Advance analytics for Production Forecasting and Cost Optimization

Challenge Summary

To create a Intelligent AI/ML based tool to capture the data from different sources and replace the conventional process of production forecasting and cost optimisation that is reliant on a skilled workforce which is often error-prone & inefficient with higher risk to the project timeline and the overall cost.

Challenge Scenario

Oil & Gas companies have been collecting vast amounts of data related to production, reservoir, temperature & pressure history, and other operational parameters. To realize better Oil production a Machine learning system can be leveraged to predict anomalies and down-time. The system should assimilate data from hundreds of variables to find patterns, with data-driven models that continuously learn and improve from new data and provide solutions for any changes in well requirements and drilling capabilities such as increased depth, directional drilling, extended lengths, and higher pressure and temperature, etc.

Profile of the End-User

Engineering Teams

Reservoir & Production Team

Facility Managers

Functional Requirements of the End-User

  • Automate predictive interpretation of drilling data to identify and mitigate risks
  • Digital planning to increase collaboration between departments such as Engineering, and Reservoir, etc.
  • Conduct what-if scenarios that affect production forecasting
  • Make the decline curve analysis process more accurate and realistic.

Functional & Operational Capabilities

  • Predict failure and suggest control measures to decrease downtime
  • Evaluate machinery performance to create an effective maintenance strategy
  • Simulate well operations to uncover hidden productivity gains
  • Seamlessly integrate data from multiple sources into daily workflows, making the process highly efficient and still offering ample flexibility to change in the future.

Operational constraints

  • This innovative system should benefit the operations team (in charge of maintaining and running field equipment to produce wells) who are highly dependent on reservoir and production teams to advise them on lift strategies or production optimization. Thereby, automate the entire modeling and forecasting process, reservoir engineering teams can integrate day-to-day field conditions, real-time data from production facilities.

Expected Tangible Benefits and Measurable Gains

  • Prescriptive analytics for Well Completion Optimization in Unconventional Resources
  • Instant Visualisation and Simulation of upcoming activities
  • Customised reports on location/activity level
  • Risk management with mitigation measures

Performance Metrics or Outcomes

  • Savings in well completion cost while maintaining similar production levels
  • Reduction in planning time due to an integrated planning platform
  • Forecast Project Cost and Time Overruns
  • Efficient report of Field Economics for well informed Investment decisions