Validate Data Before It Becomes Operational Output
Data Quality Assessment (DQA) reviews operational data as it enters the system and before it is approved. It identifies unusual values, inconsistencies, and common human errors across drilling, cost, and performance records.
Data Checked at Every Stage
DQA runs validation at every critical point in the data lifecycle. No report can be finalized without passing validation.
- During daily data entry
- Inside performance calculations
- During offset research analysis
- Before daily report approval
- Before any report is sent externally
Approval depends on validation.
Automatic Error Detection
DQA flags unusual values, missing data, and logical inconsistencies. Users review flagged values before approval.
Unusual m/day Values
Values outside expected range flagged for review against offset benchmarks.
Cost Anomalies
Unexpected cost entries identified against AFE and historical averages.
Incorrect Depth Entries
Depth values validated against directional surveys and previous records.
Missing or Duplicate Records
Gaps and duplicated entries detected across daily and technical reports.
Logical Inconsistencies
Cross-field validation catches conflicting or impossible data combinations.
Validation Before Release
DQA executes automatically before critical system actions. This protects data accuracy before internal decisions or external distribution.
- Daily drilling report approval
- Performance reporting
- Supervisor scoring updates
- External exports
Preserve Data Integrity Across Projects
DQA helps operators maintain accurate, trustworthy data across every project and reporting discipline.
Accurate data supports consistent decision-making.
Activate the DQA Module
Pre-approval validation. Automatic error detection. Structured audit trail. Data you can trust.
Book a DQA Demo