production-surveillance

To diagnose well performance changes, you can analyze SCADA, historian, and test-separator time-series data exported as CSV or spreadsheets. The system processes rates, pressures, temperatures, and lift parameters to identify production anomalies and rank intervention candidates.

Identifying liquid loading and artificial lift underperformance involves analyzing daily production CSV exports of wellhead pressures, flow rates, and plunger cycles. The system pinpoints constraints and diagnoses specific issues like slugging or lift underperformance to recommend next diagnostic steps.

Yes, you can use spreadsheet histories of choke settings and compressor data for production surveillance. The analysis processes these local time-series parameters to identify bottlenecks in compression or surface facilities and pinpoint constraints affecting well performance.

Ranking wells for intervention requires processing test-separator results and daily rate histories to detect performance degradation. The system evaluates production drops and artificial lift parameters to prioritize candidates with the highest potential for improvement.

No, you do not need a specific database connection to run anomaly detection. The system processes local time-series data directly from CSV files or spreadsheet exports containing your rates, pressures, temperatures, and lift parameters.

Production surveillance analysis shows unexpected drops in wellhead pressures and flow rates by identifying anomalies in time-series data. It diagnoses underlying causes such as slugging, liquid loading, compression constraints, or artificial lift underperformance.