Overview
As the oil and industry faces growing operational complexity and pressure to optimize production, legacy methods for calibration of complex production networks are no longer
adequate. The client needed an innovative solution to automate the
calibration of complex production network models. They partnered with LTIMindtree to transform their
manual calibration workflows into a streamlined, automated and autonomous
operation.
LTIMindtree’s Solution
LTIMindtree developed and implemented an automated, autonomous oil and gas production network calibration solution for the client to overcome the challenges of their manual, legacy system. Key aspects of the solution included:
Autonomous Production Network Calibration
LTIMindtree deployed the PSwarm algorithm integrated with Petroleum Experts’ Production Optimization Suite to automate calibration of complex production networks.
Production Gap Minimization Engine
A solution designed to consistently reduce the gap between actual and expected production increments by leveraging advanced optimization techniques and real-time feedback loops.
Multi-Constraint Optimization Algorithm
Developed an intelligent algorithm capable of navigating complex network, multi-constraint target functions to identify and implement optimal solutions efficiently.
Scalable Scenario Processing Framework
Cluster management and distributed computing capabilities enabled parallel processing of multiple scenarios, accelerating network calibration and allowing for more frequent updates.
Real-Time Data Integration Platform
An automated and continuous integration layer that connected real-time systems with other systems of record (SORs), ensuring timely and accurate collection of field and well data.
Tech Stack and Architecture
Benefits
Conclusion
LTIMindtree’s AI-powered calibration solution, built on the PSwarm algorithm and integrated with PETEX, helped the client automate one of the most time-consuming and complex tasks in subsurface operations. It enabled real-time rate predictions, improved model accuracy, reduced model-to-field errors, and saved over 1,800 hours per field annually. The solution’s scalable, data-driven architecture accelerated decision-making across joint venture-operated wells and drove better production outcomes. This case underscores how AI and intelligent automation can modernize core workflows in oil and gas, setting a new benchmark for operational excellence in the energy industry.
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.
