LEVERAGE AI TO INCREASE PRODUCTION, REDUCE COSTS, AND IMPROVE SAFETY IN THE OIL & GAS INDUSTRY
Prevent unique catastrophic accidents
From onshore to offshore to petrochemical to LNG plants, nothing is more crucial for worker safety and continuity of production than predicting and preventing critical and/or catastrophic asset failures before they happen.
With SparkCognition’s machine learning-based predictive analytics, operators get additional insight that will help them avoid unexpected downtime and astronomical costs. In a past deployment, our solution successfully identified 75% of production-impacting events, on an average of 8 days in advance.
Optimize maintenance and respond faster to emergent events
Recurring failures in assets and subcomponents drive 10% or more unexpected downtime annually and cost millions of dollars of lost production.
Our solution gives upstream, midstream, and downstream oil & gas operators invaluable advance warning to plan corrective actions and optimize maintenance scheduling for emergent asset failures—more than doubling previous lead times to address pending failures in some deployments.
Improve efficiency and sustainability through digital transformation
Operational efficiency is critical in the oil and gas industry, and with the exceptional amount of data at hand, there are many opportunities to generate more output.
SparkCognition enables operators to leverage AI and machine learning to dramatically improve productive uptime and efficiency, reduce their carbon footprint, and leverage both predictive and prescriptive insights derived from currently collected enterprise data.
Cutting edge technologies, like AI-based predictive analytics, are key enablers to improving the efficiency of our operations and meeting our ambition to become a net zero company by 2050 or sooner. Working collaboratively with SparkCognition, we have delivered this project in an agile way.
former VP of Transformation,
Upstream Technology at bp
Use case spotlight
Avoiding stuck pipe events with AI for drilling operations
Accounting for billions of dollars annually, drilling anomalies such as stuck pipe significantly threaten the bottom line. This video addresses how drilling operators can future-proof their operations with predictive analytics and machine learning-based modeling.
Learn how a large drilling operator in the Middle East detected 79% of overall drilling anomalies, including stuck pipe events, with up to six hours’ advance notice using AI.
Reduce unexpected downtime
Minimize operational costs
Optimize asset performance
Streamline decision making
Prevent zero-day cyber attacks
Rapidly scale AI
Using unsupervised machine learning techniques with models that adapt and maintain themselves dynamically, SparkCognition solutions scale efficiently for onshore, offshore, FPSO, refinery, LNG, and petrochemical operations.
Use Case Library
During drilling operations, operators may encounter complications related to stuck pipe events. Capable of bringing operations to a halt, stuck pipe is one of the most costly drilling problems in the industry, accounting for billions of dollars annually and up to half of total well cost. Therefore, drilling operators must be able to successfully predict when stuck pipe events may happen and implement mitigation procedures before the event occurs.Read Use Case
Without sufficient lead time in identifying future asset failures, oil and gas operators can only react—and count their losses from halted production and repairs. SparkCognition offers a scalable predictive analytics software solution using AI and machine learning to proactively mitigate equipment failure for oil and gas operations. Our solutions have enabled close to 99% efficiency in past deployments, driving hundreds of millions of dollars in increased annual production output and conserved maintenance costs.Read Use Case