Case Study: Reservoir & Well Diagnostics with ML
Client Challenge: Mature onshore oil field with declining rates and rising water cut. Conventional well tests were slow, inconsistent, and inconclusive and there was uncertainty on reservoir connectivity and well performance drivers
Solution: Integrated production, well test, and surveillance data. Applied ML clustering to group wells by performance patterns.Used anomaly detection to identify wellbore damage & flow restrictions. Built ML-assisted reservoir connectivity map using tracer & pressure data.
Key Insights: Early water breakthrough in 3 producers linked to high-perm streaks. 2 wells identified with completion damage restricting inflow. Undeveloped southern zone with missed recovery potential.
Impact Delivered: +8% forecasted recovery factor over 5 years. 60% faster diagnostics vs. conventional workflows. Reduced intervention costs with targeted workovers & restimulation. Data-driven roadmap for field-wide production optimization.
More Case Studies Available on request