Realtime Optimization

Production Optimization is the continuous orchestration of the production operation to deliver the target business outcomes (objective functions) without violating the process constraints. The most common goals are maximizing asset value, minimizing cost, maximizing throughput or increasing ultimate recovery.

Realtime Optimization overcomes multiple challenges

  • Optimization is performed on ad-hoc basis only when targets are not met
  • Optimization is only performed within operational silos, and not across entire operation breadth
  • Optimization requires a lot of preparation and is therefore very time consuming
  • Model creation, maintenance and calibration with the operational reality of the asset is difficult
  • The recommendations from optimization are not translated to field action
  • The outcomes are not continuously monitored and feedbacks are not captured to improve the optimization cycle

The benefits of Realtime Optimization

  • Continuous production optimization through automated and integrated processes delivering value throughout the production operation life cycle
  • Holistic approach to maximize the asset value and at the same time delivering the operational objectives like increase production, minimize operating costs, reduce energy consumption, etc
  • Leverages existing models and adopt fit for purpose tools including proxy and data driven models to provide solutions that are easy to create and maintain
  • Tight integration with operations through automated workflows to execute recommendations and achieve results
  • Continuous monitoring and feedback capturing to finetune the optimization process.

What defines IPCOS Realtime Optimization?

  • IPCOS Digital Asset Optimization is comprehensive, integrated and frequent. We bring the holistic optimization approach where you can select the target business outcomes. We orchestrate the integrated process model that will simulate and provide recommendations to achieve the objective outcomes
  • IPCOS Digital Asset Optimization is automatic: Optimization workflows typically run complex algorithms, processing data from all over the asset. To make this sustainable, workflows need to be automated as much as possible and the loop needs to be as closed as possible. While human intervention is allowed, it should only be by exception
  • IPCOS Digital Asset Optimization honors constraints from all disciplines: While maximizing optimization objectives, the optimization workflows needs to honor constraints from production, maintenance, surface facilities and other operational limitations. This will ensure the results are practically achievable in the asset.

Best practices

  • Manage business objectives and constraints centrally, consistent and accepted across the organization; and define clear process and accountability for maintaining and modifying them
  • Integrate engineering and operational workflows within the optimization process to ensure the recommendations are translated into operational actions
  • Design the optimization models and process with sufficient parameterization and process configurability, that will allow to accommodate future tuning, and easily managed by the end user.
  • Capture feedback from the field and continuously iterate the optimization process reconciling the asset reality into the process.