Sub surface ops
Digital Twins for
Production Optimization
Simulate, predict and optimize every stage of your asset lifecycle with live, physics-powered replicas
Role-play “what-if” scenarios
Our Digital Twin solution fuses multiphase flow, thermodynamics and reservoir‐decline physics with 2 million+ real-time SCADA and IoT streams, enabling production, flow-assurance and reservoir teams to run “what-if” scenarios, automate sensitivity sweeps and deliver actionable recommendations within hours.
Benefits
- 7%
Uplift
7% average uplift in field production rates via optimized gas-lift schedules - 25%
Reduce
25% reduction in flow-assurance incidents through hydrate- and slugging-mitigation scenarios - 30%
Improve
30% faster scenario-turnaround (from days to hours) with automated batch-runs
Implementation Roadmap & Timeline
Phase 1: Pilot & Model Validation
(0–10 weeks)
(0–10 weeks)
- Assemble reservoir & production data (PVT, well logs, SCADA).
- Build initial twin for a single well pad or platform processing train.
- Validate model outputs against 3 months of historical KPIs.
Phase 2: Scale & Feature Expansion
(11–24 weeks)
(11–24 weeks)
- Extend twin to upstream cluster or midstream pipeline segment.
- Integrate automated sensitivity sweeps (e.g., gas-lift pressure, choke settings).
- Deploy hybrid ML + physics inference engine for anomaly detection.
Phase 3: Enterprise Rollout & Continuous Optimization
(25–40 weeks)
(25–40 weeks)
- Full-fleet twin deployment (across multiple fields or facilities).
- Establish MLOps pipelines for retraining every 30 days.
- Quarterly steering-committee reviews to refine scenarios and run new optimization campaigns.
Request a detailed Digital Twins implementation roadmap to plan your pilot today
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Key Modules
-
Physics-Informed Simulator
Multiphase flow, heat-transfer and reservoir decline models calibrated with PVT and core-analysis data -
Live Data Connector
PLC/SCADA, OSIsoft PI System and Azure IoT Hub integration for sub-second data sync -
Scenario Manager
Automated batch-run of “what-if” cases (hydrate mitigation, compressor shutdown sequencing) -
Optimization Advisor
AI-driven parameter sweeps with Bayesian and evolutionary algorithms -
Mobile Cockpit & Control-Room Dashboard
Custom war-room UI and tablet-friendly views for on-shift engineers
Integration Capabilities
Edge & Cloud Deployment
Containerized twin on Kubernetes at offshore control rooms or hybrid-cloud on Azure/AWS
MES/SCADA & ERP Links
Native connectors for Honeywell PHD, Emerson DeltaV, SAP PM and Infor EAM
Mobile & Remote Access
Secure tablet app with read-only offline mode and auto-sync when connectivity returns
Subtasks Addressed
- Gas-lift schedule optimization and choke-setting recommendations
- Flow-assurance troubleshooting (hydrate, slugging and erosion risk analysis)
- Production-forecast comparison and variance analysis
- Data Governance & Security: Model data lineage, role-based access, audit logging, ISO 27001 and NERC CIP compliance
Training and Change Management Support
We provide onsite and virtual workshops for operations, maintenance and IT teams
-
Hands-On Workshops
Reservoir engineers and production techs run live scenario exercises -
Train-the-Trainer Program
Certify internal champions to scale modeling best practices -
Ongoing Clinics
Quarterly model-retraining clinics and optimization strategy sessions -
24/7 Expert Helpdesk
Dedicated support for tuning physics parameters and interpreting results
Expanded KPIs
- Scenario Turnaround Time: Hours per scenario vs. days manually
- Forecast Accuracy: % deviation between predicted and actual production
- Model Retraining Cadence: Days between retrains to incorporate new data
- Operational Uptime Impact: % reduction in unplanned stoppages attributable to twin insights
Ready to transform your production operations with real-time digital twins?
Frequently Asked Questions
We compare model outputs to 90 days of historical SCADA KPIs and run continuous back-tests to ensure < 5% deviation.
Yes, our simulator supports cluster-level models incorporating well interference, network hydraulics and compressor stations.
Built-in anomaly filters flag sensor drift; edge-buffering holds up to 72 hours of data with auto-ingest after restoration.
Our platform’s open SDK lets your domain experts plug in proprietary decline-curve or PVT modules.
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