id(string),well_id(string),lift_type(string),esp_frequency_hz(double),pump_efficiency(double),motor_temperature_f(double),vibration_index(double),runtime_pct(double)
daily_production.tsfile
- Time (INT64, milliseconds) — the source
production_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (16):
prod_id(string),well_id(string),oil_rate_bopd(double),gas_rate_mscfd(double),water_rate_bwpd(double),water_cut_pct(double),gor_scf_bbl(double),choke_size_64ths(double),tubing_pressure_psi(double),casing_pressure_psi(double),uptime_fraction(double),cumulative_oil_bbl(double),cumulative_gas_mscf(double),cumulative_water_bbl(double),anomaly_flag(int64),anomaly_type(string)
downtime_events.tsfile
- Time (INT64, milliseconds) — the source
start_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (6):
event_id(string),well_id(string),downtime_type(string),duration_hours(double),lost_oil_bbl_est(double),root_cause_category(string)
facility_constraints.tsfile
- Time (INT64, milliseconds) — the source
effective_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (7):
constraint_id(string),facility_id(string),field_name(string),throughput_limit_bopd(double),gas_handling_limit_mscfd(double),water_handling_limit_bwpd(double),constraint_severity(string)
flow_assurance_events.tsfile
- Time (INT64, milliseconds) — the source
event_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (8):
flow_event_id(string),well_id(string),flow_assurance_type(string),scale_index(double),paraffin_index(double),sand_index(double),corrosion_risk_index(double),intervention_required_flag(int64)
injection_support.tsfile
- Time (INT64, milliseconds) — the source
record_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (8):
inj_id(string),injector_id(string),producer_id(string),field_name(string),injection_rate_bwpd(double),injection_pressure_psi(double),producer_response_lag_days(int64),correlation_score(double)
production_allocations.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 (6):
alloc_id(string),well_id(string),zone_name(string),allocation_pct(double),allocation_method(string),confidence_score(double)
production_labels.tsfile
- Time (INT64, milliseconds) — the source
label_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (8):
label_id(string),well_id(string),forecast_class(string),workover_candidate_flag(int64),water_breakthrough_flag(int64),steep_decline_flag(int64),lift_limited_flag(int64),next_90d_expected_decline_pct(double)
reservoir_pressure.tsfile
- Time (INT64, milliseconds) — the source
test_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (6):
pressure_id(string),well_id(string),reservoir_pressure_psi(double),bhfp_psi(double),pressure_drawdown_psi(double),pressure_test_quality(string)
stimulation_events.tsfile
- Time (INT64, milliseconds) — the source
event_datecolumn. - TAG: none — the table is stored as a single device.
- FIELD (7):
stim_id(string),well_id(string),event_type(string),frac_stage_count(int64),treatment_volume_bbl(double),expected_uplift_pct(double),actual_uplift_pct(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 (24):
well_id(string),api_like_well_code(int64),field_name(string),pad_id(string),basin_name(string),formation_name(string),asset_type(string),completion_type(string),lift_type(string),operator_class(string),first_production_date(string),lateral_length_ft(int64),proppant_lb_per_ft(double),true_vertical_depth_ft(int64),initial_oil_rate_bopd(double),initial_gas_rate_mscfd(double),initial_water_cut_pct(double),initial_gor_scf_bbl(double),nominal_decline_rate_annual(double),arps_b_factor(double),initial_reservoir_pressure_psi(double),reservoir_temperature_f(double),longitude(double),latitude(double)
Conversion notes
- One TsFile per source CSV (11 tables) for this oil-well production 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 andscada_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.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/oil013-sample - Source card title / publisher: OIL-013 — Synthetic Production Time-Series Dataset (Sample)
- License: cc-by-nc-4.0 (as declared by the original dataset).
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