Client
The client was an oil and gas super major with operations worldwide across the entire energy value chain–upstream, midstream and downstream.
Market Dynamics Driving Change
The energy industry is undergoing a rapid digital transformation. With increasing pressure to optimize production, reduce downtime, and ensure compliance, oil and gas companies are turning to AI and ML to manage vast data volumes and complex operations. This sets the stage for digital transformation initiatives that leverage AI-ML in the energy sector to address core challenges and drive operational efficiency, enhance decision-making, and future-proof production operations workflows.
Business Challenges
The client’s legacy production and data management processes were constrained by several inefficiencies that limited operational efficiency and hindered timely decision-making. Despite the availability of large volumes of production and reservoir data, the absence of integrated tools, automation, and real-time insights created significant bottlenecks across engineering, analytics, and compliance workflows. These challenges collectively impacted productivity, visibility, and overall business agility, as listed below:
Lack of real-time visibility into well performance, especially in JV-operated wells
Limited access to daily allocation data made it difficult to monitor and optimize production effectively. Difficulty in well rate estimation for wells lacking multiphase meters.
Anomaly detection in unconventional wells required intensive manual surveillance
Engineers had to manually scan data to identify underperforming wells, increasing operational overhead.
Difficulty in managing and optimizing unconventional assets
Difficulties due to a high well count, relatively low production rates, rapid decline in production during the first three years of the well (circa 70%), minimal to nil subsurface sensors, and high volume of maintenance activities.
Estimating reservoir pressure is difficult due to rapid declines and limited data
Traditional methods lacked precision, making it hard to forecast inflow performance and plan interventions.
Manual calibration of production networks is time-consuming and error-prone
Engineers had to frequently intervene to adjust models, leading to delays and reduced productivity.
Our Solutions
LTIMindtree implemented four solutions that leveraged AI and ML to surmount the client’s challenges. Solutions enabled production, process and reservoir engineering teams to take swift decisions, instead of spending time in data wrangling and performing manual analysis with minimal to no governance and/or audit trails. These digital solutions empowered existing teams to manage additional oil wells and assets.
800+ Man Hours Saved Monthly – AI-Driven Anomaly Detection for Unconventional Wells
An automated performance-based ranking of 1000+ gas lifted wells coupled with highly intuitive dashboards significantly simplified the tasks such as monitoring challenging wells, reducing downtime and increasing oil and gas production.
Read more
Zero Guesswork: AI-Driven Calibration for Optimized Well Production
Fully autonomous calibration of a production network enhanced several production optimization workflows, and eliminated time-consuming and error-prone manual tasks leading to higher operational efficiency.
Read more
Smarter Wells, Faster Decisions: AI-Driven IPR Estimation at Scale
A better understanding of gas, oil, and water flow from the reservoir into the wellbore helped engineers decide the strategy for lifting fluid to the surface at minimal cost. An advanced fluid inflow performance estimator augmented the accuracy and reliability of artificial lifting-related decisions.
Read more
No More Blind Spots: AI-Driven, Real-Time Well Rate Estimation with ML.NET
A machine learning (ML) model provided early visibility into the oil and gas production rates of non-operating (aka OBO) wells, for improved production forecasting and decision-making to meet corporate targets.
Read moreInsights
Discover how AI-based solutions can transform oil and gas production operations and optimize workflows. Reach out to our experts today.
Contact eugene.comms@ltimindtree.com to know more.
