Insight
Improving Well Availability and Productivity Through AI
A large upstream operator was grappling with inconsistent well performance and suboptimal production in key fields. The company aimed to leverage AI techniques to enhance well availability, streamline interventions, and boost overall productivity.
Maximize well uptime by predicting downtime events or performance declines. Optimize production strategies and operational workflows using data-driven insights.
Machine Learning Models
Deployed predictive algorithms tailored to well conditions, logs, and sensor data (pressure, flow rates, temperature).
Automated Alerts
Configured advanced warning systems for imminent issues like sanding events or sudden drops in pressure.
Centralized Monitoring
Created a single platform for field staff to track real-time well status and recommended actions.
Iterative Model Enhancement
Continuously refined AI models using feedback from well interventions and production outcomes.
Achieved Results
01
Early detection of potential failures reduced downtime events significantly.
02
Adjusting operational parameters in real time enabled a notable lift in daily output.
03
Targeted maintenance eliminated unnecessary shutdowns or blanket maintenance routines.
04
Consolidated analytics provided management with a holistic view of well performance.
The Real-World Challenge That Drove Our AI Breakthrough
Our journey began with a real-world need—something no off-the-shelf solution could fix. This complexity pushed us to design a tailored AI model capable of adapting to unpredictable variables in dynamic environments.
Variation in geological attributes and equipment setups demanded highly customized models.
Legacy data systems lacked standardization, complicating training of AI algorithms.
Field teams required training and motivation to trust AI recommendations over legacy routines.
Approaches
Created consistent data frameworks to feed machine learning models.
Focused on high-priority wells to validate predictive accuracy and gather user feedback.
Established APIs linking well sensors to the AI platform, ensuring live updates.
Updated algorithms based on new intervention results and user input to enhance precision over time.
Benefits & Outcomes
01
Elevated well availability directly contributed to sustained output improvements.
02
Maintenance teams could prioritize high-risk wells, reducing overall costs.
03
Fewer emergency interventions and well-control incidents.
04