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Data Preprocessing Module

DrillAI’s Da Preprocessing Module cleanses and structures raw drilling telemetry into trustworthy datasets in minutes rather than days. It automatically detects and isolates each operation phase—drilling, making connections, reaming—so downstream models train on context‑specific signals. Proprietary AI routines then filter out vibration noise, correct sensor drift, and excise outliers that could otherwise skew analyses or trigger false alerts. Every data point is enriched with metadata (phase ID, timestamp, quality flag) and follows a uniform schema, enabling plug‑and‑play integration with analytics pipelines. As your fleet and sensor suite grow, the module scales seamlessly without adding headcount, delivering near real‑time insights that accelerate decision‑making and boost model accuracy.

 

Key Features:

 
  • Drilling Operation Detection: Auto‑tags each record with its corresponding drilling phase.
  • AI‑Powered Noise Filtering: Deep‑learning filters remove micro‑oscillations while preserving true events.
  • Sensor Drift Correction: Online detectors recalibrate biased sensors using redundant data channels.
  • Anomaly Handling: Flags or removes outliers based on configurable confidence thresholds.
  • Structured Output: Uniform table (timestamp, depth, WOB, RPM, phase ID, quality) ready for ML.