A mid-sized independent exploration & production (E&P) company was struggling with inconsistent well performance across its shale assets. Real-time data lived across multiple systems—SCADA, historian, production accounting—forcing engineers to manually stitch together spreadsheets and reports. Field teams lacked actionable visibility into underperforming wells, impacting both production volumes and lease operating expenses (LOE). Leadership needed a unified and predictive approach to optimize well performance and reduce operational inefficiencies.
Frame stepped in and helped the E&P achieve measurable and sustained improvements in production performance, asset reliability, and operational efficiency, including:
Improved artificial lift performance through data-driven tuning
Reduction in manual engineering effort, enabling focus on higher-value analysis
Real-time visibility into production anomalies and optimization opportunities
THE SITUATION: The operator managed a diverse portfolio of horizontal wells with varying decline curves, lift systems, and equipment conditions. Operational data was siloed, making it difficult to identify anomalies, anticipate failures, or correlate surface and subsurface behavior. Manual workflows slowed decision-making and delayed interventions. Without a scalable architecture or real-time intelligence layer, production engineers were unable to proactively manage degradation, leading to increased downtime and lost recovery potential.
THE PROBLEM: The E&P faced significant data visibility and operational challenges that limited its ability to optimize production and act proactively, including:The operator managed a diverse portfolio of horizontal wells with varying decline curves, lift systems, and equipment conditions.
Fragmented subsurface, surface, and production datasets
No unified view of well performance or anomaly detection
Manual workflows that slowed interventions and decision-making
Limited predictive insight into well degradation, artificial lift issues, or choke optimization
Lack of scalable architecture to support real-time production analytics
The Frame Solution
We deployed a modern, cloud-native production optimization platform that unified critical data sources, enabled real-time surveillance, and delivered predictive insight to engineers and field teams. Our solution combined subsurface subject matter advisor’s, strong data engineering, ML modeling, and GenAI-driven operational intelligence.
Unified SCADA, historian, and production accounting data into a Lakehouse architecture
Implemented real-time well surveillance dashboards with anomaly detection
Developed predictive models to identify wells at risk of decline before impact
Enabled early-warning alerts for lift performance deviations and equipment issues
Delivered GenAI-enabled field insights to assist supervisors and engineers with faster root-cause identification
