wangdx25/oil024_sample

OIL-024 — Synthetic Pipeline Flow Dataset (Sample) (TsFile)

Apache TsFile version of xpertsystems/oil024-sample.

Overview

A free, schema-identical preview of XpertSystems.ai's enterprise pipeline flow dataset for hydraulic modeling, leak detection, flow assurance, SCADA telemetry analytics, pump/compressor optimization, and pipeline reliability ML. The sample covers 55 pipelines with 369 segments across 10 pipeline types, 10 fluid families, 10 global regions, and 7 terrain types, with 150,137 rows linked across 12 tables spanning 7 days of 180-minute time- series.

• Tables: 12 TsFile table(s), 150,137 rows in total.
  • compressor_operations: 1,344 rows, 2025-01-01 00:00:00 → 2025-01-07 21:00:00.023000 (UTC)
  • corrosion_erosion: 20,664 rows, 2025-01-01 00:00:00 → 2025-01-07 21:00:00.368000 (UTC)
  • flow_assurance: 20,664 rows, 2025-01-01 00:00:00 → 2025-01-07 21:00:00.368000 (UTC)
  • hydraulic_profiles: 20,664 rows, 2025-01-01 00:00:00 → 2025-01-07 21:00:00.368000 (UTC)
  • leak_detection: 3 rows, 2025-01-03 09:00:00 → 2025-01-03 21:00:00 (UTC)
  • optimization_labels: 20,664 rows, 2025-01-01 00:00:00 → 2025-01-07 21:00:00.368000 (UTC)
  • pipeline_master: 369 rows, 1970-01-01 00:00:00 → 1970-01-01 00:00:00.368000 (UTC)
  • pump_station_operations: 3,752 rows, 2025-01-01 00:00:00 → 2025-01-07 21:00:00.066000 (UTC)
  • scada_telemetry: 20,664 rows, 2025-01-01 00:00:00 → 2025-01-07 21:00:00.368000 (UTC)
  • thermal_profiles: 20,664 rows, 2025-01-01 00:00:00 → 2025-01-07 21:00:00.368000 (UTC)
  • transient_events: 21 rows, 2025-01-01 06:00:00 → 2025-01-07 12:00:00 (UTC)
  • valve_operations: 20,664 rows, 2025-01-01 00:00:00 → 2025-01-07 21:00:00.368000 (UTC)

Schema (TsFile structure)

compressor_operations.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (7): pipeline_id (string), compressor_id (string), suction_pressure_psi (double), discharge_pressure_psi (double), compression_ratio (double), efficiency_pct (double), fuel_gas_mscfd (double)

corrosion_erosion.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (7): pipeline_id (string), segment_id (string), corrosion_rate_mpy (double), erosion_index (double), wall_loss_pct_est (double), leak_probability_score (double), integrity_state (string)

flow_assurance.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (7): pipeline_id (string), segment_id (string), wax_risk_score (double), hydrate_risk_score (double), slugging_risk_score (double), wax_deposition_thickness_mm (double), flow_assurance_state (string)

hydraulic_profiles.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (13): profile_id (string), pipeline_id (string), segment_id (string), pressure_psi (double), downstream_pressure_psi (double), pressure_drop_psi (double), flow_bpd (double), velocity_fps (double), reynolds_number (double), friction_factor (double), flow_regime (string), mass_balance_error_pct (double), event_active (int64)

leak_detection.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (8): leak_id (string), pipeline_id (string), segment_id (string), leak_rate_bpd (double), pressure_signature_score (double), detection_delay_sec (int64), isolated_flag (int64), estimated_loss_bbl (double)

optimization_labels.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (7): pipeline_id (string), segment_id (string), optimization_score (double), failure_risk_score (double), efficiency_grade (string), recommended_action (string), event_type (string)

