Real operators. Real results.

Real operator use cases across just 3 models showcase $4M in value over 6 months. Each model finds issues hours or days before they occur.

Tasq detected pre liquid loading signatures across 50 events per month, giving operators 31 hours of lead time before alarm threshold.

Paraffin build in tubing detected 8 days ahead of production variance. 10 events per month identified across gas lift wells.

Tasq automated detection found between 1.5x and 4x more dump valve failure events than manual logging captured.

15 plugged choke events per month detected 40 hours before alarm. Value: $8,333 to $12,667 per detection.

Tasq sends setpoint recommendations that are instant value with low human effort. 68% setpoint jobs, 32% equipment. 90% model accuracy. +15% normalized oil production post Tasq.

15% production increase on optimized subset. Through better models to identify and recommend work, operations is positively impacted. Cycle time down 25%, deferment down 15%, work reduction 20 to 50%, automating 1 FTE of downtime.

Learns from optimal setpoints through clusters, projections, and limits. 94% reduction in work. Line pressure events increased production by 23% on the most unreliable pads. Results decreased well visits and CygNet touches.

Core models validated by engineers vs internal surveillance. 5 models built and deployed by client: plunger behavior, casing rising on GL, gas lift circulating, injection setpoint drift, injection setpoints to compressor output. Additional 1,500 BOE/day (3x) in uncovered opportunity.

Recommendations are instant value with low human effort. Results validated by field. 56 BOPD increase across 19 wells. High line pressure events identified and resolved.

Trial result Q4 2022. Optimization model on 30 wells, deferment model on 300 wells. 14% uplift on 30 wells. 30% deferment reduction across 500 wells equating to reducing from 38 mmcfd to 31 mmcfd for the year.