Optimize hydrocarbon production at scale and minimize production costs

Key Capabilities

AI-based virtual meters anywhere

AI-based virtual meters anywhere

AI-based virtual meters anywhere

  • Leverage machine learning algorithms to generate virtual metering predictions for any state (e.g., flow rate, pressure, temperature) across the network
  • Model each individual well, flow line, and manifold with their unique characteristics
  • Complement physical sensors and physics-based models with AI-enabled meter estimates across the production network
Multi-phase flow rates predictions

Multi-phase flow rates predictions

Multi-phase flow rates predictions

  • Back allocate production to individual wells by accounting for multi-phase hydrocarbon production that changes over time
  • Provide probability distribution and confidence intervals to gauge inaccuracies
  • Tune the machine learning models to accommodate any level of operations complexity (e.g., natural- or artificial-lift, oil, gas, emulsion, SAGD, comingled wells)
Holistic yield optimization of artificial lift and injection wells

Holistic yield optimization of artificial lift and injection wells

Holistic yield optimization of artificial lift and injection wells

  • Leverage “Capacitance Resistance Modeling” (CRM) to quantify the relationship between producers and injectors, and tune injection parameters
  • Combine ML models with physics-based Baker Hughes ProductionLink™ to optimize artificial lift strategy
  • Interpretable AI insights provide visibility into major drivers
Agile, continuous and stochastic hybrid models

Agile, continuous and stochastic hybrid models

Agile, continuous and stochastic hybrid models

  • Interoperate AI and in-house or third-party simulation models to unlock larger value
  • Enable real-time decision making, automated calibration of physics-based model parameters and process control with fast computational time and initial set up
  • Enable uncertainty quantification through Bayesian analysis and variational inference
AI-based hydrocarbon production forecasting

AI-based hydrocarbon production forecasting

AI-based hydrocarbon production forecasting

  • Leverage deep learning to estimate production and deviations between forecast, actual, and target production
  • Model each production well, pad and field with the underlying technologies and formation characteristics
  • Prepare for the future by factoring in real-time and periodic production data as well as simulator data
Unified, integrated, and OSDU-compliant

Unified, integrated, and OSDU-compliant

Unified, integrated, and OSDU-compliant

  • Create a single unified view of the production operations integrating all internal and external data (e.g., surface network models, SCADA systems, wellbore data, well test data, production models and simulators, market data)
  • Benefit from OSDU interfaces and APIs built in the application to facilitate data exchange through O&G-specific data access and exposition standards
Download BHC3 Production Optimization Data Sheet

Scope

BHC3 Production Optimization can be deployed to any hydrocarbon production operations.

Scope

Global, regional, local​

Daily, weekly, monthly time horizon

Planning

Execution

AI-Insights and Optimization

Virtual sensors

Injection profiles

Artificial lift set points

Bottlenecks

Production deferments

Upstream Production

Onshore

Offshore

Multi-phase

Natural-lift

Artificial-lift

Benefits for Application Users

Data and Architecture


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