pipeline_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 (21): pipeline_id (string), segment_id (string), pipeline_type (string), primary_fluid (string), region (string), terrain (string), segment_order (int64), length_km (double), diameter_in (double), wall_thickness_in (double), roughness_mm (double), elevation_start_ft (double), elevation_end_ft (double), material_grade (string), coating_type (string), insulation_type (string), install_year (int64), maop_psi (double), design_flow_bpd (double), pigging_capable (int64), scada_enabled (int64)

pump_station_operations.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (8): pipeline_id (string), station_id (string), rpm (double), efficiency_pct (double), suction_pressure_psi (double), discharge_pressure_psi (double), power_kw (double), cavitation_risk_score (double)

scada_telemetry.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (9): pipeline_id (string), segment_id (string), sensor_id (string), sensor_type (string), signal_value (double), engineering_unit (string), telemetry_latency_ms (int64), quality_flag (string), drift_flag (int64)

thermal_profiles.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (8): thermal_id (string), pipeline_id (string), segment_id (string), temperature_f (double), ambient_temp_f (double), heat_loss_btu_hr_ft (double), thermal_gradient_f_per_km (double), joule_thomson_cooling_f (double)

transient_events.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (7): event_id (string), pipeline_id (string), event_type (string), event_duration_min (int64), operator_response_delay_sec (double), severity_score (double), root_cause (string)

valve_operations.tsfile

• Time (INT64, milliseconds) — the source timestamp column.
• TAG: none — the table is stored as a single device.
• FIELD (6): pipeline_id (string), segment_id (string), valve_id (string), valve_position_pct (double), throttling_state (int64), response_latency_sec (double)

Conversion notes

• One TsFile per source CSV (12 tables); each table is stored as a single device, so the rig / well / tank / equipment / sensor identifiers stay ordinary FIELDs.
• Time = the table's own clock column as INT64 milliseconds (event timestamps, sample or inspection dates, and daily record dates). The clock columns used here are timestamp.
• Tables with no clock column (pipeline_master) use a synthetic row index over their stable source order as Time.
• No column is dropped. Rows that share a timestamp are ordered by a 1 ms step in stable source order, so daily tables keep their exact calendar day.

Usage

Read this dataset with the Java SDK. It is written with the zstd compressor. The Apache TsFile Java SDK reads every compressor, but the Python SDK (pip install tsfile) implements only UNCOMPRESSED, SNAPPY, GZIP and LZ4; opening this file with it yields no rows.

Read a converted file with the Apache TsFile Java SDK (org.apache.tsfile:tsfile):

import org.apache.tsfile.file.metadata.IDeviceID;
import org.apache.tsfile.read.TsFileReader;
import org.apache.tsfile.read.TsFileSequenceReader;
import org.apache.tsfile.read.common.Path;
import org.apache.tsfile.read.expression.QueryExpression;
import org.apache.tsfile.read.query.dataset.QueryDataSet;
import org.apache.tsfile.write.schema.MeasurementSchema;

import java.util.ArrayList;
import java.util.List;

String path = "compressor_operations.tsfile";
try (TsFileSequenceReader sequenceReader = new TsFileSequenceReader(path);
     TsFileReader reader = new TsFileReader(sequenceReader)) {
    // Devices are enumerated as IDeviceID objects. Tables with TAG columns
    // have multi-segment device ids that cannot be rebuilt from their string
    // form, so always use getAllDevices() rather than getAllDeviceIds().
    for (IDeviceID device : sequenceReader.getAllDevices()) {
        List<Path> paths = new ArrayList<>();
        for (MeasurementSchema schema : reader.getMeasurement(device)) {
            String name = schema.getMeasurementName();
            if (name != null && !name.isEmpty() && !name.equalsIgnoreCase("Time")) {
                paths.add(new Path(device, name, true));
            }
        }
        QueryDataSet dataSet = reader.query(QueryExpression.create(paths, null));
        while (dataSet.hasNext()) {
            System.out.println(dataSet.next());
        }
    }
}

Source & license

• Original dataset: xpertsystems/oil024-sample
• Source card title: OIL-024 — Synthetic Pipeline Flow Dataset (Sample)
• License: cc-by-nc-4.0 (as declared by the original dataset).