Big Data-Powered Machine Learning for Operational Excellence: A Case Study Analysis for Oil & GasAbstract Drilling and workover operations represent a crucial part of a well lifecycle in terms of deliverability and economics....
Statistical Machine Learning for Intelligent OperationsAbstract Digitalisation in its various shapes of artificial intelligence, machine learning or big data analytics is slated to add...
How To Accelerate Intelligent Automation Adoption In The Oil And Gas Industry?With assets that are often located in remote and hostile environments, it is essential to have reliable and efficient methods for...
Future-Proofing Asset Management With Predictive MaintenancePredictive maintenance is an important tool that can help oil and gas conglomerates to improve asset reliability, reduce costs, and...
The futuristic customer-led model powered by digital twinsAI and automation form the backbone of digital twins. By feeding the digital twin with data, enterprises can test the physical...
Re-imagining future product development with intelligent automation and digital twinsEnterprises must leverage intelligent automation and AI to fuel digital twins with modelling and data to reshape the future of the...
Why should oil and gas enterprises embrace the digital twin technology? Globally, leading oil and gas companies are strengthening their frameworks to increase resilience and agility, by leveraging automation....
53% growth of intelligent automation in the oil and gas industryThe majority of oil and gas companies globally are distressed with their current manual operating systems. Businesses are implementing...
3 stages of an enterprise automation program lifecycleThere are clear guidelines that help companies prepare for their automation projects and leverage sustainable competitive advantage by...