Predictive Maintenance
48-72 hour advance warning of equipment degradation — fix it before it breaks.
The Problem: Reactive Maintenance Costs More
Most oil and gas operations run on a reactive model: equipment fails, someone notices (hours or days later), a work order is created, parts are sourced, and a crew is dispatched. During that entire window, production is lost.
Scheduled maintenance helps but is inherently wasteful — replacing components on a calendar regardless of actual condition. You either replace too early (wasting the remaining useful life) or too late (after damage has already begun).
The gap between these two approaches is where predictive maintenance lives: using real-time data patterns to identify the exact window when intervention is needed.
How WorkSync Solves It
WorkSync ML models continuously analyze SCADA telemetry across every monitored asset, comparing current behavior against learned degradation signatures. When a pattern match exceeds confidence thresholds, the system generates a predictive alert 48-72 hours before the expected failure window.
Rod Pump Wear
Increasing motor current draw, changing pump fillage patterns, and gradual load shifts indicate rod or downhole pump degradation days before a failure event.
ESP Performance Decline
Intake pressure trends, motor temperature drift, and vibration signature changes reveal bearing wear and impeller erosion before catastrophic failure.
Chemical Injection Drift
Injection rate deviations, tank level anomalies, and corrosion coupon trends signal chemical system issues that lead to scaling, corrosion, or paraffin buildup.
Compressor Degradation
Discharge temperature creep, suction pressure changes, and runtime pattern shifts indicate valve, ring, or packing wear before unplanned downtime.
How It Works in Practice
Scenario: A 200 BOPD rod pump well in the Permian Basin. On Tuesday morning, the WorkSync model detects a subtle increase in peak polished rod load combined with a slight decrease in pump fillage — a pattern consistent with traveling valve wear.
The system generates a predictive alert with estimated time to failure (60-72 hours), economic impact ($14,200/day in deferred production), and recommended action (pull rods, replace traveling valve). The task is automatically scored and inserted into the next available crew work plan.
The crew arrives Wednesday with the right parts and equipment. Total downtime: 6 hours. Without predictive maintenance, the well would have failed Thursday night, sat undetected until Friday's morning report, and been repaired Monday — costing over $42,000 in lost production.